U.S. Geological Survey

The U.S. Geological Survey (USGS) is both a user and a provider of remotely sensed data. The USGS manages the Landsat satellite series and a Web-enabled archive of global Landsat imagery dating back to 1972. The entire Landsat archive became available for download at no charge in December 2008, and more than 40 million Landsat scenes have been downloaded by the user community to date. The USGS also distributes aerial photography through The National Map, and archives and distributes historical aerial photography, light detection and ranging (lidar) data, declassified imagery, hyperspectral imagery, data collected by Unmanned Aircraft Systems, and imagery from a variety of Government, foreign, and commercial satellites. These data are used for a wide variety of applications such as mineral resource development, monitoring the health of U.S. and global ecosystems, land use change, emergency response, and assessments of natural hazards such as fires, hurricanes, earthquakes, droughts, and floods.

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Arctic Studies

Alaska LandCarbon Permafrost

High-latitude systems are experiencing climate change at faster rates than the rest of the globe.  Warming temperatures could have dramatic effects on two important high-latitude ecological features: permafrost and soil organic thickness.  Near-surface permafrost has a huge effect on surface and subsurface water flows and also sequesters carbon, which could become vulnerable to atmospheric emission with permafrost melting and degradation.  A thick soil organic layer constitutes an important carbon stock and an important ecological driver: it insulates permafrost from warming effects and favors forest long-term succession toward spruce forests. Thin soil organic layers, which are often a consequence of wildfires, facilitate permafrost degradation and a progression toward long-term, predominantly deciduous (birch and aspen) forests. 

These two ecological drivers, permafrost and soil organic layer thickness, are often crudely mapped because the belowground features are hard to quantify across the landscape. USGS researchers are addressing this data gap by leveraging regression tree and decision tree data mining algorithms to derive complex mapping algorithms driven by Landsat imagery, elevation and derivatives, climate, surface geology, and other spatial data. Reference data consist of soil survey pedon data, shared soil data, and collected soil observations in rural Alaska.  Various map products have been produced for the Yukon Flats ecoregion (active layer thickness – maximum thaw depth), the Yukon River Basin (soil organic layer thickness and near-surface permafrost), and Alaska-wide (soil organic layer thickness and near-surface permafrost).  As part of a successful National Aeronautics and Space Administration (NASA) Arctic-Boreal Vulnerability Experiment (ABoVE) proposal, USGS resouces will be used to 1) produce more localized permafrost maps in project intensive study sites, 2) extend permafrost mapping into northern Canada, and 3) use electrical resistivity tomography transects to quantify localized permafrost dynamics, understand fire impacts of permafrost, and improve postfire permafrost and soil organic layer mapping. 

This project contributed to the LandCarbon Alaska national assessment publication, leading Chapter 3, which assessed available spatial products of soil carbon and permafrost for consistency and agreement with process-based estimates across Alaska. The quantitative modeling approach generated regional near-surface permafrost maps that provide essential information for resource managers and modelers to better understand near-surface permafrost distribution and how it relates to environmental factors and conditions.

URL  http://lca.usgs.gov/lca/alaskapermafrost/index.php

Near-surface permafrost (within 1 m of the surface) and prediction confidence for Alaska.

Near-surface permafrost (within 1 m of the surface) and prediction confidence for Alaska.

Sensor: Multispectral (approx. 4-12 bands)

Platform: Satellite

Author: Bruce Wylie
Email: wylie@usgs.gov
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Alaska Permafrost Mapping with Landsat

Soil carbon and permafrost are important drivers of future greenhouse gas emissions and vegetation communities.  Accurately quantifying the magnitudes and spatial distribution of these soil properties is non-trivial because they are belowground characteristics that are not evident from the surface and they are heterogeneous in nature. As part of the USGS Alaska LandCarbon assessment, USGS scientists, in collaboration with other scientists, developed a series of soil carbon and permafrost maps for Alaska. This research also evaluated modeling results of the Dynamic Organic Soil version of the Terrestrial Ecosystem Model (DOS-TEM), which uses input data on soil texture, land cover, historical climate, historical fire, historical forest harvest, and model projections of future climate, fire disturbance, and forest management to estimate changes in ecosystem pools and fluxes.

Soil carbon and permafrost parameters from different map products were compared across 23 of Alaska’s major ecotypes.  Average ecotype values from each soil characteristic were then compared to products from the DOS-TEM model. Agreement between DOS-TEM estimates and best estimates of current conditions built confidence in future predictions made with this model.  DOS-TEM estimates fell in the range of mapped product estimates for total organic carbon (31–72 petagram versus 45 petagram), percent of area with near-surface permafrost (36–67% versus 44%), and percent of area with organic or peat soils (6–24% versus 18%).  DOS-TEM was only slightly outside of the observed product range for active layer thickness or maximum thaw depth (76–84 cm versus 86 cm). 

The data were then used to construct a rank-based index of susceptibility to changing climates based on permafrost vulnerability to degradation, organic layer susceptibility to fire, greenhouse gas emissions, and thawed carbon from permafrost.  For each ecotype, the product means were averaged across map products to produce a single multi-product mean related to susceptibility.  The susceptibility map highlights the expected sensitivity of tundra systems in western and arctic ecoregions to changing climates.  Interior Alaska also has patches of moderate to high susceptibility.

Information obtained from multiple permafrost and soil carbon map products is useful for validation or as an input into models predicting future carbon emissions, hydrology, and vegetation communities.  In addition, ecotypes with high mapping uncertainty or those with significant disparity with process-based model predictions identify areas where further studies or field data may be needed.  The soil susceptibility map may also help identify areas in need of model refinement and should be informative for land use managers and agencies.

Wylie, B.K., Pastick, N.J., Johnson, K.D., Bliss, N.B., and Genet, H., 2016, Soil carbon and permafrost estimates and susceptibility to climate change in Alaska, chap. 3 in Zhu, Z., and McGuire, A.D., eds., Baseline and projected future carbon storage and greenhouse-gas fluxes in ecosystems of Alaska: U. S. Geological Survey Professional Paper 1826, 196 p., http://dx.doi.org/10.3133/pp1826.

Overall soil susceptibility index (based on greenhouse gas emission, burning, and permafrost thaw) for major Alaska ecotypes.  White areas on the map have low susceptibility.

Overall soil susceptibility index (based on greenhouse gas emission, burning, and permafrost thaw) for major Alaska ecotypes.  White areas on the map have low susceptibility.

Sensor: Multispectral (approx. 4-12 bands)

Platform: Satellite

Author: Bruce Wylie
Email: wylie@usgs.gov
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Hyperspectral Remote Sensing to Characterize Mineral Resources in Alaska

Alaska is a major producer of base and precious metals and has a high potential for additional undiscovered mineral resources. However, discovery is hindered by Alaska’s vast size, remoteness, and rugged terrain. Hyperspectral remote sensing is one method that can be used to rapidly acquire data about the distributions of surficial materials, including different types of bedrock and ground cover. The USGS is conducting the Alaska Hyperspectral Project to assess the applicability of this technology in Alaska (http://minerals.usgs.gov/science/hyperspectral-AK-mineral-deposits/). The primary study area is a remote part of the eastern Alaska Range where porphyry deposits are exposed.

This project applies an integrated approach that combines spectroscopic measurements with field- and laboratory-based geologic investigations. Hyperspectral data (also known as imaging spectrometer data) have been collected at the following scales: (1) regional, (2) outcrop, and (3) hand specimen. The regional airborne survey, conducted over 2 days, used the HyMap(TM) sensor and captured the spectral characterization of surface materials across an extensive area (1,900 km2) at 6-m resolution. A ground-based outcrop-scale survey done with the hand-held HySpex(TM) sensor provides higher spatial resolution mineral mapping over a kilometer-scale hillside at 30-cm resolution. The most detailed data were collected at 500-μm spatial scale on individual rock samples in the laboratory using Corescan’s Hyperspectral Core Imager Mark III(TM) imaging spectrometer. Analyses of these measurements reveal complex spatial relations of minerals. The hand specimen and outcrop results are used to improve interpretations of the regional hyperspectral dataset.

The hyperspectral surveys provide key pieces of information. Mineral classification maps show the predominant minerals for each spectrum. The USGS has taken steps to extract even more information from the spectral data by developing methods to determine qualitative abundances of the predominant minerals across the survey area. Subtle changes in the shapes of spectral features are also being examined to map differences in the chemical composition of select minerals. Variations in rock type are generally reflected by relative abundances of predominant minerals and observed compositional differences of some minerals . In this study area, muscovite spectral features are empirically observed to change with proximity to porphyry copper deposits.

http://minerals.usgs.gov/science/hyperspectral-AK-mineral-deposits/

Regional mineral classification map overlaying a digital elevation model of the Orange Hill area, Wrangell–St. Elias National Park and Preserve, Alaska. Colors represent the spectrally dominant minerals. Data collected at 6-m spatial resolution.

 Regional mineral classification map overlaying a digital elevation model of the Orange Hill area, Wrangell–St. Elias National Park and Preserve, Alaska. Colors represent the spectrally dominant minerals. Data collected at 6-m spatial resolution.

Sensor: Hyperspectral

Platform: Airplane, Ground based / sensor web / web cam

Author: Raymond Kokaly
Email: raymond@usgs.gov
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Sea Ice Decline, Permafrost Thaw, and Benefits for Geese in the Alaskan Arctic

Global warming is rapidly thawing permafrost along the Arctic Coastal Plain of northern Alaska, with a cascading effect that results in coastal subsidence, inundation by salt water, and subsequent changes to habitat distribution and quality.  As part of the USGS Changing Arctic Ecosystem Initiative, scientists at the Alaska Science Center are using WorldView-2 and -3 satellite imagery to map changes taking place to goose “grazing lawn” (GL) habitat (http://pubs.usgs.gov/fs/2014/3088/).  In the figure, the class “GL  Transition” represents tundra recently dominated by freshwater graminoids that has subsided and is changing into habitat dominated by salt-tolerant species (GL Dense, Moderate, and Sparse). These new GL habitats are preferentially grazed by some avian herbivores and  appear to benefit the energetic and reproductive success of several species of geese.  Habitat maps are being created using all 8 WorldView spectral bands, plus two derived bands (Normalized Difference Vgetation Index(NDVI) and Red Edge NDVI) in proven classification algorithms.  The USGS is establishing the location and areal extent of salt-tolerant graminoid habitats across the full extent of the Arctic Coastal Plain (Point Barrow east to Oliktok Point).  These maps complement ongoing research to 1) estimate the biomass and nutrients available to waterfowl in salt-tolerant graminoid habitat, 2) plan for the location of coastal subsidence, inundation, and habitat change monitoring stations, and 3) retroactively analyze and forecast future coastal habitat change for Department of Interior management agencies and local governments and residents.

http://alaska.usgs.gov/science/interdisciplinary_science/cae/index.php

WorldView-2 map imagery showing the study site on the Arctic Coastal Plain of Alaska, and detailed perspectives of the study area. The class GL (grazing lawn) Transition in the middle left image represents tundra recently dominated by freshwater graminoids that has subsided and is changing into habitat dominated by salt-tolerant species (GL Dense, Moderate, and Sparse).

WorldView-2 map imagery showing the study site on the Arctic Coastal Plain of Alaska, and detailed perspectives of the study area. The class GL (grazing lawn) Transition in the middle left image represents tundra recently dominated by freshwater graminoids that has subsided and is changing into habitat dominated by salt-tolerant species (GL Dense, Moderate, and Sparse).

Sensor: Multispectral (approx. 4-12 bands)

Platform: Satellite

Author: John Pearce
Email: jpearce@usgs.gov
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Using Repeat Airborne Lidar and Landsat to Quantify Arctic Tundra Fire Impacts

Wildfire disturbance is an important factor contributing to ecosystem and landscape changes.  The impact of fires on permafrost-influenced terrain in boreal forest regions is well documented; however, the role of fires in initiating thermokarst development in arctic tundra regions is poorly understood.  Rapid climate change at high latitudes has increased interest in the spatial and temporal dynamics of thermokarst and other permafrost thaw-related features in diverse disciplines including landscape ecology, hydrology, engineering, and biogeochemistry.  As a result, there is an urgent need to develop new techniques and tools to observe and quantify changes to near-surface permafrost terrain. 

Remote sensing provides a means for documenting and quantifying many of the changes now occurring on arctic landscapes.  In particular, application of multitemporal airborne lidar allows for the detection of terrain subsidence caused by thermokarst.  Lidar elevation model differencing provides a direct measure of land surface elevation changes over time.  This study compares two airborne lidar datasets covering ~400 km2 acquired in the aftermath of the large and severe Anaktuvuk River tundra fire that occurred in 2007 in northern Alaska.  Digital terrain models (DTMs) at 1-m spatial resolution were developed from the lidar datasets that were acquired 2 years and 7 years postfire.  These datasets were differenced using the Geomorphic Change Detection tool to quantify thermokarst development in response to the tundra fire disturbance. 

Results show permafrost thaw subsidence (more than 0.2 m) occurring across 34% of the burned tundra area studied, compared to less than 1% in similar undisturbed, ice-rich tundra terrain.  Postfire thermokarst development as detected in the airborne lidar data shows a relationship with trends in a dense time series of different multispectral indices (Tasseled Cap, NDVI, Normalized Difference Moisture Index (NDMI)) derived from multispectral Landsat satellite data.  These relationships allow scaled-up mapping of thaw-affected terrain area across the entire ~1,000-km2 area impacted by the Anaktuvuk River tundra fire; where sufficient cloud-free Landsat data are available, they may also allow for the assessment of thermokarst impacts across other tundra fire disturbances since the mid-1980s. 

These new methodologies will enable assessment of the vulnerabilities of ice-rich permafrost terrain to changing disturbance regimes in northern high latitude landscapes.  A better understanding of the processes controlling thermokarst initiation and development in Arctic regions is important because of the resulting impacts on the land-atmosphere exchange of water, energy, and greenhouse gases, along with the influence on surface hydrology, snow accumulation, and vegetation dynamics.

http://www.nature.com/articles/srep15865

Postfire thermokarst following an arctic tundra fire in northern Alaska. (a) QuickBird image acquired the summer after a large and severe tundra fire showing burned versus unburned tundra. (b) Repeat lidar-derived subsidence image indicating degradation of ice-rich permafrost 7 years postfire.

Postfire thermokarst following an arctic tundra fire in northern Alaska. (a) QuickBird image acquired the summer after a large and severe tundra fire showing burned versus unburned tundra. (b) Repeat lidar-derived subsidence image indicating degradation of ice-rich permafrost 7 years postfire.

Sensor: Lidar (terrestrial or bathymetric), Multispectral (approx. 4-12 bands)

Platform: Airplane, Satellite

Author: Benjamin M. Jones
Email: bjones@usgs.gov
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Astrogeology

A Last Look at Titan with Cassini

USGS scientists have been involved in mission planning, cartographic data processing, and scientific studies for the international Cassini-Huygens mission to the Saturn system since its inception in the early 1990s. Saturn’s Mercury-sized moon Titan, which has a range of geological features and processes unmatched by any other body besides the Earth, has been the main focus of these efforts. With a little over a year left before the spacecraft is deliberately flown into Saturn’s atmosphere to burn up, the mission is embarking on a “Grand Finale” that will bring its nearest orbit around Saturn to just outside the ring system, and then into the narrow gap between the rings and the planet’s cloud tops.  These final orbits will provide unprecedented detailed views of Saturn’s rings and atmosphere as well as measurements of the gravitational and magnetic fields.  They will also provide the last looks at Titan with multiple instruments, including a final peek at the “magic island” in the north polar hydrocarbon sea Ligeia Mare, which has been visible only intermittently in previous observations.

Cassini synthetic aperture radar image of the north pole of Saturn’s moon Titan.  The dark feature is Ligeia Mare, a 400-km-wide sea of liquid hydrocarbons.  The inset shows the so-called “magic island,” which appeared in 2013 and then vanished again.  A variety of explanations for the transient feature have been considered, but the most likely is that it was a “glint” off a patch of waves on the sea surface caused by local winds. The inset box is 70 km on a side, centered approximately 77°N, 247°W.

Cassini synthetic aperture radar image of the north pole of Saturn’s moon Titan.  The dark feature is Ligeia Mare, a 400-km-wide sea of liquid hydrocarbons.  The inset shows the so-called “magic island,” which appeared in 2013 and then vanished again.  A variety of explanations for the transient feature have been considered, but the most likely is that it was a “glint” off a patch of waves on the sea surface caused by local winds. The inset box is 70 km on a side, centered approximately 77°N, 247°W.

Sensor: IFSAR / SAR / Radar

Platform: Satellite

Author: Laszlo Keystay
Email: laz@usgs.gov
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Global Topographic Map of Mercury

The first global topographic map of Mercury has been released by the USGS Astrogeology Science Center, in collaboration with Arizona State University, Johns Hopkins University Applied Physics Laboratory, Carnegie Institute of Washington, and NASA. This map provides the first comprehensive view of Mercury’s entire surface illustrating the geologic and tectonic characteristics of the planet closest to the sun.

More than 100,000 images acquired from the Mercury Dual Imaging System (MDIS) camera on board the MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) spacecraft were used to derive the digital elevation model (DEM) at 665 m/pixel. The highly elliptical orbit of MESSENGER and the close proximity to the sun resulted in a dataset of images with a large variety of disparate geometric and illumination characteristics. This challenging dataset led the USGS to implement new and robust techniques to detect features in images and to match corresponding features between overlapping images. This feature-based approach is the first step in the process of refining image position and orientation parameters, which are critical for the accurate determination of elevation data.

The global map reveals 10 km of vertical relief of Mercury’s surface with lows of –5,380 m and highs of 4,481 m at its extremes. The DEM provided the basis for image orthorectification of global monochrome and color mosaics released by the MESSENGER team.

https://www.usgs.gov/news/first-global-topographic-map-mercury-released

Color-coded shaded relief derived from the global DEM in a Robinson projection. Elevations are in meters relative to the reference radius 2,349.4 km. One degree of longitude at the equator is 42.6 km.

Color-coded shaded relief derived from the global DEM in a Robinson projection. Elevations are in meters relative to the reference radius 2,349.4 km. One degree of longitude at the equator is 42.6 km.

Sensor: Camera, Lidar (terrestrial or bathymetric)

Platform: Satellite

Author: Laszlo Keystay
Email: laz@usgs.gov
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Gullies Formed by Dry Ice on Mars

The High Resolution Imaging Science Experiment (HiRISE) camera on board the Mars Reconnaissance Orbiter captures the surface of Mars at higher resolutions than ever before obtained from an orbiter:  image pixel sizes are as small as 25 cm. The capacity to deliver fine-scale detail serves one of the major science objectives of HiRISE, which is to track changes in Martian surface features.

Martian "gullies" have been studied extensively because they resemble water-formed features on Earth. After their discovery, they were initially thought to form by groundwater release or snowmelt. However, the monitoring campaign has revealed that they are active in the winter under extremely cold temperatures. This activity indicates that carbon dioxide (dry ice) frost, rather than liquid water, is responsible for creating the landforms. Scientists from the USGS and other institutions are now using HiRISE to monitor hundreds of locations on the surface and have discovered a diverse assortment of activity—some of it, like the gully flow shown in the image, driven by processes that do not occur on the Earth.

Portion of HiRISE image ESP_038546_1250 showing new deposits of sand and dust (that appear blue in the enhanced color image) from a gully on Mars. These deposits are knocked loose by carbon dioxide and appear distinct because they are not yet covered by red dust.

Portion of HiRISE image ESP_038546_1250 showing new deposits of sand and dust (that appear blue in the enhanced color image) from a gully on Mars. These deposits are knocked loose by carbon dioxide and appear distinct because they are not yet covered by red dust.

Sensor: Camera

Platform: Satellite

Author: Laszlo Keystay
Email: laz@usgs.gov
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Mapping the Small Bodies of the Solar System

The solar system is full of objects (“small bodies”) that include comets, asteroids, and dwarf planets. Many of these small bodies are relics from the early solar system and therefore provide clues about the early solar system and the formation of the planets. These small bodies are also potentially resource rich, e.g. water ice, and could support future human missions. The USGS is actively involved in several missions to understand these small bodies, including the Dawn mission to Ceres, the New Horizons flyby of Pluto, and the Japanese mission Hayabusa-2. USGS support ranges from cartographic software to nomenclature to thermophyscial modeling and data analysis. Below is an example of a mosaic of the surface of Pluto that was constructed by the New Horizons science team using USGS cartographic software. Global mosaics, such as the one shown for Pluto, are used for control of all of the other data collected.

Mosaic of Long Range Reconnaissance Imager (LORRI) images of Pluto from Ross et al. (2016). Image credit: NASA/SETI/USGS/SwRI

Mosaic of Long Range Reconnaissance Imager (LORRI) images of Pluto from Ross et al. (2016). Image credit: NASA/SETI/USGS/SwRI

 

Sensor: Camera, Multispectral (approx. 4-12 bands), Thermal

Platform: Satellite

Author: Laszlo Keystay
Email: laz@usgs.gov
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Moon in Color

Color views of the Moon have revealed substantial distributions of water on the lunar surface in the form of molecules trapped in minerals.  This discovery has fundamentally changed the prevailing view of the Moon as a sterile object. The USGS is supporting further analyses of lunar water by producing a high-precision cartographic mosaic from data collected by the NASA Moon Mineralogy Mapper (M3) instrument. These products include geodetically controlled, near-global maps of the lunar surface in visible to near-infrared wavelengths. The improved mosaic eliminates spatial offsets of up to 4 km and supports more detailed mapping of the distribution of water deposits on the surface of the Moon.

http://astrogeology.usgs.gov

Mosaic of M3 hyperspectral images of Copernicus Crater on the Moon.

Mosaic of M3 hyperspectral images of Copernicus Crater on the Moon.

Sensor: Hyperspectral

Platform: Satellite

Author: Laszlo Keystay
Email: laz@usgs.gov
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Carbon

Carbon Sequestration Potential of Federal Lands

Federal lands, covering about 23.5% of the conterminous United States, provide and sustain a wide range of ecosystem services including biodiversity preservation, mineral and energy development, recreation, and timber production. However, no systematic information about the spatial patterns and temporal changes of carbon stock and carbon sequestration potentials on Federal lands is available, representing a critical national knowledge gap.

As mandated by the U.S. Congress in the 2007 Energy Independence and Security Act, the USGS has quantified carbon sequestration potentials in the conterminous United States under various land use and climate change scenarios.  The current study evaluated contemporary and future ecosystem carbon dynamics in conterminous United States Federal lands under three Intergovernmental Panel on Climate Change Special Report on Emission Scenarios A1B, A2, and B1.  The Forecasting Scenarios of Land Use (FORE-SCE) model and the General Ensemble Biogeochemical Modeling System (GEMS) were used to simulate land use change and carbon dynamics, respectively.

The study estimated that conterminous United States Federal lands stored 11,613 million metric tons (MMTs) of carbon circa 2005 and were projected to store 13,965 MMTs of carbon in 2050, an increase of 19.4%.  The corresponding projected annual carbon sequestration rate (in kilograms of carbon per hectare per year) from 2006–2050 would be carbon sinks (i.e., carbon gains) of 620 and 228 for forests and grasslands, respectively, and a source (i.e., carbon release) of 13 for shrublands.  The Federal lands’ contribution to the national ecosystem carbon budget could decrease from 23.3% in 2005 to 20.8% in 2050.  The carbon sequestration potential in the future depends not only on the footprint of individual ecosystems but also on each Federal agency’s land use and management.  The results presented here update current knowledge about the contemporary ecosystem carbon stock and sequestration potential of Federal lands, which would be useful for Federal agencies to formulate management practices to achieve the national greenhouse gas mitigation goals.

(Top left) Spatial distribution of the contemporary (circa 2005) ecosystem carbon stock (in vegetation and the top 20-cm depth of soil, averaged from three model simulations) in Federal lands across the conterminous United States.  The other panels show carbon stock changes from 2006–2050 averaged from seven ensemble model simulations for each Intergovernmental Panel on Climate Change scenario (A1B, A2, and B1).

(Top left) Spatial distribution of the contemporary (circa 2005) ecosystem carbon stock (in vegetation and the top 20-cm depth of soil, averaged from three model simulations) in Federal lands across the conterminous United States.  The other panels show carbon stock changes from 2006–2050 averaged from seven ensemble model simulations for each Intergovernmental Panel on Climate Change scenario (A1B, A2, and B1).

Sensor: Multispectral (approx. 4-12 bands)

Platform: Satellite

Author: Shuguang Liu
Email: sliu@usgs.gov
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Data-Driven Carbon Fluxes in Rangeland and Cropland

Understanding current carbon fluxes is important for developing remediation or mitigation strategies in response to  anticipated changes in atmospheric greenhouse gas concentrations under future climate scenarios. Although atmospheric carbon dioxide (CO2) fluxes from rangelands and croplands  are small relative to those of forest systems,these land covers make up a large area in the conterminous United States (CONUS). In addition, historical grasslands (Mollisols) typically contain large soil carbon stocks that could be vulnerable to emission under altered climate conditions and land management practices. 

To estimate weekly carbon fluxes from rangelands and croplands, data-driven rule-based models were developed using crop and grassland flux tower datasets from the Fluxnet, Ameriflux, and Agriflux networks and from independent flux tower locations.  Crop and grassland flux tower estimates for weekly carbon flux associated with gross primary production, ecosystem respiration, and net ecosystem production are estimated with detailed light response curve analysis, which also facilitates the filling of data dropouts caused by temporary equipment failures.  Input drivers  for the algorithms include weekly Normalized Difference Vegetation Index (NDVI) at 250-m resolution and derived phenological metrics, soil attributes (available water capacity, clay content, soil organic carbon from SSURGO), weather data (precipitation and air temperature), and climate data. To facilitate crop carbon flux mapping, 250-m resolution crop type maps were constructed to capture consistent crop rotation histories back to 2000.  Crop type mapping was accomplished with decision tree algorithms using weekly NDVI, phenological metrics, weather data (precipitation and temperature), climate data, elevation, slope, aspect, irrigation, soils (available water capacity, soil organic matter, bulk density, and clay content), ecoregions, and major land resource areas as defined by National Resource Conservation Service (NRCS).

Resultant weekly carbon flux maps are summarized to show annual time series, seasonal trends, and comparisons between various crop types and grasslands.  An error map produced for inter-annual carbon flux estimates and combined with extrapolation severity quantified uncertainty and identified optimal future flux tower locations.  Preliminary results indicate 129 g C m-2 day-1 of additional carbon is removed from the atmosphere by grasslands when compared to non-irrigated crops. Grasslands were near carbon equilibrium at about 372 mm of annual precipitation, while non-irrigated crops require 629 mm of annual precipitation for carbon equilibrium.  Flux tower databases are also being used to conduct regional synthesis of carbon fluxes in legume crops, grain crops, grasslands, shortgrass prairie, mixed grass prairie, and tallgrass prairie systems.

The feasibility of making annual crop type maps at the end of the growing season, which is much more rapid than existing products, will also be assessed.

http://lca.usgs.gov/lca/cflux_gplains/index.php

Mean gross primary production (GPP), ecosystem respiration (Re), and net ecosystem production (NEP) for 2000–2013 masked for grasslands, sagebrush-steppe ecosystems, and five crop types: alfalfa, corn, millet, soybean, and winter wheat.

Mean gross primary production (GPP), ecosystem respiration (Re), and net ecosystem production (NEP) for 2000–2013 masked for grasslands, sagebrush-steppe ecosystems, and five crop types: alfalfa, corn, millet, soybean, and winter wheat.

Sensor: Multispectral (approx. 4-12 bands)

Platform: Satellite

Author: Bruce Wylie
Email: wylie@usgs.gov
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Mangrove Monitoring and Carbon Assessment

Mangroves are among the most carbon rich forests globally and they provide numerous ecological and economic services such as coastal erosion protection, water filtration, and breeding grounds for fish.  These coastal ecosystems are among the most threatened and vulnerable worldwide and have experienced a dramatic decline during the last half century. Better scientific understanding of the rates, patterns, causes, and consequences of mangrove change is needed.

The overall goal of this project is to assess mangrove vulnerability to climate change and land use change and to understand effects of the changes on mangrove carbon storage and sequestration. Information generated from this project will help answer questions such as, 1) how are the structure, density, and health of mangrove forests changing, and 2) what management interventions are needed to maintain or improve forest vigor and health.

The study components include 1) remote sensing data collection, 2) data analysis (classification and change detection implementing Vegetation Change Tracker (VCT) and Land Change Monitoring, Assessment, and Projection (LCMAP) techniques) and accuracy assessment, and 3) permanent plot establishment for aboveground biomass (AGB) and future carbon sequestration estimates. The J.N. “Ding” Darling National Wildlife Refuge, Florida, is being used as a pilot project, and methodology and lessons learned will be applied to other areas. A similar project is being carried out on the island of Pohnpei, Federated States of Micronesia, in collaboration with the U.S. Fish and Wildlife Service as well as the Micronesia Conservation Trust and the Conservation Society of Pohnpei.

Research results will be useful for managers to identify and reduce the vulnerability of mangroves (and possibly other coastal wetland types) and their carbon stocks to climate change. Mangrove biomass will be measured using species-specific allometric equations. Afterward, mangrove aboveground carbon (AGC) will be obtained, and the carbon stock of each mangrove stand will be summed to obtain the total mangrove AGC in each sample plot. Each pixel in Landsat observations will be utilized to extrapolate the sample point biomass observations.

Location of permanent sampling plots for measuring aboveground biomass at J.N. “Ding” Darling National Wildlife Refuge, Florida.

Location of permanent sampling plots for measuring aboveground biomass at J.N. “Ding” Darling National Wildlife Refuge, Florida.

Sensor: Multispectral (approx. 4-12 bands)

Platform: Satellite

Author: Elitsa Peneva-Reed
Email: epeneva-reed@usgs.gov
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Remote Sensing Ecology: Biofuels, Biomass, & Carbon

Biofuels derived from cellulosic grass, such as switchgrass, have the potential to provide domestic biofuels with minimal adverse effect on food production.  USGS scientists are seeking to identify ecological conditions that may favor switchgrass production over conventional agriculture crops, particularly corn.   The crop-grassland boundary in eastern Nebraska has been identified as a potential area for effective and sustainable switchgrass production; switchgrass production under future climate conditions is predicted to be similar to or greater than current production. The researchers developed a model that predicted switchgrass productivity and grassland biomass, and used the results to quantify ecosystem services and cellulosic biomass benefits from converting small portions of sub-marginal, high relief crop areas to switchgrass, which can serve both as biofuel sources and waterway buffers.  

The innovations developed during this study produced two additional by-products. First, because much of the work was at the 250-m scale of the Moderate Resolution Imaging Spectroradiometer (MODIS), scientists developed and tested an approach to downscale the results to 30-m resolution using multiple Landsat scenes within the same year.  MODIS growing season Normalized Difference Vegetation Index (NDVI) data, used as input to the biomass model, were seamlessly downscaled  with this method, producing a final grassland biomass map with Landsat 30-m pixel resolution. This approach has been adopted by the National Land Cover Database (NLCD) USGS/BLM rangeland mapping team, who downscale weekly MODIS NDVI during phenologically  critical periods when Landsat data are not available due to collection schedule or data quality (e.g., cloud cover).

Second, given the heavy reliance on the regression tree software Cubist (http://www.rulequest.com) for this and other projects, the researchers developed and tested a protocol to optimize the classification scheme. The protocol establishes optimal sizes for Cubist testing and training data sets as well as the maximum number of rules allowed to minimize over- and under-fitting tendencies in the models. This protocol was demonstrated in a case study to address mapping over-fitting errors, under-fitting errors, and optimal model errors. 

In collaboration with the U.S. Department of Agriculture (USDA) Agricultural Research Service (ARS), the team will be refining and improving the switchgrass biomass mapping algorithm. The USDA ARS has provided field data at switchgrass trial plots across the Great Plains.

http://lca.usgs.gov/lca/biofuels_platte/index.php

Cropland areas estimated to be relatively more efficient for switchgrass production than corn production.

Cropland areas estimated to be relatively more efficient for switchgrass production than corn production.

Sensor: Multispectral (approx. 4-12 bands)

Platform: Satellite

Author: Bruce Wylie
Email: wylie@usgs.gov
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Climate and Land Cover Change

Completion of Historical “Backcast” Modeling to 1938 for the Conterminous United States

Land use and land cover (LULC) in the United States has changed dramatically over the last century.  With a changing landscape, natural processes have been forever altered, impacting climate, carbon, hydrology, biodiversity, and other ecosystem services.  An understanding of historical LULC is needed to assess the past effects of LULC change on ecological and societal processes, and to facilitate the modeling of potential future LULC change to support planning and mitigation efforts. Multiple contemporary, spatially explicit LULC databases are available for the conterminous United States at moderate spatial and thematic resolutions, including the National Land Cover Database, LANDIRE, and the USGS Land Cover Trends project.  However, these data rely on remote sensing data and are unavailable for dates prior to the initiation of Landsat.  There are no historical, spatially explicit, consistent LULC databases available for the conterminous United States.

To meet the need for historical LULC data, staff at the USGS Earth Resources Observation and Science (EROS) Center have used a modeling approach to produce historical LULC maps back to 1938 for the conterminous United States.  Historical remote sensing databases were combined with Agricultural Census data, demographic histories, a database of reservoir construction dates, county-level wetland drainage histories, and other historical data to construct historical “demand” back to 1938.  Demand essentially provides a prescription for the quantities of historical LULC change at annual time steps at a regional level, with U.S. Environmental Protection Agency (EPA) ecoregions serving as the spatial framework.  A spatial allocation component within the FOREcasting SCEnarios of land use change (FORE-SCE) model ingests quantitative demand at a regional level and produces a spatially explicit representation of the prescribed proportions of LULC change. 

The resulting product is an annual, spatially explicit LULC database for the conterminous United States from 1938–1992, with 15 distinct LULC classes mapped at 250-m resolution.  The data are designed to be consistent with existing modeled land cover data from 1992–2100, produced as part of the USGS LandCarbon project.  Combined, the two datasets provide truly unique, spatially explicit, annual “snapshots” of LULC conditions across the conterminous United States from 1938–2100, with four alternative future scenarios for the years 2006–2100.  The unique nature of these data makes them suitable to assess the relationship of LULC change with a wide variety of ecological processes.  With data now available for both historical and future time periods, researchers can assess historical LULC change processes, determine historical impacts on ecosystem services, and use the future scenarios to determine potential future impacts, facilitating mitigation and planning efforts. Land cover modeling results discussed here are available at http://landcover-modeling.cr.usgs.gov. 

http://landcover-modeling.cr.usgs.gov

Modeled land use and land cover from 1938–1992 in the San Francisco, California, area. The inset area is approximately 125 x 90 miles.

Modeled land use and land cover from 1938–1992 in the San Francisco, California, area. The inset area is approximately 125 x 90 miles. 

Sensor: Multispectral (approx. 4-12 bands), Thermal

Platform: Satellite

Author: Terry Sohl
Email: sohl@usgs.gov
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Harmonization of Forest Disturbance Datasets

A wide range of spatial forest disturbance datasets exist for the conterminous United States, yet inconsistencies among map products arise because of differing programmatic objectives and classification methodologies. Harmonized maps were produced from multiple data sources (i.e., Global Forest Change, LANDFIRE Vegetation Disturbance, National Land Cover Database, Vegetation Change Tracker, Web-enabled Landsat Data, and Monitoring Trends in Burn Severity) using a pixel-based data fusion process. The harmonization process, which involved fitting common class ontologies and testing spatial congruency, reconciled differences in forest fire, harvest, and other disturbances across four time intervals (1986–1992, 1992–2001, 2001–2006, and 2006–2011) by relying on convergence of evidence across all datasets available for each interval. Pixels mapped as disturbed for two or more datasets were labeled as disturbed in the harmonized maps. Results indicated that harmonization of readily available data increased data utility by incorporating causality information across input datasets, extending the monitoring period, and improving user’s accuracies. However, conservative rules for labeling a pixel as disturbed contributed to lower producer’s accuracies relative to the best available individual disturbance map. Omission errors were high for all forest disturbance maps due to underlying limitations in Landsat classification algorithms.

Annualized area of forest disturbance (sq km/year) and annualized disturbance as a percent of total forest (%) for CONUS across all readily accessible forest disturbance datasets created using Landsat imagery, including Global Forest Change (GFC), LANDFIRE Vegetation Disturbance (LF), National Land Cover Dataset (NLCD), data delivered to the LANDFIRE program by the North American Carbon Program using the Vegetation Change Tracker (VCT) process (referred to as LF Raw VCT), and Web-enabled Landsat Data (WELD). Estimates from the USGS Land Cover Trends Project and first version of North American Forest Dynamics Vegetation Change Tracker are included for comparison. Baseline forest used to compute percent disturbed was obtained from 1987 CONUS forest estimates included in the 2010 USDA Resources Planning Act (RPA).

Annualized area of forest disturbance (sq km/year) and annualized disturbance as a percent of total forest (%) for CONUS across all readily accessible forest disturbance datasets created using Landsat imagery, including Global Forest Change (GFC), LANDFIRE Vegetation Disturbance (LF), National Land Cover Dataset (NLCD), data delivered to the LANDFIRE program by the North American Carbon Program using the Vegetation Change Tracker (VCT) process (referred to as LF Raw VCT), and Web-enabled Landsat Data (WELD). Estimates from the USGS Land Cover Trends Project and first version of North American Forest Dynamics Vegetation Change Tracker are included for comparison. Baseline forest used to compute percent disturbed was obtained from 1987 CONUS forest estimates included in the 2010 USDA Resources Planning Act (RPA).

Sensor: Multispectral (approx. 4-12 bands)

Platform: Satellite

Author: Christopher E. Soulard
Email: csoulard@usgs.gov
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Identifying Large Areas of Change

The ability to quickly identify where change on the ground occurs on a national level can enable focused mapping efforts and help identify trends in landscapes over time. The USGS National Geospatial Technical Operations Center undertook preliminary research into methods to evaluate change. The shift from areas of low or no amounts of vegetation to high, or vice versa, can indicate where larger land cover/ land use changes are occurring due to e.g., landslides or urbanization. Normalized Difference Vegetation Index (NDVI) datasets created from Moderate Resolution Imaging Spectroradiometer (MODIS) raster images were obtained from NASA as the MOD13Q1 Version 6 product, with a spatial resolution of 250 m per pixel and the best available pixels from the acquisitions during a 16-day period incorporated into a single dataset. Two datasets were obtained for each area of interest representing the same season. These datasets were incorporated into automated toolsets to highlight areas of change between two dates of interest for large regions.

To highlight areas of significant vegetation change, the MODIS NDVI images were subtracted, agricultural areas masked out using the National Land Cover Database as a guide, and any pixel with a value within 2.5 standard deviations from the mean value of each image was extracted. These pixels were converted to area and summed within the overlapping USGS 1:100,000 quadrangle boundaries to determine the percentage of changed area for each polygon. Shortcomings to this method do exist. Because growing seasons vary from year to year, the direct comparison of the same time period may show changes in NDVI that do not directly reflect actual land cover change, but rather changes in the growing season. Masking out agricultural areas may mitigate this somewhat, but the risk will remain for non-agricultural areas. In addition, the results from this method will not illustrate what types of land cover change are occurring—only that changes in vegetation have occurred.

Initial results are promising. This method allows for rapid identification of  significant vegetation change over large areas and can serve to focus efforts and highlight areas where mapping updates may be needed.

Sensor: Multispectral (approx. 4-12 bands)

Platform: Satellite

Author: Kristina H Yamamoto
Email: khyamamoto@usgs.gov
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Land Change Monitoring, Assessment, and Projection

The USGS Land Change Monitoring, Assessment, and Projection (LCMAP) initiative centers on structured, operational, ongoing, and timely collection and delivery of accurate and relevant data, information, and knowledge on land use, cover, and condition. LCMAP supports a wide array of objectives: (1) provide documentation and understanding of historical land change and contemporary land change as it occurs; (2) explain how past, present, and future land change affects society, natural systems, and the functioning of the planet at local to global scales; (3) alert relevant stakeholders to important or emerging land change events in their jurisdictions; and (4) support others in the use of land change data, information, and science results.

During the past year, significant progress has been made in implementing the first objective.  The assembly of an “analysis-ready” Landsat archive is underway that will provide data cubes of Landsat 4–8 surface reflectance and top-of-atmosphere reflectance data for the U.S. that contain pixel-level quality assurance information to enable screening of clouds and cloud shadows.  In addition, prototype 1985–2015 annual land cover and land cover change datasets have been completed for a large portion of the Pacific Northwest and another 10 sites around the country.  By late 2017, LCMAP capabilities will include a routine continuous U.S. land change monitoring capability that is supported by analysis-ready Landsat data, all feeding an agile capacity to provide timely land change data and assessments for decision makers. LCMAP initially will be implemented for the U.S. but can be expanded to provide global coverage.

2011 land cover for a portion of the Pacific Northwest generated using automated LCMAP land classification capabilities.

2011 land cover for a portion of the Pacific Northwest generated using automated LCMAP land classification capabilities.

Sensor: Multispectral (approx. 4-12 bands), Thermal

Platform: Satellite

Author: Tom Loveland
Email: loveland@usgs.gov
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Release of Provisional Climate Data Record and Essential Climate Variable Products

For the past several years, the Land Remote Sensing Program has sponsored the development of Landsat science products referred to as climate data records (CDRs) and essential climate variables (ECVs) to support scientific research and applications associated with the study of long-term trends in natural or human-induced changes to the Earth’s land surface.  These products include atmospherically corrected surface reflectance and surface temperature, burned area, dynamic surface water extent, fraction of snow covered area, and aboveground biomass. The development of the science data processing algorithms is undertaken through collaboration among scientists from multiple USGS Science Centers, NASA (Goddard Space Flight Center and the Jet Propulsion Laboratory), University of Maryland, and the Rochester Institute of Technology.  The goal is to generate these science products from the historical record of Landsat data dating back to 1982 corresponding to the beginning of the Landsat 4 Thematic Mapper (TM) measurements through the present Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and Landsat 8 Operational Land Imager (OLI) data and into the future.

The combined daily data acquisition rates by Landsat 7 and 8 today is 1,200 scenes per day, which is the highest in the history of the program.  In addition, the Landsat Global Archive Consolidation (LGAC) activity is increasing the amount of historical data in the archive through the repatriation of data downlinked to the International Cooperator network.  This means that the temporal depth and density of the Landsat archive, particularly over the conterminous United States, provides the opportunity to apply time series analysis of geophysical and biophysical properties of the land surface to study seasonal, interannual, and decadal variability. Through the development of dense multitemporal “data stacks,” scientists can now compare contemporaneous observations with historical trends to assess landscape resiliency and vulnerability to change associated with natural processes, land management policies, and land use practices. 

In fiscal year 2016 the development of these Landsat science products has made significant progress.  Landsat surface reflectance products can be generated on a routine basis for anywhere in the world.  Burned area and dynamic surface water extent products have been generated on a provisional basis from Landsat TM and ETM+ data and have been provided to stakeholders for evaluation and feedback, and by the end of the fiscal year the science processing algorithms will be updated to accommodate processing of OLI data.   A Landsat surface temperature product is currently undergoing evaluation by select investigators and is expected to be available on a provisional basis in early 2017.  Prototype fractional snow cover and aboveground biomass products have also been successfully demonstrated.

http://remotesensing.usgs.gov/ecv/

Illustration of a “data stack” comprised of seamless mosaics of Landsat 8 Operational Land Imager (OLI) surface reflectance data for the conterminous United States.

Illustration of a “data stack” comprised of seamless mosaics of Landsat 8 Operational Land Imager (OLI) surface reflectance data for the conterminous United States.

Sensor: Multispectral (approx. 4-12 bands)

Platform: Satellite

Author: John Dwyer
Email: dwyer@usgs.gov
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Ecosystems - Restoration

Alabama Barrier Island Restoration Assessment at Dauphin Island

Dauphin Island, Alabama, is a strategically important barrier island along the northern Gulf of Mexico in large part because it serves as the only barrier island providing protection to much of Alabama’s coastal natural resources. The size of the system spans over 200 acres of evolving barrier island habitat including beach, dune, intertidal wetlands, maritime forest, and freshwater ponds. In addition, Dauphin Island provides protection to approximately one-third of the Mississippi Sound and estuarine habitats including oyster reefs, marshes, and seagrasses. The island has been severely impacted by repeated extreme events over the past several centuries, most recently Hurricanes Ivan, Katrina, and Isaac, and by the Deepwater Horizon oil spill. The State of Alabama, the USGS, and the U.S. Army Corps of Engineers (USACE) are conducting a joint study to evaluate feasibility level alternatives to increase the resiliency and sustainability of Dauphin Island. The overarching goal is to preserve and enhance the ecological functions and values of the island and associated estuarine resources the barrier island helps to maintain.

The USGS Wetland and Aquatic Research Center (WARC) and the USGS St. Petersburg Coastal and Marine Science Center (SPCMSC) are leading several tasks under the feasibility study. Of these tasks, numerous efforts involve the use of remote sensing data. The SPCMSC will use aerial photography and satellite imagery to delineate short-term and long-term trends in shoreline change. The SPCMSC will also experiment with high-resolution imagery to produce maps of vegetated island cover that can serve as input for frictional characteristics in numerical models and for trend analysis of general barrier island habitats. The WARC will visually map barrier island habitats from high-resolution aerial photography acquired in 2015 and 1998. The 1998 habitat map will then be used to train and develop a habitat model that couples topographic position information (i.e., elevation, slope, distance from shoreline, etc.) with hydrodynamic output data developed by the SPCMSC; the 2015 habitat map will be used for validation. The habitat model will be coupled with hydrodynamic model outputs developed by researchers at the SPCMSC for modeling barrier island habitats in the future for various restoration alternatives.

http://www.nfwf.org/gulf/Documents/al-dauphin-assessment-14.pdf

Oblique aerial photograph of Dauphin Island, Alabama, from 2012 (Morgan and Westphal, 2016). The view is toward the north-northwest, with Pelican Passage to the east; the mainland is visible in the distance.

Oblique aerial photograph of Dauphin Island, Alabama, from 2012 (Morgan and Westphal, 2016; http://pubs.usgs.gov/ds/0988/). The view is toward the north-northwest, with Pelican Passage to the east; the mainland is visible in the distance.

Sensor: Camera, Lidar (terrestrial or bathymetric), Multispectral (approx. 4-12 bands)

Platform: Airplane, Satellite

Author: Nicholas Enwright
Email: enwrightn@usgs.gov
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Barriers and Opportunities for Landward Migration of Coastal Wetlands with Sea-level Rise

In the 21st century, accelerated sea-level rise and coastal development are expected to greatly alter coastal landscapes across the globe. The future of mangrove forests, salt marshes, and salt flats (i.e., tidal saline wetlands, collectively) is uncertain, and coastal environmental managers are increasingly challenged to develop conservation strategies that will increase the resilience of these valuable ecosystems. One strategy for preparing for the effects of sea-level rise is to ensure that there is space available for tidal saline wetlands to adapt to sea-level rise. USGS scientists used alternative future sea-level rise and urbanization scenarios to show where tidal saline wetlands may adapt via landward migration, where barriers may prevent landward migration, and how existing protected lands might accommodate expected landward migration. The analyses spanned five U.S. Gulf Coast States—Texas, Lousiana, Mississippi, Alabama, and Florida—and evaluated three sea-level rise scenarios and a business-as-usual future urbanization scenario.

At the region level, the analyses show that there is a massive amount of land along the U.S. Gulf of Mexico coast that is available for the landward migration of tidal saline wetlands. These areas consist of upslope and upriver ecosystems that are vulnerable to ecological regime shifts induced by sea-level rise. The county-level analyses show that much of the migration is expected to be concentrated along certain coastlines (e.g., Collier, Monroe, and Miami-Dade Counties in Florida; Assumption, Cameron, Lafourche, Terrebonne, St. Mary, and Vermilion Parishes in Louisiana). Topographic constraints are expected to limit the extent of landward migration along some coastal reaches. Migration barriers due to current and future urban development are expected to be highest in Florida, especially along the coastline that extends from Tampa to Fort Meyers. Although Louisiana is expected to experience the most landward migration of any State, much of the migration is expected to occur on unprotected lands (i.e., lands not owned by Federal, State, local, or private institutions with the capacity for continued conservation). In contrast, much of the anticipated landward migration in southern Florida is expected to occur on protected lands. Collectively, these analyses provide information that can be used to identify migration corridors and develop future-focused adaptation strategies that will improve the potential that the ecosystem goods and services provided by tidal saline wetlands will continue to be available for future generations.

http://pubs.usgs.gov/ds/0969/ds969.html

Tidal saline wetland migration and barriers expected for a 1.2-m sea-level rise by 2100 near Freeport, Texas. This study focused solely on assessing the area available for landward migration of tidal saline wetlands (depicted in light purple) and did not make any predictions regarding the ability of existing tidal saline wetland (depicted in magenta) to keep pace with sea-level rise via vertical accretion.

Tidal saline wetland migration and barriers expected for a 1.2-m sea-level rise by 2100 near Freeport, Texas. This study focused solely on assessing the area available for landward migration of tidal saline wetlands (depicted in light purple) and did not make any predictions regarding the ability of existing tidal saline wetland (depicted in magenta) to keep pace with sea-level rise via vertical accretion.

 

Sensor: Camera, Lidar (terrestrial or bathymetric)

Platform: Airplane

Author: Nicholas Enwright
Email: enwrightn@usgs.gov
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Drones for Habitat Restoration Assessment

Unmanned Aerial System (UAS) technology provides an economical method of measuring and monitoring impacts of restoration in bottomland forest sites of northeastern Indiana. This project links UAS-acquired data with field observations to assess the ability of UAS to monitor forest sites being restored as part of the Natural Resource Damage Assessment and Restoration program.  The first flight over the restoration area carried a standard color camera that produced imagery at a final resolution of 3.12 cm, and the second flight used the MicaSense RedEdge camera to yield 5-band imagery (blue, green, red, red edge, and near infrared) at 6.34 cm resolution.  Derived products will include various vegetation indices and a three-dimensional (3D) surface model generated using structure-from-motion processing. The UAS data will complement field data to assess carbon loading, describe community development, detect invasive species, evaluate mortality of planted trees, and assess variability in growth and plant physiology across sites.  Results will inform future monitoring design in restoration settings.

https://uas.usgs.gov/

 

 Flooded bottomland restoration site at Bluffton, Indiana. The foreground includes young shrubs and trees on a higher elevation location. Many planted stems have died in the middle area (shown under water), and silver maple recruitment is abundant near the mature trees along the edge of the restoration in the background.

 

Flooded bottomland restoration site at Bluffton, Indiana. The foreground includes young shrubs and trees on a higher elevation location. Many planted stems have died in the middle area (shown under water), and silver maple recruitment is abundant near the mature trees along the edge of the restoration in the background.

 

 Image of the Bluffton Native Habitat Waterway, which was flown on September 7, 2016.

Image of the Bluffton Native Habitat Waterway, which was flown on September 7, 2016.

Sensor: Camera, Multispectral (approx. 4-12 bands)

Platform: UAS

Author: Matthew Struckhoff
Email: mstruckhoff@usgs.gov
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Greenup and Evapotranspiration (ET) of the Colorado River Delta

During the spring of 2014, 130 million m3 of water were released from Morelos Dam on the lower Colorado River, allowing water to reach the Gulf of California for the first time in 13 years.  Nearly two years later, scientists continue to analyze the effects of this historic experiment, the result of a new U.S.-Mexico agreement. To assess the response of vegetation to the pulse flows, remote sensing techniques were used to measure greenup and evapotranspiration (ET) of vegetation within the delta’s riparian corridor. ET was assessed with an algorithm derived from MODIS Enhanced Vegetation Index (EVI) data, while greenup was measured using Landsat 8 Normalized Difference Vegetation Index (NDVI) data. There was a small but significant increase (3%) in ET and a significant increase (17%) in NDVI from 2013 (pre-pulse) to 2014 (post-pulse) within the delta’s riparian corridor (P < 0.05). While NDVI declined in 2015, it was still significantly higher than in 2013 (P < 0.05). This increase reverses an overall decline in NDVI and ET since the last major flood in 2000. Using the ET findings coupled with salinity data collected during the pulse flows, USGS researchers developed a conceptual model explaining the role of groundwater and surface flows in maintaining the riparian corridor in Mexico. Based on preliminary findings, pulse flows could be an effective tool for restoring the lower Colorado River’s riparian zone.

The difference in greenup between 2013 (pre-pulse) and 2015 (post-pulse); this change reversed a 13-year decline in green vegetation between 2000 and 2014.  Image first appeared in Jarchow, C. J., Nagler, P. L., Glenn, E. P. 2016. Greenup and evapotranspiration following the Minute 319 pulse flow to Mexico: An analysis using Landsat 8 Normalized Difference Vegetation Index (NDVI) data. Ecological Engineering.

The difference in greenup between 2013 (pre-pulse) and 2015 (post-pulse); this change reversed a 13-year decline in green vegetation between 2000 and 2014.  Image first appeared in Jarchow, C. J., Nagler, P. L., Glenn, E. P. 2016. Greenup and evapotranspiration following the Minute 319 pulse flow to Mexico: An analysis using Landsat 8 Normalized Difference Vegetation Index (NDVI) data. Ecological Engineering.

Sensor: Multispectral (approx. 4-12 bands)

Platform: Satellite

Author: Christopher Jarchow, Pamela Nagler
Email: cjarchow@usgs.gov; pnagler@usgs.gov
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High-Resolution Hydrographic Mapping with Lidar

High-resolution hydrographic mapping, which provides essential data for flood mitigation and planning,  is being completed on thirteen 12-digit hydrologic units near Sioux Falls, South Dakota. A lidar-derived digital elevation model is being processed using selective drainage methods to hydro-enforce culvert locations into the modeled drainage network. While some culverts had been inventoried prior to this study, many additional culverts were inventoried as a part of this study, and still more culvert locations are being identified using selective drainage processing. Cooperating agencies will ground-truth the culvert locations not yet inventoried, and will field verify any locations where the synthetic drainage network appears to depart from existing flowlines in the National Hydrography Dataset. The lidar-derived watershed boundaries and surface drainage patterns will provide resource managers and urban planners with better detail and a more current picture of hydrographic features in the study area.

http://sd.water.usgs.gov/projects/HighResMapping/HighResMapping.html

Location of the study area.

Location of the study area.

Sensor: Lidar (terrestrial or bathymetric)

Platform: Airplane

Author: Ryan Thompson
Email: rcthomps@usgs.gov
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Mississippi Coastal Improvements Program Barrier Island Habitat Mapping and Analytics

Restoration of coastal ecosystems has emerged as a high priority management issue because these lands, which are highly vulnerable to climate change, provide valuable ecosystem services. The Mississippi barrier islands are dynamic coastal landforms that are the first line of defense between the Gulf of Mexico and the Mississippi mainland coast. These islands are experiencing changes in structure (land area and habitat) and geomorphic processes (erosion and accretion) due to frequent intense storms, relative rise in sea level, and changes in sediment supply. Long-term loss of the barrier islands threatens the highly productive Mississippi Sound estuarine ecosystem and exposes the mainland Mississippi coast and its associated habitats to increasing saltwater intrusion and damage from future tropical storms. To reduce the risk for vulnerable areas, under the Mississippi Coastal Improvements Program (MsCIP), the U.S. Army Corps of Engineers (USACE) is investing in barrier island restoration at Ship Island through direct sand placement of approximately 22 million cubic yards to restore island structure and enhance sand supply to the littoral (tidal) transport system. Construction associated with the Ship Island restoration is scheduled to begin in February 2017.

A long-term monitoring and adaptive management (MAM) program is being integrated into the MsCIP barrier island restoration project. The incorporation of a science-based approach into the large-scale restoration effort includes the development of a conceptual ecological model, the identification of risk and uncertainties, performance measures, objectives, success criteria, monitoring parameters, and potential adaptive management actions. Throughout the restoration project life cycle, the MAM calls for several remote sensing activities. One activity is detailed mapping of barrier island habitats (i.e., submerged and emergent wetlands, tidal flats, beach, dune, etc.) before restoration (i.e., baseline mapping effort), during, and after restoration. The MAM also calls for the use of geospatial data such as satellite imagery, aerial imagery, and topobathymetric data to assess and monitor changes to barrier island habitats and the resources they support (i.e., fish and wildlife such as gulf sturgeon, sea turtles, and shorebirds) as a result of the restoration activities. This MAM includes remote sensing efforts from the USGS Wetland and Aquatic Research Center and the USGS St. Petersburg Coastal and Marine Science Center.

https://gom.usgs.gov/mscip

Oblique aerial photograph of West Ship Island, Mississippi, from 2012. The island is almost 2,000 feet at its widest point. The view is easterly, with the mainland toward the left (Morgan and Westphal, 2016).

Oblique aerial photograph of West Ship Island, Mississippi, from 2012. The island is almost 2,000 feet at its widest point. The view is easterly, with the mainland toward the left (Morgan and Westphal, 2016; http://pubs.usgs.gov/ds/0988/).

Sensor: Camera, Lidar (terrestrial or bathymetric), Multispectral (approx. 4-12 bands)

Platform: Airplane, Satellite

Author: Nicholas Enwright
Email: enwrightn@usgs.gov
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Monitoring the Effectiveness of Watershed Restoration in Semiarid Grasslands

In the semiarid grasslands of southeastern Arizona, historical degradation and uncertainty about local responses to future climate change threaten the continued productivity of the region. Land managers are implementing watershed restoration measures to promote climate change resilience and preserve ecological function while allowing traditional land uses such as livestock grazing. Restoration techniques include placing structures made of rock and wood (e.g., gabions, check dams, trincheras, one-rock dams, and post vanes) in drainages to induce streamflow meander, reduce the speed of water flow, lower erosion rates, and increase water infiltration and riparian plant biomass. USGS scientists are evaluating the effectiveness of these measures using a variety of remote sensing sources and analysis methods.  Multispectral Landsat Thematic Mapper data provide a long-term (1984 to present) resource for investigating the impact of past restoration projects on the vegetation growth in and around regional stream channels. Terrestrial lidar data and multispectral (4-band) imagery acquired via small Unmanned Aerial Systems (sUAS) are used to monitor current restoration projects. Lidar-derived high-resolution digital surface models allow researchers to track aggradation and erosion in stream channels and assess the effect of restoration on sediment retention, while sUAS imagery can be combined with field measurements of plant cover and species composition to quantify vegetation response to restoration efforts. Land managers will use this information to improve restoration designs based on site specific restoration goals. Aerial lidar acquired from local governments is additionally being used to model pollinator habitat and prioritize areas for restoration.

http://geography.wr.usgs.gov/science/aridlands/

Vegetation transects mapped on sUAS imagery (left) and derived digital surface model (right) before restoration at Wildcat Canyon near Douglas, Arizona. Wildcat Canyon channel is in the lower right of each image. Each transect is 20 m long.

Vegetation transects mapped on sUAS imagery (left) and derived digital surface model (right) before restoration at Wildcat Canyon near Douglas, Arizona. Wildcat Canyon channel is in the lower right of each image. Each transect is 20 m long. 

Sensor: Lidar (terrestrial or bathymetric), Multispectral (approx. 4-12 bands), Orthoimagery

Platform: Ground based / sensor web / web cam, Satellite, UAS

Author: Natalie R. Wilson
Email: nrwilson@usgs.gov
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Ecosystems - Vegetation

Characterization and Monitoring of Shrubland Components in the Western United States

The USGS Earth Resources Observation and Science (EROS) Center National Land Cover Database team in collaboration with the Bureau of Land Management (BLM) is producing the most comprehensive remote sensing based quantification of western United States shrublands to date.  Nine individual products are being developed that represent the primary shrubland components: percent shrub, percent sagebrush, percent big sagebrush, percent herbaceous, percent annual herbaceous, percent litter, percent bare ground, shrub height, and sagebrush height.  This approach relies on three major steps: creating training datasets using field measurements and high-resolution satellite imagery at selected sites, extrapolating these training datasets to the landscape level using Landsat 8, and validating the final products with independent field measurements.  Product creation has been prioritized to focus on sagebrush ecosystems.  Image nominal date 2013 products were developed in 2013 for southwestern Idaho, southeastern Oregon, northwestern Nevada, and northeastern California. Products from 2014 images were developed for the Mojave Desert, the Great Basin, western Utah, and southern Idaho in 2016.  In addition, field sampling was completed for future products focused on the Sonoran Desert, Wyoming, and Montana.  For sagebrush ecosystems, research has shown this approach enables more successful monitoring of gradual change and offers opportunities to develop historical 30-year trends of gradual habitat change from climate that can be projected into the future. 

http://eros.usgs.gov/land-coverland-use/national-land-cover

Status of USGS shrub and grass mapping by region.  Dates listed in each region represent the nominal year of Landsat 8 imagery used for mapping the region.

Status of USGS shrub and grass mapping by region.  Dates listed in each region represent the nominal year of Landsat 8 imagery used for mapping the region.

Sensor: Multispectral (approx. 4-12 bands), Thermal

Platform: Satellite

Author: Collin Homer
Email: homer@usgs.gov
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Great Smoky Mountains National Park Vegetation Mapping Project

The USGS Upper Midwest Environmental Sciences Center (UMESC) is producing a seamless vegetation map of Great Smoky Mountains (GRSM) National Park.  The UMESC has been conducting vegetation mapping for the National Park Service (NPS) for over a decade.  These highly accurate and highly detailed vegetation maps are used by individual parks to manage lands and conduct research.  High-resolution (0.305-m or better) 4-band digital imagery was collected during peak fall color.  For GRSM, this meant three separate flights for the entire park to capture the progression of fall color from the highest to lowest portions of the park.  This imagery is used in a 3D digitizing platform to distinguish vegetation at the Alliance and Association level of the U.S. National Vegetation Classification (USNVC) across the entire park.  This project, initiated in 2015, is projected to be delivered to the NPS in 2021.

The progression of fall color in 2015, in color infrared, from September 24 (left), to October 17 (center), to October 30 (right) north of the Newfound Gap parking area in Great Smoky Mountains National Park.

The progression of fall color in 2015, in color infrared, from September 24 (left), to October 17 (center), to October 30 (right) north of the Newfound Gap parking area in Great Smoky Mountains National Park.

Sensor: Camera

Platform: Satellite / Airplane / UAS

Author: Jennifer Dieck; Andrew Strassman
Email: jdieck@usgs.gov; astrassman@usgs.gov
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Mapping and Monitoring Biological Soil Crusts

Biocrusts (communities of mosses, lichens, and cyanobacteria) are ecologically important in arid lands for their role in stabilizing soils and reducing erosion, fixing carbon, and cycling nutrients, but their condition and extent are difficult to determine in remote and rugged areas like Utah’s Canyonlands. Trampling by livestock and humans can cause irreparable damage to biocrusts; therefore, small Unmanned Aerial Systems (UAS) provide an ideal platform for remote monitoring of these fragile communities. For this project scientists are using UASs to collect high-resolution ( less than 1-cm) near-infrared and color images over a number of biocrust monitoring plots established by the USGS in 2006.  WorldView-3 satellite data (31-cm panchromatic resolution, 1.24-m multispectral, and 3.7-m shortwave infrared) covering Canyonlands National Park and adjacent BLM management units were acquired at the same time as the UAS overflights.  Hand-held field spectroradiometer measurements are being used to characterize spectral reflectance profiles of biocrusts, soils, and vegetation, which along with field cover and UAS data will be used to scale up biocrust information over the larger landscape.  This work is a collaborative effort that involves USGS researchers from the Western Geographic Science Center, Southwest Biological Science Center, and Canyonlands Research Center, and scientists at the University of Colorado.

Unmanned Aerial Systems (UAS) were used to collect sub-centimeter color and near-infrared images of biological soil crust monitoring plots (top panel). Field spectra, crust community composition, and chlorophyll samples were collected at some field sites (center triptych). WorldView-3 multispectral imagery was collected of the study area coincident with UAS and field data collection (bottom panel).

Unmanned Aerial Systems (UAS) were used to collect sub-centimeter color and near-infrared images of biological soil crust monitoring plots (top panel). Field spectra, crust community composition, and chlorophyll samples were collected at some field sites (center triptych). WorldView-3 multispectral imagery was collected of the study area coincident with UAS and field data collection (bottom panel).

Sensor: Camera, Multispectral (approx. 4-12 bands)

Platform: Satellite, UAS

Author: Miguel Villarreal
Email: mvillarreal@usgs.gov
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Marsh Canopy Leaf Area and Orientation Calculated for Improved Marsh Structure Mapping

The typical assessment of vegetation condition focuses on the relative proportion of living and dead material, which provides no information on the key element of vegetation structure (i.e., density and orientation). Canopy structure information is critical for monitoring ecosystem status and trends, and is essential in climate, weather, and ecological studies. A three-dimensional description of canopy structure improves water flow estimates, advances optical condition and change mapping, and advances fire burn dynamics and emission projections. Unfortunately, quantitative and robust field techniques for measuring vegetation structure are lacking. One problem is that orientation is typically estimated rather than measured, yielding uncertain error bounds that propagate through the calculated density parameter. If both density and orientation could be calculated solely from common field measurements without the need for user estimates, the information content and direct comparability over time and space for a given species would dramatically increase. Furthermore, independent density and orientation measures would be directly amenable to remote sensing mapping, greatly increasing the effectiveness of monitoring status and trends.

USGS scientists are developing an approach for producing the spatiotemporal estimation of leaf area index (LAI) of a highly heterogeneous coastal marsh without relying on user estimates of marsh leaf-stem orientation. The derived canopy LAI profile used three years of field-measured photosynthetically active radiation (PAR) vertical profiles at seven S. alterniflora (saltmarsh cordgrass) marsh sites. First, an iterative transform of the PAR attenuation profiles produced best-fit light extinction coefficients (KM). KM sun zenith dependency was then removed obtaining, the leaf angle distribution (LAD) representing the average marsh orientation. Finally, the LAD was used to calculate the LAI canopy profile. These derived LAI and LAD reproduced measured PAR profiles with 99 % accuracy and corresponded to field-documented structures. LAI and LAD better reflect marsh structure than visular estimates; results substantiate the need to account for marsh orientation. The structure indexes are directly amenable to remote sensing spatiotemporal mapping and offer a more meaningful representation of wetland grassland systems, promoting biophysical function understanding.

Ramsey III, E., Rangoonwala, A., Jones, C.E., and T. Banister., 2015.  Marsh Canopy Leaf Area and Orientation Calculated for Improved Marsh Structure Mapping, Photogramm Eng Rem S, 81(10) 807-816. doi: 10.14358/PERS.81.10.807

http://www.asprs.org/a/publications/pers/2015journals/PERS_October_2015_Member/HTML/files/assets/basic-html/page57.html

(a) Yearly PAR vertical profiles at a single marsh site (397) from 2010 to 2012. (b) Predicted PAR using model-derived LAI and LAD values shown in (c).

(a) Yearly PAR vertical profiles at a single marsh site (397) from 2010 to 2012. (b) Predicted PAR using model-derived LAI and LAD values shown in (c).

Sensor: Ground based light sensors

Platform: Ground based / sensor web / web cam

Author: Amina Rangoonwala
Email: rangoonwalaa@usgs.gov
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Monitoring Landscape Level Seasonality with “PhenoCams”

Land surface phenology is a crucial link between climate and natural resources. The Department of Interior (DOI) North Central Climate Science Center (NC CSC) has partnered with the AmericaView program to establish phenology cameras, or “PhenoCams,”  at strategic locations throughout the north-central U.S.  These fixed cameras transmit an image of the landscape to an online server every 30 minutes during daylight hours.  Both raw imagery as well as derived metrics of vegetation greenness are freely available through the National PhenoCam Network website. The international community has agreed upon the use of coupled PhenoCam sites and in situ observations as the primary validation for land surface phenology products; as such, PhenoCam activity is occurring in coordination with the Committee on Earth Observation Satellites Land Product Validation subgroup (CEOS LPV) and the USA National Phenology Network. The NC CSC has developed and documented protocols for comparing PhenoCam and remotely sensed data pixel-by-pixel. This comparison allows the hyper-temporal resolution (every ½ hour)  PhenoCam imagery to provide a more detailed and localized interpretation of the changing vegetation and habitat dynamics seen on less frequent satellite observations, such as those from Landsat every 8 days.

https://phenocam.sr.unh.edu/webcam/

A stunning view of the Grand Tetons as seen from the National Elk Refuge phenocam.  The image was acquired on May 28, 2016, at 11:00 am local time.   The lush green vegetation in the image is being compared to the vegetation indices observed by MODIS and Landsat 7 and 8 as well as the antecedent climate conditions.

A stunning view of the Grand Tetons as seen from the National Elk Refuge phenocam.  The image was acquired on May 28, 2016, at 11:00 am local time.   The lush green vegetation in the image is being compared to the vegetation indices observed by MODIS and Landsat 7 and 8 as well as the antecedent climate conditions.

Sensor: Camera, Multispectral (approx. 4-12 bands)

Platform: Ground based / sensor web / web cam, Satellite

Author: Jeff Morisette
Email: morisettej@usgs.gov
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Quantifying Understory Fuels Using Lidar Data in the Superior National Forest

The Wildland Fuels Research project at the USGS Earth Resources Observation and Science Center seeks to develop novel applications of remotely sensed data to better quantify and map wildland fuels in support of wildfire planning and response.  A new initiative has begun in collaboration with the Superior National Forest (SNF) in northern Minnesota to quantify understory fuels using airborne lidar data.  In many areas of the SNF, small balsam fir trees make up a substantial portion of the understory vegetation and contribute to fire behavior when these areas burn.  However, existing vegetation and fuels maps do not typically capture understory since only dominant overstory species are represented.  This deficiency limits the ability of SNF managers to accurately predict fire behavior and fire effects.

USGS scientists are conducting field work to quantify the amount and distribution of understory fuels in the SNF, particularly focusing on balsam fir trees.  They will then use these data with existing airborne lidar to derive models of understory vegetation structure.  Landsat and other image sources will be utilized to extrapolate the understory fuels maps throughout the SNF and potentially other areas.  The goals are to provide SNF with a comprehensive quantification of balsam fir understory fuels structure throughout the forest and to develop mapping methodologies applicable to other parts of the region experiencing similar conditions.  Several ground-based fuels mapping methods are being investigated and the collection and use of terrestrial lidar data are also being considered.

Example of lidar-derived metric products of canopy structure from northern Cook County, Minnesota. A) Image showing an area characterized by varied forest strands.  (Red box shows where profile data in E were taken.) B) Lidar-derived maximum canopy height.  C) Lidar-derived height of low- to medium-height vegetation beneath the overstory canopy. D) Density of vegetation at 2–4 m within the canopy.  Note how spatial patterns shift between B, C, and D.  E) Profile of lidar returns showing taller canopy with relatively little vegetation and mid and low elevations to the left and canopy with denser near-surface vegetation to the right.

Example of lidar-derived metric products of canopy structure from northern Cook County, Minnesota. A) Image showing an area characterized by varied forest strands.  (Red box shows where profile data in E were taken.) B) Lidar-derived maximum canopy height.  C) Lidar-derived height of low- to medium-height vegetation beneath the overstory canopy. D) Density of vegetation at 2–4 m within the canopy.  Note how spatial patterns shift between B, C, and D.  E) Profile of lidar returns showing taller canopy with relatively little vegetation and mid and low elevations to the left and canopy with denser near-surface vegetation to the right.

Sensor: Lidar (terrestrial or bathymetric), Multispectral (approx. 4-12 bands)

Platform: Airplane, Ground based / sensor web / web cam, Satellite

Author: Kurtis Nelson
Email: knelson@usgs.gov
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Remote Sensing of Winter Cover Crop Performance

In the Chesapeake Bay Watershed, the use of winter cover crops on agricultural land has been identified as a priority conservation practice for improving soil health and reducing the loss of nutrients and sediment from farmland. Winter cover crops (such as rye, barley, wheat, and radish) are planted in the fall, following the harvest of summer row crops (such as corn, soybean, vegetables). The cover crops are typically killed the following spring to release nutrients for the subsequent cash crop. Winter cover crops take up nitrogen that would otherwise be vulnerable to leaching over the winter, and they protect the soil from raindrop impact and erosion.  Because they help meet important environmental targets, cover crops are strongly promoted by agricultural conservation agencies in the Chesapeake Bay region, and their use on farms has rapidly increased over the past decade. However, on-farm performance has been shown to be highly variable, and the effects on water quality are not well quantified.

This project uses multispectral satellite imagery to measure wintertime vegetation on agricultural fields and combines this information with site-specific knowledge of crop rotations and cover crop management practices. Proximal sensors and on-farm sampling are used to calibrate imagery interpretation, and hyperspectral biophysical models are used to understand the impact of various components of ground cover (vegetation, soils, crop residue, and shadow) on field reflectance.  Using these methods, USGS researchers can map cover crop performance at the watershed scale and improve the understanding of conservation outcomes associated with various cover crop management strategies. This information is used by farmers and conservation agencies to promote adaptive management of winter cover crop programs to maximize environmental benefits. Scientific challenges include maintaining consistent calibration for satellite imagery interpretation from image to image across time, as well as accounting for the effects of soil moisture and background soil reflectance to accurately measure low levels of vegetation.

https://profile.usgs.gov/whively

Wintertime biomass on agricultural fields following corn harvest, Talbot County, Maryland, showing the distribution of fields with minimal to high levels of vegetation.

Wintertime biomass on agricultural fields following corn harvest, Talbot County, Maryland, showing the distribution of fields with minimal to high levels of vegetation.

Sensor: Hyperspectral, Multispectral (approx. 4-12 bands)

Platform: Ground based / sensor web / web cam, Satellite

Author: W. Dean Hively
Email: whively@usgs.gov
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Shrub and Grass Fuel Maps Using Remotely Sensed Data and Biogeochemical Modeling

Shrub and grassland ecosystems in the western United States are especially prone to fire events, yet available data for assessing fire risk in these areas are inadequate.  Part of the difficulty in effectively characterizing shrub and grasslands for fire applications is related to the high degree of intra- and inter-annual variability of fuel characteristics in these ecosystems.  A better understanding of the dynamics of these ecosystems and the conditions that promote wildfires needs to be developed.  This information is of special importance to projects that are providing fire managers with nationally consistent and detailed spatial information about vegetation and fuel structure.

Through the support of the NASA Applied Sciences Program, staff at the USGS Earth Resources Observation and Science (EROS) Center embarked on an assessment to derive better fuel characterizations in western United States shrub and grassland ecosystems.  The primary objectives of the first phase of the project included the following:  (1) improve shrub and grassland mapping for fire applications; (2) develop intra-seasonal fuel datasets in shrub and grassland areas using a combination of Landsat and Moderate Resolution Imaging Spectroradiometer (MODIS) data; and (3) determine if improvements in shrub and grassland data layers will alter and improve fire behavior model results.

The current focus is on the Great Basin, which includes portions of Nevada, southern Idaho, and western Utah.  This area is the site of many large and frequent shrub and grassland fires. The shrubland areas are dominated by sagebrush, while the grassland areas have a substantial amount of invasive cheatgrass associated with them.  The shrub and grassland areas of the region are characterized by high levels of biomass variability detectable through time series data analyses from MODIS.  Those areas that have burned recently tend to have higher levels of biomass than those that have not.  Understanding these patterns helps the fire management community recognize which areas have high likelihood of burning in the future, thus enabling them to anticipate and plan accordingly.

The project is currently developing methods to merge Landsat with MODIS data throughout the region.  The high spatial resolution of Landsat is desirable for fire modeling applications, while the MODIS sensor provides high temporal frequency data that enables insight into  seasonal dynamics.  Merging  Landsat and MODIS data provides the beneficial aspects of both imagery datasets  and will help to better understand the patterns of green-up and senescence at spatial scales desired by the fire management community.  

Red indicates areas burned at least once during 1984–2010 within the Great Basin.  Most of the burned areas are located in shrub and grasslands.  The northern portion of the region (especially within the Snake River Plain and the Northern Basin and Range ecoregions) had proportionately more fires than the southern portion of the region.  This information is useful for helping predict which areas are most likely to burn in the future.

Red indicates areas burned at least once during 1984–2010 within the Great Basin.  Most of the burned areas are located in shrub and grasslands.  The northern portion of the region (especially within the Snake River Plain and the Northern Basin and Range ecoregions) had proportionately more fires than the southern portion of the region.  This information is useful for helping predict which areas are most likely to burn in the future.

Sensor: Multispectral (approx. 4-12 bands), Thermal

Platform: Satellite

Author: James Vogelmann
Email: vogel@usgs.gov
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Structural Classification of Marshes with Polarimetric SAR

The coastal marsh within Barataria Bay on the western side of the Mississippi River Delta was heavily impacted by the 2010 Deepwater Horizon oil spill. Polarimetric synthetic aperture radar (PolSAR) and field data were collected near-concurrently in the summers of 2010, 2011, and 2012 in the north-central Gulf of Mexico to assess the condition of coastal marshes, including Barataria Bay.  PolSAR data alone were collected in 2009. Empirical relationships between field-derived leaf area index (LAI) and leaf angle distribution (LAD, average orientation) and PolSAR-based biophysical indicators were created and applied to map S. alterniflora (saltmarsh cordgrass) marsh canopy structure. The classified sequence and spatial pattern of marsh structure maps from 2009 to 2012 revealed a structurally dynamic marsh landscape that was not perceived by the multitude of optical to radar sensors and photointerpretation used to detect change within this high profile region. The dynamic change patterns documented in the independent classifications offer a compelling history of progression from year to year. This study demonstrates the unique perspective on marsh biophysical change offered by PolSAR marsh structure mapping to the study of terrestrial ecology. The developed mapping was based on the NASA Unmanned Aerial Vehicle Synthetic Aperature Radar (UAVSAR) L-band system, which is similar to that of the Japanese Aerospace Exploration Agency (JAXA) ALOS-2  and to that designed for the NASA-ISRO SAR Mission (NISAR) mission.

http://www.mdpi.com/2072-4292/7/9/11295

The images show coastal marsh within Barataria Bay on the western side of the Mississippi River Delta heavily impacted by the 2010 Deepwater Horizon oil spill. LAI-LAD classes (2009 to 2012). (Legend Pattern Color = LAI Range, LAD Range) Dark Brown = 1.6, 0.67, Brown = 2.5 to 2.8, 0.61 to 0.67, Light Tan = 3.6 to 4, 0.52 to 0.72, Dark Green = 4.8 to 5.3, 0.44 to 0.62, Light Green = 5.9 to 6.5, 0.41 to 0.5, Minor classes Olive and Reds = 7.2 to 11, 0.31 to 0.4.

The images show coastal marsh within Barataria Bay on the western side of the Mississippi River Delta heavily impacted by the 2010 Deepwater Horizon oil spill. LAI-LAD classes (2009 to 2012). (Legend Pattern Color = LAI Range, LAD Range) Dark Brown = 1.6, 0.67, Brown = 2.5 to 2.8, 0.61 to 0.67, Light Tan = 3.6 to 4, 0.52 to 0.72, Dark Green = 4.8 to 5.3, 0.44 to 0.62, Light Green = 5.9 to 6.5, 0.41 to 0.5, Minor classes Olive and Reds = 7.2 to 11, 0.31 to 0.4.

 

Sensor: IFSAR / SAR / Radar

Platform: Airplane, NASA UAVSAR

Author: Amina Rangoonwala
Email: rangoonwalaa@usgs.gov
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Vegetative Response to Water availability on the San Carlos Apache Reservation

On the San Carlos Apache Reservation in east-central Arizona, vegetation types such as ponderosa pine forests, pinyon-juniper woodlands, and grasslands have important ecological, cultural, and economic value for the Tribe. This value extends beyond the Tribal lands and across the western United States. Vegetation across the southwestern United States is susceptible to drought conditions and fluctuating water availability. Remotely sensed vegetation indices can be used to measure and monitor spatial and temporal vegetative response to these water and drought dynamics. USGS scientists derived the Modified Soil Adjusted Vegetation Index II (MSAVI2) from Moderate Resolution Imaging Spectroradiometer (MODIS) imagery to measure the condition of three dominant vegetation types (ponderosa pine forest, woodland, and grassland) in response to two fluctuating environmental variables: precipitation and the Standardized Precipitation Evapotranspiration Index (SPEI). The analysis, conducted for 2002 through 2014,  showed that grassland and woodland have a similar moderate to strong, year-round, positive relationship with both precipitation and SPEI. This suggests that these vegetation types respond negatively to drought conditions and are more susceptible to initial precipitation deficits. Ponderosa pine forest had a comparatively weaker relationship with monthly precipitation and summer SPEI, indicating that it is more buffered against short-term drought conditions. This research highlights the response of multiple dominant vegetation types to seasonal and interannual water availability and demonstrates the effectiveness of multitemporal remote sensing imagery as a tool for the detection of vegetation response to climate change at regional scales. Such tools can provide cost-effective monitoring to inform management of drought-affected areas.

https://www2.usgs.gov/climate_landuse/lcs/projects/vcarbon.asp

http://geography.wr.usgs.gov/science/TribalLandVegetation/index.html

Time series for Standardized Precipitation Evapotranspiration Index (SPEI) for the study period. Positive SPEI values are shown in blue while negative SPEI values (drought) are shown in yellow.

Time series for Standardized Precipitation Evapotranspiration Index (SPEI) for the study period. Positive SPEI values are shown in blue while negative SPEI values (drought) are shown in yellow.

Sensor: Multispectral (approx. 4-12 bands)

Platform: Satellite

Author: Zhuoting Wu
Email: zwu@usgs.gov
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Ecosystems - Wildlife

Exploring New Technologies to Estimate Abundances of Sandhill Cranes

In March 2011, USGS and U.S. Fish and Wildlife Service (USFWS) biologists conducted a pilot project designed to estimate the abundance of sandhill cranes (Grus canadensis) at one roost at the Monte Vista National Wildlife Refuge in Colorado. The Refuge is an important fall and spring migration area for sandhill cranes; almost the entire Rocky Mountain population stages there every spring. Historically, most aerial migratory bird surveys have been conducted using pilots and observers seated in fixed-wing or rotary aircraft, who identify and count birds using ocular estimation techniques. The number of skilled pilots/observers is limited, however, and the USFWS was interested in exploring cost-effective and safe alternatives to ensure they meet their trust responsibilities of assessing the status of all migratory bird species. This trial effort to use a small Unmanned Aerial System (sUAS) to assess crane abundance was an unqualified success, with the resulting estimate only 4.6% different than ground counts conducted by biologists, justifying further development and testing of techniques. 

Based on the success of the 2011 project, the first-ever nighttime sUAS flights were conducted in March 2012. There are advantages in surveying cranes at night because the birds roost in concentrated groups on shallow wetland sites and are relatively stationary. These surveys need to be completed in one night, however, because major inter-roost movements can occur between successive nights that would result in biased abundance estimates.  The team completed flights over the primary roosts in less than 6 hours, using 47 parallel transects spaced to optimally capture thermal imagery for analysis.  The 2012 flights resulted in an estimate of 14,658 cranes occupying the five roost sites. To compare crane abundance estimated from two potentially useful platforms, in March 2016 flights were conducted over the same roost areas at the Refuge during one night with both sUAS and a manned, fixed-wing aircraft carrying a Forward Looking Infrared (FLIR) camera system. Imagery from the FLIR platform was collected first, and data collection by the sUAS was initiated immediately subsequent to the FLIR work. Image processing and analysis is currently being conducted; once complete, managers and researchers will have better data to assess which platform may best meet their needs based on the size of the area to be surveyed, cost, and safety considerations.

http://uas.usgs.gov/CO_SandhillCranesMonteVistaNWR.shtml

Thermal infrared image of sandhill cranes (black dots) on roost at Monte Vista National Wildlife Refuge, Colorado.

Thermal infrared image of sandhill cranes (black dots) on roost at Monte Vista National Wildlife Refuge, Colorado.

Sensor: Thermal

Platform: Airplane, UAS

Author: Leeann Hanson
Email: leanne_hanson@usgs.gov
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Migration Patterns and Wintering Distribution of Juvenile Common Loons

Little is known about the movements, habitat use, and causes of mortality of common loons during their first few years.  To address this knowledge gap, scientists with the USGS Upper Midwest Environmental Sciences Center in La Crosse, Wisconsin, and partners captured and radiomarked juvenile common loons on lakes scattered across Minnesota and Wisconsin during the summers of 2014 and 2015. Satellite transmitter and geolocator tag technologies  were used to describe the movements and wintering ground use of juvenile loons in Minnesota and Wisconsin during their first two years of life. Researchers continued to monitor the movements of a few of these radiomarked loons in 2016. The radiomarked juvenile loons typically departed natal lakes for neighboring or other nearby lakes before making longer movements toward their wintering areas in the Gulf of Mexico and the Atlantic Ocean. The loons staged on a variety of lakes and reservoirs in several states during their first fall migration. Loons summered as yearlings near the Gulf of St. Lawrence or Nova Scotia and then returned to the Gulf of Mexico for their second winter. This information will be used by resource managers to inform regional common loon conservation strategies. 

The migration of the juvenile common loons can be followed online at the USGS common loon migration Web page at http://www.umesc.usgs.gov/terrestrial/migratory_birds/loons/migrations.html.

http://www.umesc.usgs.gov/terrestrial/migratory_birds/loons/migrations.html

A radiomarked juvenile common loon is released on a northern Minnesota lake.  Photo credit:  Carrol Henderson (Minnesota Department of Natural Resources).

A radiomarked juvenile common loon is released on a northern Minnesota lake.  Photo credit:  Carrol Henderson (Minnesota Department of Natural Resources).

Sensor: Telemetry

Platform: Satellite

Author: Kevin Kenow
Email: kkenow@usgs.gov
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Modeling Landscape-scale Habitat Relations for Landbirds During Migration

Millions of landbirds migrate through the Gulf of Mexico region each spring and autumn. Migration is energetically taxing, and these migrants depend on stopover habitats to provide the food and cover needed to complete their journey. For some species, as much as 85% of annual mortality occurs during migration. Stopover habitats in the Gulf of Mexico region have been lost or degraded due to the effects of development, agriculture, livestock grazing, timber industry activities, and the spread of exotic species. The continued loss or degradation of stopover habitat poses a risk to migrating birds, so knowing the location and landscape composition where peak numbers of birds consistently stop to rest and forage is critical for conservation planning. USGS Wetland and Aquatic Research Center scientists are using weather surveillance radar data and landscape metrics to model bird-habitat relations within 70 km of four radar stations along the western coast of the Gulf of Mexico. Reflectivity data collected from 2008–2012 were used to estimate migratory landbird density during spring and fall migration. Landscape variables were measured from 2006 Coastal Change Analysis Program (C-CAP) land cover, National Elevation National Hydrography, and 2010 U.S. Census Bureau TIGER datasets. Results of this research will support the conservation plans of the Gulf Coast Joint Venture by identifying the factors that characterize suitable migratory landbird stopover habitat.

This image depicts the distribution of landbirds during migratory stopover. Weather surveillance radar data were collected during fall migration 2008–2012 within 70 km of the Corpus Christi, Texas, radar.

This image depicts the distribution of landbirds during migratory stopover. Weather surveillance radar data were collected during fall migration 2008–2012 within 70 km of the Corpus Christi, Texas, radar.

Sensor: Weather Surveillance Radar 1988 Doppler

Platform: Ground based / sensor web / web cam

Author: Wylie C. Barrow, Jr.
Email: barroww@usgs.gov
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Wolf Population, Ecology, and Movement

To facilitate the recovery of federally endangered wolves (Canis lupus), it is critical to learn as much as possible about their behavior and habitat use. The direct study of wolves is difficult, however, due to their avoidance of humans and the inaccessibility of their wilderness territories.  The USGS Northern Prairie Wildlife Research Center uses Very High Frequency (VHF) and/or Global Positioning System (GPS) radio collars to locate and monitor wolves in three areas to investigate their movements, ecology, and population. 

The study is concentrated in the east-central Superior National Forest of northeastern Minnesota in cooperation with the Minnesota Department of Natural Resources. Collaborators include graduate students and other scientists with research projects in Yellowstone National Park and on Ellesmere Island, Canada.  In the Superior National Forest and Yellowstone National Park, the collars are located by aerial tracking, which in winter allows observation of collared wolves and their packs, thus providing data for annual surveys of populations and long-term population trajectories.  The population in the Superior National Forest has been monitored this way since 1968 and in Yellowstone since 1995.  In Yellowstone, locating wolf packs via telemetry from the ground enables observers to study behavior of individual wolves and of pack-to-pack interactions.  Wolf movements are also studied, such as territoriality, daily movements, and long-distance dispersal.  For example, a maturing female wolf observed in the Superior National Forest moved over 200 km and then returned to her natal area.

Subsidiary information is obtained in all three study areas through capturing the wolves for collaring and using telemetry signals to determine mortality and survival, locate dens, and collect other specimens.  Information gathered long-term via these methods has been useful in providing insights into wolf population persistence, wolf-deer interactions, and the role of wolves in a recent moose decline.  It also allows biologists to understand what to expect with reintroduced and recovering wolf populations

GPS-collared Wolf 7246 moved from her natal area over 200 km from Minnesota into Canada and then returned to her natal area.

GPS-collared Wolf 7246 moved from her natal area over 200 km from Minnesota into Canada and then returned to her natal area.

Sensor: Radio receiver

Platform: GPS radio collar

Author: L. David Mech and Shannon Barber-Meyer
Email: david_mech@usgs.gov
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Energy and Minerals

Integration of Remote-Sensing Alteration Mapping into New Geospatial-statistical, Quantitative Mineral Resource Methods

Geospatial and statistical techniques were used to apply Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) remote sensing data as a new method to map porphyry copper mineral resource potential in the southwestern United States. Quantitative mineral-resource assessments for undiscovered porphyry copper deposits in four permissive tracts were conducted using ASTER remote sensing, geochemistry, gravity and magnetic, lithologic, and deposit and prospects data. Permissive tracts are discrete geographic areas that have potential for hosting ore deposits of a particular type and for which estimates of numbers of undiscovered deposits are made. All permissive tract data were compiled in a geographic information system (GIS) and USGS scientisits applied new geospatial-geostatistical techniques to form the basis of new quantitative methods for analysis and visualization of tract data. 

In previous assessment studies applying ASTER alteration mapping, sites that may be associated with porphyry copper mineralization (based on a visual assessment of remotely sensed alteration types, patterns, and lithology) were represented as point locations on a map. A more accurate, automated method of compiling geometric properties and evaluating hydrothermal alteration sites using alteration areas (polygons) was developed from a regional alteration map of the southwestern U.S. consisting of 247 ASTER scenes. Alteration density of argillic, phyllic, and propylitic units based on a 1-km-diameter circle around each pixel was mapped using a low-pass filter. Alteration polygons were compiled from rock units that typically host porphyry copper deposits that contained alteration densities greater than 19%. Physical characteristics of each polygon were recorded and then ranked. Polygon scores were classified and color coded on maps in three groups: low (0–4), moderate (5–7), and high (8–22). In addition, alteration polygons that were not associated with known deposits or prospects were identified to signify an area that had potentially not been explored. The classified ASTER alteration polygons were particularly effective for showing areas of favorable alteration for porphyry copper deposits on regional-scale tract maps. Although the study area is one of the most thoroughly explored porphyry copper districts in the world, with 43 known Phanerozoic deposits, this assessment indicates that there are 14, or possibly 17 (using the ASTER data), additional porphyry copper deposits likely to be present. In addition, the ASTER polygon dataset showed two areas that have a high probability of containing porphyry copper deposits that have not been extensively explored using conventional means.

ASTER hydrothermal alteration map and outlines of alteration polygons southwest of Tucson, Arizona. Colors of alteration polygons indicate rank based on geological, geophysical, and geochemical properties within each polygon and their proximity to other polygons. Higher rank indicates more favorable properties within the polygon for the presence of porphyry copper deposits (altered rocks in mines omitted).

ASTER hydrothermal alteration map and outlines of alteration polygons southwest of Tucson, Arizona. Colors of alteration polygons indicate rank based on geological, geophysical, and geochemical properties within each polygon and their proximity to other polygons. Higher rank indicates more favorable properties within the polygon for the presence of porphyry copper deposits (altered rocks in mines omitted).

Sensor: Multispectral (approx. 4-12 bands)

Platform: Satellite

Author: John C. Mars
Email: jmars@usgs.gov
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Landscape Effects of Hydraulic Fracturing

High-resolution imagery from the National Agricultural Imagery Program (NAIP) was used to digitize the landscape disturbance related to hydraulic fracturing (“fracking”) and other forms of hydrocarbon extraction activity throughout the Marcellus Shale region of Pennsylvania from 2004 to 2010.  Specific topological features such as well pads, pipelines, and roads were extracted and developed into a temporal Geographic Information Systems (GIS) database to characterize the spatial footprint of unconventional (hydraulic fracturing) and conventional oil and gas development. Researchers used these data to measure the spatial extent of oil and gas development and to assess the exposure of the extant natural resources across the landscape of the watersheds in the study area. The project found that either form of development (1) occurred in ~50% of the 930 watersheds that defined the study area; (2) was closer to streams than the recommended safe distance in ~50% of the watersheds; (3) was in some places closer to impaired streams and state-defined wildland trout streams than the recommended safe distance; (4) was within 10 upstream km of surface drinking water intakes in ~45% of the watersheds that had surface drinking water intakes; (5) occurred in ~10% of state-defined exceptional value watersheds; (6) occurred in ~30% of the watersheds with resident populations defined as disproportionately exposed to pollutants; (7) tended to occur at interior forest locations; and (8) had >100 residents within 3 km for ~30% of the unconventional oil and gas development sites. Furthermore, the study found that exposure to the potential effects of landscape disturbance attributable to conventional oil and gas development was more prevalent than its unconventional counterpart.

http://egsc.usgs.gov/ms_sum.html

An example of the level of the intensity of oil and gas development in the form of wells, roads, and pipelines and how it can affect the landscape.

An example of the level of the intensity of oil and gas development in the form of wells, roads, and pipelines and how it can affect the landscape.

Sensor: An example of the level of the intensity of oil and gas development in the form of wells, and pipelines and how it can affect the landscape., roads

Platform: Airplane

Author: Terry Slonecker
Email: tslonecker@usgs.gov
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Mojave Desert Soils and Sediments Project

The BLM/USGS Mojave Desert soils and sediments project is investigating the mineralogy of the Clark Mountain Range, California, for associations of minerals with human health concerns and economic importance.  Soils, rock lithology, and dry lake surfaces are well exposed for mapping using image spectrometer data.  These lands have a wide variety of surface materials that are identifiable using spectral features unique to each mineral.  Mineral suites are directly relatable to mineral resources, such as rare earth deposits, hydrothermal systems, and evaporate (gypsum) dry lake deposits.  Human heath connections to soil type will be challenging, but naturally occurring fibrous or toxic minerals may be present in this area, including asbestos-form minerals and zeolites such as erionite.

Airborne Visible / Infrared Imaging Spectrometer (AVIRIS) data acquired in 2014 are being used for current mapping of the surface mineralogy.  Mapping algorithms (e.g., USGS Tetracorder and Prism Software) classify materials whose mineral identification will be confirmed with further analysis.  Maps of minerals and mineral groups will be assembled that will be interpreted for answers to important questions such as 1) are there minerals related to human health concerns, and if so, what are they and where are they located, 2) what type of mineral resources occur and where are they located within this study area.

http://crustal.usgs.gov/

Looking north to the Clark Mountains from Mountain Pass, California.

Looking north to the Clark Mountains from Mountain Pass, California.

NASA/JPL AVIRIS mosaic Color Infrared Composite Image of the Clark Mountains region.

NASA/JPL AVIRIS mosaic Color Infrared Composite Image of the Clark Mountains region.

Sensor: Hyperspectral

Platform: Airplane

Author: Keith Livo
Email: elivo@usgs.gov
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Geology and Soils

Lidar-Derived Elevation Modeling in Support of Geologic Mapping

Lidar technology is revolutionizing the field of geological mapping, leading to discoveries in a variety of related disciplines. As lidar acquisitions become more readily available, researchers have incorporated lidar-derived products in their analyses to precisely map features like active faults, landslides, sinkholes, flood inundation, surficial deposits, and the extent of bedrock geologic units. One such mapping initiative being conducted by the USGS delineates surficial deposits of wind-blown sand in the Atlantic Coastal Plain from western Georgia to central North Carolina. This area is known for having a complex geological history, and numerous questions regarding the origin of its surficial sand deposits remain unanswered. Lidar-derived elevation models allowed researchers to analyze landforms in much greater detail and discover features too subtle to be discerned in the field. Models reveal swaths of low-profile landforms, such as relict dunes and Carolina Bays, in striking detail. Geologic mapping efforts in this area are leading to better management of the Carolina Sandhills National Wildlife Refuge and improved understanding of relations between geology, paleoclimate, soils, and biology. Lidar data for this study were acquired by the South Carolina Department of Natural Resources (SCDNR) between 2008 and 2012. Data and descriptions of acquisitions are available via the National Map 3D Elevation Program and the SCDNR.

Lidar-derived elevation models in the Atlantic Coastal Plain.

Lidar-derived elevation models in the Atlantic Coastal Plain.

Sensor: Lidar (terrestrial or bathymetric)

Platform: Airplane

Author: Christopher Garrity; Christopher Swezey
Email: cgarrity@usgs.gov; cswezey@usgs.gov
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Locating Dust Sources and Cataloging Dust Storms

Monitoring dust emission from the western United States is important on both local and regional scales because of the effects on air quality, human health and safety, ecosystem function, and water availability. The Sources, Compositions, and Effects of Atmospheric Dust from American Drylands project develops and maintains a catalog of dust-emission events in the western United States that are visible in satellite imagery.  The overall objectives are to determine the location, size, frequency, duration, and transport patterns of dust events in western North America.  Although this catalog has broad applicability, it primarily complements ongoing work focusing on the effects of dust deposited on mountain snow cover.

Dust on mountain snow cover changes snow albedo and enhances the absorption of solar radiation, thereby increasing rates of snowmelt, which leads to earlier-than-normal spring runoff and overall smaller late-season water supplies for tens of millions of people and industries in the American West.  Identification of these dust-source areas guides field work and subsequent studies to understand dust properties that affect snow albedo.  The ability to link deposited dust to dust-source areas may inform mitigation of dust emissions that diminish Colorado River water resources.

http://gec.cr.usgs.gov/projects/sw/dust_detection/

The MODIS image to the left documents dust emission from many point sources along the Little Colorado River on the southern Colorado Plateau. The MODIS image to the right shows dust on snow throughout the Rocky Mountains, especially in the San Juan Mountains in Colorado.  The dust in this image includes the dust emitted from the southern Colorado Plateau shown in the image to the left.

The MODIS image to the left documents dust emission from many point sources along the Little Colorado River on the southern Colorado Plateau. The MODIS image to the right shows dust on snow throughout the Rocky Mountains, especially in the San Juan Mountains in Colorado.  The dust in this image includes the dust emitted from the southern Colorado Plateau shown in the image to the left.

Sensor: Multispectral (approx. 4-12 bands)

Platform: Satellite

Author: Harland Goldstein
Email: hgoldstein@usgs.gov
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Pleistocene Landscape Evolution of the Southern Rockies

Scientists at the USGS Geosciences and Environmental Change Science Center are utilizing newly implemented Quaternary chronologic techniques to determine when the present dramatic topography began to form and what induced it. Techniques include 10Be and 26Al cosmogenic nuclide, optically stimulated luminescence, U-series, and radiocarbon analyses that use various strategies to age date features in the landscape. These data are being coupled with geologic mapping of the structural, bedrock, neotectonic, and geomorphic features of the southern Rocky Mountains to understand the geomorphic history of the region.

 

Sensor: Lidar (terrestrial or bathymetric)

Platform: Airplane

Author: Cal Ruleman
Email: cruleman@usgs.gov
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Surficial Geologic Mapping

The Greater Platte River Basins (GPRB) are characterized by fragile ecosystems that may be particularly vulnerable to changes in climate and/or land use. Two such areas within the GPRB—the South Platte River corridor in eastern Colorado and the Niobrara National Scenic River in northern Nebraska—are the focus of surficial geologic mapping and research to provide a geologic framework for the ecosystems, and to better understand how their geomorphic systems have responded to environmental changes in the past.  Geologic mapping and geochronologic research are key to understanding the timing and causes of past landscape change, and lead to a better understanding of what might be done to adapt to, or mitigate, adverse effects from future changes in climate and/or land use. Field work is combined with various remotely sensed data, including National Aerial Photography Program (NAPP) color infrared photography, National Agriculture Imagery Program (NAIP) digital orthoimagery, and lidar data. The lidar data have been particularly useful for identifying and mapping subtle topographic features such as low fluvial scarps between young river terraces—which allow for a better understanding of recent river activity—and other geomorphologic features that are either naturally subtle or have been subdued by land use. Along the South Platte River corridor in eastern Colorado, much of the area has been extensively farmed and cultivated for more than a century; as a result, many geomorphologic features are difficult to distinguish in traditional orthoimagery or aerial photographs. However, in lidar images, geomorphologic features are commonly evident even within areas traversed by central pivot irrigation. For both areas, lidar data enhance recognition of valley margins, river terraces, eolian dune forms, natural and artificial levees, and floodwater inundation zones. Preliminary results of the geologic mapping and research document historical changes in the modern fluvial systems, and identify times during the Holocene and late Pleistocene when rates of change were high along the rivers and their tributaries.

http://gec.cr.usgs.gov/projects/platte/surficialmap.html

Part of the South Platte River corridor in eastern Colorado:  (A) 2015 NAIP orthoimagery, and (B) Quality-level 2 lidar data from the 2013 South Platte River Flood Area 1 lidar dataset. The imagery provides two different views of the same landscape and are used together to facilitate surficial geologic mapping along the river corridor.

Part of the South Platte River corridor in eastern Colorado:  (A) 2015 NAIP orthoimagery, and (B) Quality-level 2 lidar data from the 2013 South Platte River Flood Area 1 lidar dataset. The imagery provides two different views of the same landscape and are used together to facilitate surficial geologic mapping along the river corridor.

Sensor: Camera, Lidar (terrestrial or bathymetric), Multispectral (approx. 4-12 bands)

Platform: Airplane

Author: Margaret E Berry
Email: meberry@usgs.gov
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Hazards - Earthquakes

Earthquake Hazards and Landscape Change Research Using Terrestrial Lidar

The USGS Earthquake Science Center uses a 3D laser scanner to study surface deformation associated with active faults, to map fault zones, and to perform detailed analyses of landscape change associated with earthquakes, landslides, wildfires, and other natural phenomena. Specifically, these studies have allowed researchers to determine three-dimensional patterns of landscape deformation resulting from the 2014 South Napa Earthquake (http://www.geosociety.org/news/pr/2015/15-90.htm), have provided information to the National Park Service and San Francisco Public Utilities Commission regarding the magnitude of erosion affecting water quality following the 2013 Rim wildfire in Yosemite National Park, and have provided valuable mapping of fault zones to better locate research excavations and understand extent of surface deformation. In-progress work includes use of terrestrial lidar to measure aeseimic creep (surface deformation that occurs without damaging earthquakes) and landslide activity. USGS earthquake scientists also collaborate with researchers that operate small unmanned aerial vehicles (UAVs or drones) in order to assess error inherent in that emergent technology and to improve current methods of rapidly mapping areas affected by natural hazards.

 

The USGS Earthquake Science Center has collected terrestrial lidar data in many locations with diverse scientific objectives: PS – characterization of paleoseismological sites; FZ – map fault zones under canopy where airborne lidar resolution is insufficient; EQ – quantify coseismic and postseismic landscape deformation following earthquake (e.g. 2014 South Napa Earthquake); S/GF – analyze fault scarps and ground failure/liquefaction features from prehistoric earthquakes; C – measure fault creep; LS – landslide/erosion studies (postfire, earthflows, etc). Most of these sites have the secondary objective of data collection to be used as pre-earthquake baseline ultra-high-resolution

The USGS Earthquake Science Center has collected terrestrial lidar data in many locations with diverse scientific objectives: PS – characterization of paleoseismological sites; FZ – map fault zones under canopy where airborne lidar resolution is insufficient; EQ – quantify coseismic and postseismic landscape deformation following earthquake (e.g. 2014 South Napa Earthquake); S/GF – analyze fault scarps and ground failure/liquefaction features from prehistoric earthquakes; C – measure fault creep; LS – landslide/erosion studies (postfire, earthflows, etc). Most of these sites have the secondary objective of data collection to be used as pre-earthquake baseline ultra-high-resolution topographic data. Active faults are in purple.

 

Sensor: Camera, Lidar (terrestrial or bathymetric)

Platform: Ground based / sensor web / web cam, UAS

Author: Stephen DeLong
Email: sdelong@usgs.gov
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Nepal Earthquake Support

Shortly before noon on April 25, 2015, a massive earthquake registering 7.8 on the Richter scale struck central Nepal.  Just 3 hours later—around 4 a.m. Central Time—the USGS Earth Resources Observation and Science (EROS) Center disaster response coordinators were contacted by the emergency on-call officer from the International Charter on Space and Major Disasters:  Could the USGS provide coordinates to the National Geospatial-Intelligence Agency (NGA) so it could task several of its satellites to acquire high-resolution images of the quake zone?

Getting such a call is nothing new, as the USGS has been providing support to the International Charter since becoming a member in 2005.  The Charter is a mechanism for rapidly acquiring satellite imagery of locations impacted by natural or human-made disasters and getting that data, and products derived from them, into the hands of emergency responders and relief agencies as quickly as possible, at no charge.

How does it work?  When an earthquake, flood, oil spill, or other disaster occurs, a specially trained authorized user submits a request for satellite imagery and whatever other data or products are needed.  Authorized users can initiate the Charter response for a disaster occurring in their own country, or on behalf of someone from another country.  The request sets in motion the tasking of satellites (usually within just 2 to 3 hours) to capture images, and the subsequent delivery of data to whomever needs it.

The USGS has provided access to over 5,000 images on the Hazards Data Distribution System (http://hddsexplorer.usgs.gov) for the response to the Nepal earthquake.  The 2,100 high-resolution commercial images, which were provided by NGA through their contract with Digital Globe, have been made available to responders in 28 countries. 

http://www.disasterscharter.org

Landslide indicator map showing the locations of landslides as a result of the April 25, 2015, earthquake in Nepal.  Imagery was provided through the USGS to the users of the International Charter on Space and Major Disasters.

Landslide indicator map showing the locations of landslides as a result of the April 25, 2015, earthquake in Nepal.  Imagery was provided through the USGS to the users of the International Charter on Space and Major Disasters.

Sensor: Lidar (terrestrial or bathymetric), Multispectral (approx. 4-12 bands), Thermal

Platform: Airplane, Satellite

Author: Brenda Jones
Email: bkjones@usgs.gov
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The Fairweather Fault’s Ruptured Landscape

How often does the Fairweather Fault break in large earthquakes along the outer coast of Glacier Bay National Park in southeastern Alaska? Researchers at the USGS Alaska Science Center are mapping active surface traces of the Fairweather Fault to identify sites that may answer this question and reveal the frequency and size of past large earthquakes. By assessing past earthquake activity of the Fairweather Fault, scientists hope to improve the USGS National Seismic Hazard Map for the southeastern Alaska region.

The 1958 Lituya Bay earthquake (M 7.7) ruptured more than 260 km of the Fairweather Fault in southeastern Alaska, where the Yakutat block collides obliquely with North America. The fault, which accommodates ~46 mm/yr of dextral slip (greater than 90% of the Pacific–North American Plate motion), ruptured from Yakutat Bay to Cross Sound and produced ~3–6.5 m of dextral offset as measured in post-earthquake surveys conducted along the southern ~30 km of the fault between Crillon Lake and Icy Point , including over 1 m of vertical offset at one site. To identify potential paleoseismic sites, USGS scientists searched for similar features using new airborne lidar topography, Interferometric Synthetic Aperture Radar (IFSAR) orthorectified radar imagery, and historical aerial photography to map the geomorphic expression of the southern Fairweather Fault in densely vegetated, steep terrain. A “HeliPod” helicopter-mounted lidar system surveyed three ice-free sections of the fault over areas 4–6.5 km long by 1–4 km wide. Bare-earth digital terrain models (DTMs) derived from last-return point clouds (~1 pt/m2) revealed structures consistent with earthquake offset, including 1–5-m-high mostly east-facing scarps, linear troughs, slope benches, shutter ridges, ponded alluvium, and dextrally offset landforms, including 12 stream channels offset 12–128 m, and 2 moraines offset 40–79 m.

Coupled with offshore bathymetry, data reveal a ~20° restraining bend and 3–4 km right step between offshore and onshore fault traces at Icy Point. South of the restraining bend, the linear offshore fault trace expresses strike-slip morphology. Within the bend, an array of right-stepping en-echelon folds and faults appear to accommodate transpression. North of the restraining bend, fluvial and marine terraces that only occur west of the onshore fault trace indicate west-side-up transpressional deformation. The change in deformation style across the restraining bend coincides with the southernmost impingement of the Yakutat block in southeastern Alaska. By using remote sensing data and new offshore bathymetric data together, researchers have identified promising field sites to assess the earthquake history along the southern Fairweather Fault.

Caption: (a) Color shaded relief map derived from lidar data acquired along the Fairweather Fault southeast of Crillon Lake. Warm colors reflect higher elevations; cool colors reflect lower elevations.

(a) Color shaded relief map derived from lidar data acquired along the Fairweather Fault southeast of Crillon Lake. Warm colors reflect higher elevations; cool colors reflect lower elevations. Crillon Lake is ~100 m above sea level, whereas North Dome is over 800 m above sea level. The Fairweather Fault (arrows) forms a conspicuous crease through a narrow valley along the northwestern flank of North Dome. The black-and-white background image is 2.5-m resolution interferometric synthetic aperture radar (IFSAR) orthorectified intensity image (ORI) provided by the USGS. (b) Lidar data were collected using a “Helipod” system mounted onto a Robinson R-44 helicopter. (c) The laser scanner of the “Helipod” lidar system is in a box bolted to the side of the helicopter. The system also uses a GPS receiver to record geographic position, and an inertial measurement unit (IMU) to record angular velocity and acceleration data during the helicopter flight.

Sensor: Camera, IFSAR / SAR / Radar, Lidar (terrestrial or bathymetric)

Platform: Airplane, Helicopter, Satellite

Author: Rob Witter
Email: rwitter@usgs.gov
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Hazards - Fires

LANDFIRE Modeling Dynamic Fuels with an Index System Innovations

Feedback from end users of LANDFIRE fuels data suggests that static fuel model layers, which represent average fire conditions, have limited utility in areas where seasonal conditions have profound impacts on available fuels.  To address this issue, LANDFIRE is developing methodologies to modify fuels data based on seasonal conditions, an effort dubbed Modeling Dynamic Fuels with an Index System (MoD-FIS).  Multiple methods are being developed in different areas since different processes impact fuel conditions around the U.S.  The first two regions investigated were the Southeast and the Great Basin/Southwest.

In the Southeast, soil moisture and drought conditions have the greatest impact on surface fuel availability.  A method was developed to modulate the LANDFIRE surface fuel model layer based on Keetch-Byram Drought Index values interpolated from weather stations across the region.  Implemented within the Wildland Fire Decision Support System, LANDFIRE MoD-FIS data are now available for fire behavior analysts to incorporate into operational fire modeling efforts to support strategic planning and tactical incident response. 

In the Great Basin and Southwest regions, herbaceous vegetation growth, as a product of available precipitation, is the primary driver of surface fuel conditions.  Landsat imagery from a 10-year time series was analyzed to determine the average vegetation conditions over that period.  Correlating these values with herbaceous cover estimates resulted in a model of herbaceous fuel availability based on image-derived vegetation conditions. 

Landsat imagery from seasonal green-up periods is then combined with the previously developed model to determine herbaceous fuel availability for the current time period.  The current conditions are compared with the 10-year average conditions, and the departure from average is used to determine new surface fuel model assignments.  These provisional products are being tested by local fire managers and have shown great promise thus far.  Planning for operational production and distribution of these products is underway.

Development efforts for creating MoD-FIS data in other parts of the U.S. are currently being researched.  The program’s goal is to provide MoD-FIS products for the entire country.

http://www.landfire.gov

Landsat image-derived vegetation cover for the Southwest/Great Basin region of the U.S.  The darker colors represent dense vegetation cover, while the light colors show sparser areas.  This data allows for existing LANDFIRE surface fuel layers to be refined using current estimates of herbaceous cover.

 

Landsat image-derived vegetation cover for the Southwest/Great Basin region of the U.S.  The darker colors represent dense vegetation cover, while the light colors show sparser areas.  This data allows for existing LANDFIRE surface fuel layers to be refined using current estimates of herbaceous cover.

 

Sensor: Multispectral (approx. 4-12 bands)

Platform: Satellite

Author: Kurtis Nelson
Email: knelson@usgs.gov
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Landsat Burned Area Essential Climate Variable

Essential climate variables (ECVs) are used to track critical attributes of atmospheric, oceanic, and terrestrial systems over time scales appropriate for analyzing their relationships with climate change. As part of a larger Climate Data Record (CDR) and ECV Development project, scientists at the USGS Geosciences and Environmental Change Science Center in Denver, Colorado, have led the development and validation of the Burned Area ECV algorithm. This algorithm automatically extracts burned areas from Landsat imagery, which has a spatial resolution of 30 m and a temporal resolution of 16 days or more, depending on cloud cover. Fires are frequently unreported; consequently, existing fire databases are often incomplete. Furthermore, these databases often have location errors, and records may be duplicated. The Burned Area ECV products will provide new and unique information about spatial and temporal patterns of fire occurrence that existing fire databases may lack, especially in areas such as the shrub and grassland ecosystems in the Great Plains and in the western and southeastern United States.

Validation protocols have been established incorporating and adapting the Committee on Earth Observation Satellites (CEOS) Land Product Validation (LPV) Subgroup's best practice guidelines in collaboration with the European Space Agency (ESA) Climate Change Initiative ECV Fire Disturbance (Fire_cci) validation team. Validation data collection is underway for a number of Landsat path/row scenes in the United States; the data will be used to quantitatively assess the accuracy of the Burned Area ECV and to identify areas for improvement in future algorithm versions.

http://remotesensing.usgs.gov/ecv/BA_overview.php

Landsat Burned Area Essential Climate Variable products for the conterminous U.S. for (A) 1985–1994, (B) 1995–2004, and (C) 2005–2014.

Landsat Burned Area Essential Climate Variable products for the conterminous U.S. for (A) 1985–1994, (B) 1995–2004, and (C) 2005–2014.

Sensor: Multispectral (approx. 4-12 bands)

Platform: Satellite

Author: Todd Hawbaker
Email: tjhawbaker@usgs.gov
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Lidar Assessment of the Black Forest Wildfire

Prolonged drought and climate change continue to increase the prevalence and severity of wildland fire, while the growing number of houses set within natural areas around urban developments (i.e., within the wildland urban interface [WUI]) adds to the potential hazard exposure. Characterizing the risk to WUI housing from wildfire is an important area of natural hazards and applied remote sensing research. This project is investigating how lidar data can be used to describe the vertical structure and fine-scale fuel characteristics within the home ignition zone. Using the Black Forest Fire of 2013 near Colorado Springs, Colorado, this research is generating lidar-derived vegetation measures, structure characteristics, and landscape features to quantify the prefire conditions that increased or decreased the likelihood of structure ignition and consumption in the State’s most destructive wildfire event to date. In addition to addressing this disaster, answers derived from these methods are useful to inform hazard mitigation decisions across the growing wildland urban interface in the western United States.

http://geography.wr.usgs.gov/science/fire/

Aerial view of Colorado's Black Forest wildfire of 2013 showing the burn perimeter (red boundary) and the locations of destroyed (red) and unaffected structures (green).

Aerial view of Colorado's Black Forest wildfire of 2013 showing the burn perimeter (red boundary) and the locations of destroyed (red) and unaffected structures (green).

Sensor: Lidar (terrestrial or bathymetric), Multispectral (approx. 4-12 bands)

Platform: Airplane, Satellite

Author: Jason Kreitler
Email: jkreitler@usgs.gov
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Monitoring Fire Disturbance

The Landsat series of satellites provide remotely sensed data suitable for mapping wildfire disturbance.  However, the sensors on board the current and historical Landsat satellites vary in terms of the spatial resolution, number of spectral bands, bandwidths, and overall data quality and calibration characteristics.  To date, the USGS and others have used Landsat data collected from the Landsat Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+), and Operational Land Imager (OLI) era (1984–present) to map wildfire disturbance.  Historical fire mapping efforts, however, have essentially ignored the era from the launch of Landsat 1 through Landsat 4 (1972–1983).  The data collected during this period by Landsat’s Multispectral Scanner (MSS) sensors are suitable for fire mapping but possess different spatial resolution and spectral band characteristics than data collected by TM, ETM+, and OLI.  In order to provide a longer time series of fire occurrence and burn severity for the assessment of climate change impacts on burn severity trends, it is necessary to develop a burn severity characterization method that calibrates indices derived from Landsat MSS and TM/ETM+/OLI data.

Both the MSS and TM/ETM+/OLI results must be adjusted to a common spectral and spatial scale to facilitate the comparison of continuous burn severity indices through the full Landsat era.  Methodologies have been identified that are suitable to detect, map, and monitor fire disturbances in the 1972–1983 time period using Landsat 1–4 MSS data and then calibrate both MSS results and similar results derived from TM/ETM+/OLI fire data records for 1984–present.  Automated scripts have been written to efficiently calibrate multiple fire mapping datasets across large landscapes.  Historical MSS, TM, ETM+, and OLI burn mapping datasets have been acquired or derived for study areas in the Mojave bioregion, selected watersheds in Colorado, and other locations across the country.  These Landsat image datasets will be used to test and validate the calibration techniques and automated processing algorithms.  Perhaps of more critical importance, however, the effort will demonstrate the science value of historical wildland fire disturbance mapping and monitoring for the full Landsat era from 1972 to the present. 

Categorical burn severity for the Mojave bioregion for 1972–2008.  Landsat Multispectral Scanner data were used to generate the 1972–1983 fire location and burn severity information.  Within the severity map, dark green is non-burn, light blue is low severity, yellow is moderate severity, and red is high severity.  The brown line is the Mojave bioregion boundary.

Categorical burn severity for the Mojave bioregion for 1972–2008.  Landsat Multispectral Scanner data were used to generate the 1972–1983 fire location and burn severity information.  Within the severity map, dark green is non-burn, light blue is low severity, yellow is moderate severity, and red is high severity.  The brown line is the Mojave bioregion boundary.

Sensor: Multispectral (approx. 4-12 bands), Thermal

Platform: Satellite

Author: Randy McKinley
Email: rmckinley@usgs.gov
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Prefire and Postfire Lidar Burn Severity Analysis

This project addresses several wildfire research questions using a unique remote sensing opportunity to analyze prefire and postfire lidar data. The Pole Creek Fire burned 27,000 acres through various forest types in October 2012 in Deschutes National Forest near Sisters, Oregon. Lidar data were collected prior to the wildfire, offering a unique opportunity to investigate fire disturbance impacts and processes with high-resolution data.

Current research efforts include a comparison of lidar and Landsat-derived burn severity, estimation of biomass loss and carbon accounting using lidar and Moderate Resolution Imaging Spectroradiometer (MODIS) fire radiative energy, and fuel treatment and mountain pine beetle infestation effects on ensuing fire severity using multitemporal lidar data. This research is quantifying how prefire forest condition affects burn severity, and how various remote sensing techniques can be used to explain fire patterns and improve modeling of wildland fire and forest ecology.

http://geography.wr.usgs.gov/science/fire/

Location of Pole Creek Fire in central Oregon and the overlap of viable lidar and Landsat imagery (from McCarley et al.).

Location of Pole Creek Fire in central Oregon and the overlap of viable lidar and Landsat imagery (from McCarley et al.).

Sensor: Lidar (terrestrial or bathymetric), Multispectral (approx. 4-12 bands)

Platform: Airplane, Satellite

Author: Jason Kreitler
Email: jkreitler@usgs.gov
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Remapping LANDFIRE Vegetation and Fuels Data

LANDFIRE, the Landscape Fire and Resource Management Planning Tools Program, is a vegetation, fire, and fuel characteristic mapping program managed by the U.S. Department of Agriculture Forest Service and the U.S. Department of the Interior, in partnership with The Nature Conservancy.  LANDFIRE represents the first and only complete, nationally consistent collection of over 20 geospatial layers, databases, and ecological models depicting potential and existing vegetation, surface and canopy fuels, and fire regimes information that can be used across multiple disciplines to support cross-boundary planning, management, and operations across all lands of the United States and insular areas. LANDFIRE data products are designed to be used at landscape scales in support of strategic vegetation, fire, and fuels management planning to evaluate management alternatives across boundaries. LANDFIRE data products facilitate national and regional level strategic planning and reporting of wildland fire and natural resource management activities, as well as tactical incident response to large wildland fires.

The first LANDFIRE mapping effort began in 2004 based on Landsat data from circa 2001. Although many changes on the landscape have been captured through periodic updates using geospatial disturbance data and image-based change detection information, current LANDFIRE data products maintain this 2001 foundation.  Additional landscape changes not captured in the disturbance data, subtle vegetation and landscape changes from insects or disease damage or other sources, and mis-classifications in the original LANDFIRE data products are being addressed through development of a comprehensive remap process. The LANDFIRE remap effort provides an opportunity for the program to evaluate past production processes and methods of using remotely sensed and field data for map development. This review will include exploring additional mapping methods to maximize the use of the available data and past mapping efforts, and provide a characteristic representation of contemporary conditions for areas that are undergoing change.

As part of the LANDFIRE remap, newer spatial data sources will be investigated including Landsat 8, Sentinel-2, and lidar. New field plot data will also be incorporated including National Resource Conservation Service National Resource Inventory data. Finally, broadening program partnerships, including with the USGS Gap Analysis Program, will combine with these data sources to create a new base map data suite that improves upon the legacy LANDFIRE data products.

http://www.landfire.gov

In this May 2016 image, LANDFIRE team members are pictured gathering new field data in a remap prototype area of central Idaho.

In this May 2016 image, LANDFIRE team members are pictured gathering new field data in a remap prototype area of central Idaho.

Sensor: Lidar (terrestrial or bathymetric), Multispectral (approx. 4-12 bands)

Platform: Airplane, Satellite

Author: Kurtis Nelson
Email: knelson@usgs.gov
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Remote Sensing Support for Burned Area Emergency Response Teams

Since 2003, the USGS Earth Resources Observation and Science (EROS) Center and the U.S. Forest Service (USFS) Remote Sensing Applications Center (RSAC) have jointly provided satellite-derived burn severity mapping products to meet the requirements of DOI and USFS Burn Area Emergency Response (BAER) teams. BAER teams are mandated to quickly (within 2 weeks) evaluate the effects of wildland fires and develop mitigation plans to safeguard valuable natural resources, protect human life and property, and promote landscape recovery. Derived from Landsat images, the soil burn severity map is a major resource used by the BAER teams to develop postfire hazard mitigation prescriptions. Additionally, burn severity maps are provided to USGS Landslide Hazards staff to support ongoing debris flow modeling and prediction analyses associated with wildland fires.

The USGS EROS Center rapidly processes Landsat and other satellite imagery enabling the timely generation of map products for large wildland fires on DOI-managed lands, generally less than 2 days after fire containment. These map products allow the BAER teams to better understand the patterns of burn severity and make more precise mitigation recommendations. Since 2003 and through the 2015 fire season, the USGS and USFS have mapped 1,594 wildfires representing 46.7 million burned acres in support of BAER and local DOI and USFS land managers.

In 2016, wildland fire activity on DOI-managed lands is expected to be extensive. By early June, the USGS had responded to five DOI requests for burn area mapping support. Additionally, USGS assistance was requested by the Provincial Operations Centre in Edmonton, Alberta, Canada, to help with the acquisition of Landsat and other satellite imagery for the over 1-million acre wildfire near Fort McMurray.

http://eros.usgs.gov/landscape-dynamics/fire-science

http://www.fs.fed.us/eng/rsac/baer/

Landsat postfire image (September 20, 2015; left) and preliminary soil burn severity map superimposed on a Landsat prefire image (September 1, 2014; right) for the August/September 2015 National Creek Complex fire in Oregon’s Crater Lake National Park.  The fire burned 16,744 acres just north of Crater Lake and was the largest in the recorded history of the park. Within the postfire image, the burn scar is medium to bright red while vegetation is various shades of green. Within the burn severity map, dark green is non-burn, light blue is low severity, yellow is moderate severity, and red is high severity. The approximate burn perimeter is designated by a red polygon in both images.

Landsat postfire image (September 20, 2015; left) and preliminary soil burn severity map superimposed on a Landsat prefire image (September 1, 2014; right) for the August/September 2015 National Creek Complex fire in Oregon’s Crater Lake National Park.  The fire burned 16,744 acres just north of Crater Lake and was the largest in the recorded history of the park. Within the postfire image, the burn scar is medium to bright red while vegetation is various shades of green. Within the burn severity map, dark green is non-burn, light blue is low severity, yellow is moderate severity, and red is high severity. The approximate burn perimeter is designated by a red polygon in both images.

Sensor: Multispectral (approx. 4-12 bands)

Platform: Satellite

Author: Randy McKinley
Email: RMcKinley@usgs.gov
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Hazards - Other

Aerial Videography Captures Forest Damage from Hurricane Sandy

The substantial damage that Hurricane Sandy inflicted on coastal communities and surrounding wetlands resulted primarily from an associated storm surge of record extent and impact.  In the hardest hit area, Federal lands, national parks, and wildlife refuges are interspersed  with a dense urban landscape where the impact to estuaries, wetlands, and coastal forests is more diffuse and difficult to quantify spatially without the aid of aerial photographic and satellite imagery.  Access points to these land units and natural resources adjoining roads showed wide-area tree mortality and downed forests of unknown extent and severity. While wind strength and damage from Hurricane Sandy was greatest at landfall in New Jersey, inundation occurred along the entire eastern seaboard from Florida to Maine, eroding shoreline, driving saltwater inland, and uprooting trees.

DOI land managers require information on the extent of forest damage to guide decisions about recovery, research and restoration.  The USGS has long used its seaplane asset with camera mount and portal to accomplish post-hurricane reconnaissance missions for the benefit of rapid assessment of damages to natural and cultural resources.  A flight plan was implemented to conduct low-altitude videography over select DOI land units along the East Coast from North Carolina to New Jersey that obtained high-resolution imagery to assess forest damage by documenting disturbed canopy and downed trees.  The imagery scale of video frames was calibrated to capture whole trees and forest gaps suitable for determining tree fall compass direction and forest cover.  Collective video frame analyses were conducted to achieve an understanding of spatial impact at the landscape scale and causal relations of treefall by wind and surge.

A USGS Web portal hosts the raw image files for public access and use by other USGS scientists and agency partners; these georeferenced photos document Hurricane Sandy’s impact and post-storm landscape condition for future studies of forest recovery and succession. The project will produce an understanding of the interaction between soil liquefaction caused by storm surge tides and hurricane wind force and direction that can be applied in spatially-explicit landscape simulation models.  These models will help anticipate responses of forested ecosystems under future climate change, which predicts hurricanes of increasing frequency and intensity. Raw files of video imagery are posted on the USGS Hurricane Sandy Web Portal at http://nwrcwebapps.cr.usgs.gov/sandy/.

http://nwrcwebapps.cr.usgs.gov/sandy/

Aerial reconnaissance imagery of natural color and infrared videography of select DOI parks and refuges along the East Coast impacted by Hurricane Sandy.

Aerial reconnaissance imagery of natural color and infrared videography of select DOI parks and refuges along the East Coast impacted by Hurricane Sandy.

Sensor: Camera, Video

Platform: Airplane

Author: Thomas Doyle
Email: doylet@usgs.gov
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Assessing Vulnerability to Drought in Dryland Ecosystems

Scientists at the USGS Southwest Biological Science Center are partnering with the USGS Western Geographic Science Center, the USGS Earth Resources Observation and Science Center, and the University of Arizona to help managers plan for and manage drought-impacted ecosystems in the western U.S. by conducting research that synthesizes plot-based and remotely sensed vegetation monitoring data. Analyses using a time series of Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat-derived vegetation indices reveal the importance of critical climate windows and pivot points that drive vegetation condition across ecoregions of the western U.S. The team is working to understand how landscape and soil attributes, in combination with management actions, mediate climate-vegetation relationships and the balance between grasses and woody plants, which has important implications for ecosystem function. The team is building short-term forecasts of vegetation condition using multi-model ensembles of climate and water balance variables that can help managers make short-term decisions and plan for long-term changes in vegetation composition and distribution.

https://nccwsc.usgs.gov/display-project/5050cb0ee4b0be20bb30eac0/551ad102e4b03238427837ba

Perennial vegetation cover between 2000 and 2010 in the Mojave Desert has changed substantially due to prolonged drought and land use effects. USGS research is helping managers understand ecological drought and its implications for ecosystem structure and function. Abbreviations: DEVA, Death Valley National Park; JOTR, Joshua Tree National Park; MOJA, Mojave National Preserve.

Perennial vegetation cover between 2000 and 2010 in the Mojave Desert has changed substantially due to prolonged drought and land use effects. USGS research is helping managers understand ecological drought and its implications for ecosystem structure and function. Abbreviations: DEVA, Death Valley National Park; JOTR, Joshua Tree National Park; MOJA, Mojave National Preserve.

Sensor: Multispectral (approx. 4-12 bands)

Platform: Satellite

Author: Seth Munson
Email: smunson@usgs.gov
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Enhanced Services and Tools for Emergency Response

As part of its mission to provide timely and relevant remotely sensed imagery and related datasets for disaster support, the USGS Earth Resources Observation and Science (EROS) Center Emergency Operations project implemented several new tools and capabilities intended to expand on existing services for domestic and international emergency response.

The first new capability was an interactive, map-based Collection Management Tool (CMT; http://cmt.usgs.gov/) for incoming user requests.  Concurrent with the CMT release in mid-2015, a new emergency response Web portal was launched (http://eoportal.usgs.gov/) to provide supporting information on the USGS EROS emergency response capabilities, services and data access, and other topics.  The third major development released in early 2016 provides an enhanced capability for search, access, and visualization of image-derived map products and other related datasets through the USGS Hazards Data Distribution System (HDDS), http://hddsexplorer.usgs.gov/. 

All three of these new capabilities were developed and tested in direct response to end user input, experiences, and feedback.  Together, this suite of new tools and services will allow the USGS to continue to enhance its support for the broad community of agencies and organizations engaged in emergency response. 

http://eoportal.usgs.gov/

Screen example showing the emergency operations Web portal that was released in February 2015.  The updated Web site features many new and expanded content areas and includes information on USGS EROS emergency response services, data access, International Charter, and many other topics.

Screen example showing the emergency operations Web portal that was released in February 2015.  The updated Web site features many new and expanded content areas and includes information on USGS EROS emergency response services, data access, International Charter, and many other topics.  

Sensor: Lidar (terrestrial or bathymetric), Multispectral (approx. 4-12 bands), Therma

Platform: Satellite

Author: Brenda Jones
Email: bkjones@usgs.gov
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Fifteen Years of Collaborative Disaster Response

The International Charter on Space and Major Disasters formed in November 2000 to provide a unified system of emergency response satellite data to areas that have been struck by disasters resulting in loss of life and widespread destruction around the world.  The Charter draws on the capabilities and resources of its 15 national space agencies and space operators to quickly provide satellite data at no cost to those in need.

Over the last 15 years, the Charter has brought space assets into action in over 115 countries for more than 450 natural and anthropogenic disasters, including floods, hurricanes, tsunamis, earthquakes, forest fires, and oil spills.  The Charter coordinates data from dozens of international satellites at varying resolutions to provide a quick response to disaster-afflicted areas.

The Charter member representatives celebrated by wearing matching International Charter 15th Anniversary t-shirts.  To commemorate this special anniversary, the European Space Agency (ESA) coordinated the production of this scribble video, https://www.youtube.com/watch?v=vif1kqwfCEc.

https://eros.usgs.gov/science/hazards-disasters

The International Charter 15th anniversary was celebrated at the USGS Earth Resources Observation and Science (EROS) Center.

The International Charter 15th anniversary was celebrated at the USGS Earth Resources Observation and Science (EROS) Center.

Sensor: Lidar (terrestrial or bathymetric), Multispectral (approx. 4-12 bands), Thermal

Platform: Airplane, Satellite

Author: Brenda Jones
Email: bkjones@usgs.gov
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Hurricane Sandy Surge and Marsh Dieback

Detection of hurricane surge impacts requires regional mapping of surge flooding duration and estimation of abnormal change in wetland condition.  To assess the impacts of Hurricane Sandy to coastal wetlands along the New Jersey Atlantic shore, USGS scientists studied the potential causal linkage of surge persistence and marsh condition. Surge persistence was estimated using a time series of TerraSAR-X and COSMO-SkyMed synthetic aperture radar (SAR)-based surge extents. Satellite Pour l’Observation de la Terre (SPOT) and Moderate Resolution Imaging Spectroradiometer (MODIS) were analyzed to estimate the loss of green biomass as a measure of marsh condition change before and after landfall.            

High correspondence in surge persistence and change in marsh surrounding and to the north of Great Bay suggest a causal relationship. Surge flooding persisted for 12 hours past landfall in marshes from Great Egg Harbor Bay to north of Great Bay.  Surge persisted up to 59 hours surrounding Great Bay and decreased to 12 hours after landfall in marsh to the north. Marsh condition exhibited a similar intensity pattern: high change surrounding Great Bay decreased to low change in marsh condition moving to the north. The spatial correspondence of persistence and marsh condition change reflects the similarity in their spatial patterns. High persistence and high condition change exhibited high spatial correspondence in marsh surrounding Great Bay just to the right of where Hurricane Sandy made landfall. To the north of Great Bay, moderate to low surge persistence and marsh condition change showed high correspondence.

In contrast, non-correspondence of marsh condition change and persistence dominated the interior marshes of the Great Bay and Great Egg Harbor Bay estuaries. These estuaries exhibited little change in marsh condition while sustaining high flood persistence. Salinity measurements suggest that these areas were influenced by freshwater discharges after landfall possibly mitigating damage. Back-barrier lagoon marshes to the south of Great Bay exhibited a mixture of correspondences. High persistence was as often related with low as with high marsh condition change. Low persistence exhibited similar mixed correspondence. 

These results provide a framework for monitoring wetland resilience and inundation patterns in order to protect floodplain ecosystems, mitigate flood hazards, sustain biodiversity, and contribute to effective land use planning.

http://dx.doi.org/10.1080/01431161.2016.1163748

(a) New Jersey coastal marsh study area (marsh in red, box outlines area shown in b, c, and d. (b) Surge persistence, (c) marsh condition change maps, and (d) the coincidence matrix showing their spatial association.

(a) New Jersey coastal marsh study area (marsh in red, box outlines area shown in b, c, and d. (b) Surge persistence, (c) marsh condition change maps, and (d) the coincidence matrix showing their spatial association.

Sensor: IFSAR / SAR / Radar, Multispectral (approx. 4-12 bands)

Platform: Satellite

Author: Amina Rangoonwala
Email: rangoonwalaa@usgs.gov
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Improved Drought Monitoring with New Soil Moisture Observations

Drought monitoring and early warning requires a convergence of evidence from varied sources with enough lead time for mitigation and other management actions. Soil moisture is a key state variable that controls the partitioning of precipitation into runoff and the rate of landscape evapotranspiration (ET).   To record soil moisture measurements, NASA developed the Soil Moisture Active Passive (SMAP) satellite mission, which was designed to measure the amount of water in the upper 2 inches (5 cm) of soil everywhere on the Earth’s surface.  SMAP science objectives are to understand processes that link the terrestrial water, energy, and carbon cycles; to estimate global water and energy fluxes at the land surface; to quantify net carbon flux in boreal landscapes; to enhance weather and climate forecast skill; and to develop improved flood prediction and drought monitoring capabilities.

Through the early adopters program, the DOI North Central Climate Science Center (NC CSC) in conjunction with the USGS Earth Resources and Observation Science (EROS) Center was able to quickly evaluate SMAP soil moisture data products soon after the launch of the sensor on January 31, 2015. Results show that SMAP soil moisture correlated well with in situ soil moisture, gridded rainfall, and model-derived evapotranspiration, building confidence in SMAP’s utility for drought monitoring and early warning applications. This research is published as: Velpuri, N.M., Senay, G.B., Morisette, J.T. (2016). Evaluating New SMAP Soil Moisture for Drought Monitoring in the Rangelands of the US High Plains, Rangelands, 38:4, p183-190.

http://smap.jpl.nasa.gov/

Study area showing hydrologic units (HUC8 watersheds) that are dominated by grasslands and shrublands. Stars represent locations of United States Climate Reference Network (USCRN) soil moisture observation sites used in the study. Background image is 8-day average SMAP Soil Moisture fields summarized for March 30–April 7, 2015.

Study area showing hydrologic units (HUC8 watersheds) that are dominated by grasslands and shrublands. Stars represent locations of United States Climate Reference Network (USCRN) soil moisture observation sites used in the study. Background image is 8-day average SMAP Soil Moisture fields summarized for March 30–April 7, 2015.

Sensor: IFSAR / SAR / Radar

Platform: Satellite

Author: Jeff Morisette
Email: morisettej@usgs.gov
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QuickDRI: A New Tool in the Remote Sensing Toolbox for Drought Monitoring

Drought is an equal-opportunity natural hazard: it can strike any part of the country at almost any time.  Drought conditions can vary tremendously across space and time, from short, extreme events that often involve high temperatures and greatly decreased precipitation, to season-long episodes of extended precipitation deficits. Despite the inherent variability in drought events, they are often associated with many negative effects on crops, livestock, water supply, wildlife and their natural habitats, and human health. No two droughts are alike and, as a result, many types of observations and models are used to monitor drought conditions.  A new indicator, called the Quick Drought Response Index, or QuickDRI, is being developed to fill the need to identify and characterize rapidly developing, flash-drought events. QuickDRI provides complementary information to another seasonal drought indicator, the Vegetation Drought Response Index, or VegDRI.

QuickDRI serves as a drought alarm and is designed to have improved sensitivity to early-stage drought conditions and rapidly evolving drought events.  This index is calculated using similar methods to VegDRI.  QuickDRI models incorporate multiple remote sensing- and climate-based input variables that portray key components of the hydrologic cycle influencing drought-related vegetation stress (for example, evapotranspiration [ET], soil moisture, and vegetation index-based plant health).

The QuickDRI project involves researchers at the National Drought Mitigation Center and the Center for Advanced Land Management Information Technologies at the University of Nebraska–Lincoln, the USGS Earth Resources Observation and Science Center, the U.S. Department of Agriculture’s Agriculture Research Service, and the Land Data Assimilation Systems at NASA Goddard Space Flight Center. Weekly operational QuickDRI maps are expected to be in regular production in late summer 2016 and available from an interactive viewer at the Monitoring Vegetation Drought Stress website (http://vegdri.cr.usgs.gov/).

http://vegdri.cr.usgs.gov/

Example of the Quick Drought Response Index (QuickDRI) for May 27, 2012.  The index reflects increasing stress on vegetation especially across southern Missouri, southern Illinois, and northern Arkansas.  This regional pattern coincides with much higher than normal temperatures and much lower than normal precipitation during April and May.

Example of the Quick Drought Response Index (QuickDRI) for May 27, 2012.  The index reflects increasing stress on vegetation especially across southern Missouri, southern Illinois, and northern Arkansas.  This regional pattern coincides with much higher than normal temperatures and much lower than normal precipitation during April and May.

Sensor: Multispectral (approx. 4-12 bands)

Platform: Satellite

Author: Jesslyn F. Brown
Email: jfbrown@usgs.gov
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Space-based Tracking of Inundated Area Dynamics

The Dynamic Surface Water Extent (DSWE) product under development at the USGS can be used to systematically characterize cycles and changes in surface inundation for a broad variety of applications. DSWE presents the results of tests for the presence of open water and mixtures of surface water and vegetation in Landsat Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+) and Operational Land Imager (OLI) image pixels collected over the United States. As one regional-scale example, DSWE data from 1984 through 2015 were used to calculate the yearly proportion of pixels free of clouds, cloud shadows, and snow that are classified as “open water” for the entire Chesapeake Bay Watershed (CBW). These proportions resulted in a time series of CBW areas that were consistently inundated on an annual basis. Such data can in turn be summarized over smaller areas such as watersheds or counties. A county-level assessment of changes between 1985 and 2015 in the CBW identified Sussex County as having a relatively large increase in perennially inundated area. A semi-decadal subset of these maps shows the consistent trend toward greater perennially open water in the area of the Prime Hook National Wildlife Refuge. Restoration efforts are currently underway to reverse this trend; the derivation of DSWE from Landsat images collected in the future will hopefully show decreases in open water as those areas are replaced by improved habitat (i.e., water/vegetation mixtures). Research is underway to increase DSWE thematic accuracy and temporal resolution by combinating Landsat scenes with other remotely sensed images and in situ monitoring data. For the end user, the DSWE product will provide a cost-effective, temporally consistent means of assessing inundation dynamics over intra- and inter-annual periods not only for habitat and water resource management, but for climate and land use change science and forecasting. This work is supported by the USGS Land Remote Sensing and Land Change Science Programs.

http://remotesensing.usgs.gov/ecv/SWE_overview.php

Maps depicting the proportion of times each year that a location was classified as “open water”.  These images show an increase in perennially inundated land at the expense of vegetated wetland habitat in the Prime Hook National Wildlife Refuge, Delaware. Continued systematic collection and processing of remotely sensed data to standard, publicly available products will help managers efficiently assess whether restoration actions are producing intended results.

Maps depicting the proportion of times each year that a location was classified as “open water”.  These images show an increase in perennially inundated land at the expense of vegetated wetland habitat in the Prime Hook National Wildlife Refuge, Delaware. Continued systematic collection and processing of remotely sensed data to standard, publicly available products will help managers efficiently assess whether restoration actions are producing intended results.

 

Sensor: Lidar (terrestrial or bathymetric), Multispectral (approx. 4-12 bands), Thermal

Platform: Ground based / sensor web / web cam, Satellite, UAS

Author: John Jones
Email: jwjones@usgs.gov
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Hazards - Volcanoes

High-resolution Monitoring of Mount St. Helens Crater

The catastrophic eruption of Mount St. Helens in Washington State on May 18, 1980, removed the upper 400 m of the volcano and left a large horseshoe-shaped crater.  Two subsequent eruptive episodes, in 1980–1986 and 2004–2008, partially filled this crater with domes of solidified lava, and glacial ice has coated much of the remaining crater floor.  Global Positioning System data suggest that the 1980–1986 lava dome is subsiding by a few centimeters per year, but the spatial pattern of this deformation cannot be discerned from one measurement alone.

New high-resolution “staring spotlight” synthetic aperture radar (SAR) data collected by the German TerraSAR-X satellite, combined with a lidar digital elevation model, provide a high-resolution (25 cm) view of Mount St. Helens crater.  By interferometrically combining SAR scenes acquired on different dates, it is possible to measure surface displacements that have occurred over the ensuing time period.  These data indicate that the 2004–2008 lava dome is subsiding rapidly, by a few centimeters per week, with spatial variations in deformation date roughly correlative with dome thickness.  The 1980–1986 dome is also subsiding, but at a much lower rate of a few centimeters per year, likewise variable according to dome thickness.  In addition, motion of rock glaciers along the crater walls is apparent.  A better understanding of the post-eruptive behavior of lava domes is critical to monitoring for signs of future activity.  Signs of renewed magma ascent beneath the crater will likely disturb the subtle pattern of dome subsidence and should be detectable using high-resolution SAR data.  Mapping dome deformation may also reveal the thermal characteristics of the lava and provide a means of estimating thickness—a technique that can be used at other lava dome eruptions worldwide, especially where ground-based monitoring data and observations are not possible.

Interferogram composed of TerraSAR-X staring spotlight SAR images acquired on August 17 and 28, 2014.  Colored fringes indicate ground deformation, with one set of fringes equivalent to 1.5 cm of ground motion along the radar line of sight.  The large number of fringes on the 2004–2008 lava dome indicate rapid subsidence there, while fewer fringes on the 1980–1986 lava dome attest to lower

Interferogram composed of TerraSAR-X staring spotlight SAR images acquired on August 17 and 28, 2014.  Colored fringes indicate ground deformation, with one set of fringes equivalent to 1.5 cm of ground motion along the radar line of sight.  The large number of fringes on the 2004–2008 lava dome indicate rapid subsidence there, while fewer fringes on the 1980–1986 lava dome attest to lower 

Sensor: IFSAR / SAR / Radar

Platform: Satellite

Author: Mike Poland
Email: mpoland@usgs.gov
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Improving Hazard Mitigation at One of Indonesia’s Most Dangerous Volcanoes

Kelud volcano, located in East Java, has produced some of Indonesia’s most deadly eruptions.  The expulsion of water from the summit crater lake during the volcano’s typically short but explosive eruptions has created lahars­–volcanic mudflows–that have caused widespread fatalities and destruction.  Following a devastating eruption in 1919 that claimed more than 5,000 lives, an extensive engineering project began with an aim to drain the water from the crater lake. Successive eruptions impeded the success of the initial engineering project; however, following the 1966 eruption that caused more than 200 fatalities, a new deeper tunnel was constructed, and the lake's volume was substantially reduced.  Kelud’s last eruption in 2014 was a plinian eruption, in which gas and ash is violently ejected in a narrow stream to a height of several miles, with a large Volcanic Explosivity Index (VEI) of 4 (on a scale of 1 to 4). Inspite of its strength, only 2 people were killed when the weight of the ash deposits collapsed their homes.

The USGS and the U.S. Agency for International Development's Office of U.S. Foreign Disaster Assistance (USAID-OFDA)  Volcano Disaster Assistance Program (VDAP) works to support the Center for Volcanology and Geologic Hazard Mitigation (CVGHM) of Indonesia to mitigate volcanic hazards throughout the country.  In March 2016, VDAP assisted CVGHM in conducting a small unmanned aerial system (UAS) photogrammetry survey of the crater of Kelud and the main outlet channel to create a high-resolution digital elevation model (DEM).  The 2016 DEM is being used to estimate the volume of the crater lake, to measure topographic changes to the crater following the 2014 eruption, and to supplement lidar collected in 2014 to improve lahar inundation modeling downstream from the volcano.  This is the second CVGHM-VDAP UAS photogrammetry project in Indonesia, and the technology has shown great promise as a new tool for volcano monitoring, hazard mitigation, and research.

Shaded relief image derived from a very high-resolution (5-cm) digital elevation model (DEM) of a section of the eastern crater of Kelud volcano located in East Java, Indonesia.  The DEM was created using overlapping imagery captured from a small unmanned aerial system (UAS) during a photogrammetry survey in March 2016.  The field survey included the use of kinematic Global Positioning System (GPS) and photo targets for ground control used in creating the DEM.

Shaded relief image derived from a very high-resolution (5-cm) digital elevation model (DEM) of a section of the eastern crater of Kelud volcano located in East Java, Indonesia.  The DEM was created using overlapping imagery captured from a small unmanned aerial system (UAS) during a photogrammetry survey in March 2016.  The field survey included the use of kinematic Global Positioning System (GPS) and photo targets for ground control used in creating the DEM.

Sensor: Camera, Lidar (terrestrial or bathymetric)

Platform: UAS

Author: Angie Diefenbach
Email: adiefenbach@usgs.gov
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Magma Accumulation beneath Mauna Loa

For decades, the USGS has conducted geodetic monitoring of Mauna Loa, the largest volcano in the world, measuring well over 14,000 m from its base beneath the ocean to its summit above sea level.  The volcano makes up more than 50% of the island of Hawaiʻi and has been the source of numerous destructive lava flows over the past 200 years. The most recent eruption was in 1984, making the current 31-year period the longest without eruption since the early 1800s.  Mauna Loa has, however, experienced several periods of unrest since 1984.   Deformation measurements aid in detecting the accumulation and movement of magma beneath the volcano that might predict an eruption. Based on both deformation and seismic activity, the USGS Hawaiian Volcano Observatory raised the alert status of Mauna Loa to “Advisory” in September 2015, indicating that the volcano was no longer at a background level of activity.

Interferometric Synthetic Aperture Radar (IFSAR) provides a satellite-based means of mapping surface deformation with excellent spatial resolution.  Data acquired by the COnstellation of small Satellites for the Mediterranean basin Observation (COSMO)–SkyMed system demonstrate a change in the pattern of deformation at Mauna Loa in mid-2015.  The deformation pattern that was present starting in mid-2014 resembled that seen during previous periods of unrest and indicated magma accumulation in an elongated reservoir beneath the volcano’s summit caldera and upper Southwest Rift Zone (SWRZ).  Since late 2015, however, IFSAR data show that inflation is occurring only beneath the upper SWRZ—an observation confirmed by numerous ground-based Global Positioning System (GPS) sensors located on the volcano.  IFSAR, GPS, seismicity, and other indicators are closely tracking changes at the volcano and will provide warning of any future eruptive activity.

Interferograms from COSMO–SkyMed synthetic aperture radar data showing surface deformation spanning October 25, 2014 – June 22, 2015 (left) and June 22, 2015 – May 23, 2016 (right).  The butterfly pattern of fringes reflects magma accumulation in an elongated reservoir that runs along the length of the caldera at a depth of about 3–5 km beneath the surface.  The deformation pattern is shifted to the south in the more recent image with respect to the older one, reflecting a change in the pattern of magma accumulation over time.  These data were supplied as part of the global Group on Earth Observations Supersite initiative and would not otherwise have been available.

Interferograms from COSMO–SkyMed synthetic aperture radar data showing surface deformation spanning October 25, 2014 – June 22, 2015 (left) and June 22, 2015 – May 23, 2016 (right).  The butterfly pattern of fringes reflects magma accumulation in an elongated reservoir that runs along the length of the caldera at a depth of about 3–5 km beneath the surface.  The deformation pattern is shifted to the south in the more recent image with respect to the older one, reflecting a change in the pattern of magma accumulation over time.  These data were supplied as part of the global Group on Earth Observations Supersite initiative and would not otherwise have been available.

Sensor: IFSAR / SAR / Radar

Platform: Satellite

Author: Michael Poland
Email: mpoland@usgs.gov
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Monitoring the Evolving Crater of Mount St. Helens

The USGS Cascades Volcano Observatory utilizes oblique and vertical aerial photography to monitor topographic changes at Mount St. Helens volcano.  During the 2004–2008 eruption of Mount St. Helens, photogrammetry surveys were conducted on a weekly to monthly basis to create high-resolution digital elevation models (DEMs) used to measure the growth of the erupting lava dome.  Following the eruption, photogrammetry surveys have been conducted annually to track changes in the crater of the volcano, including the advancement of the crater glacier, settling of the 2004–2008 lava dome, and erosion of the crater walls. The next photogrammetry survey will take place in September 2016.

Perspective view, looking to the south into the crater of Mount St. Helens.  The distance between the east and west crater rims is approximately 2 km (~6,500 ft).  The shaded relief image created from a high-resolution (1-m) digital elevation model (DEM) shows the detailed morphology of the crater walls, lava domes, and glacier of Mount St. Helens.  The DEM was created by photogrammetry methods utilizing oblique aerial photographs acquired via helicopter in September 2015.

Perspective view, looking to the south into the crater of Mount St. Helens.  The distance between the east and west crater rims is approximately 2 km (~6,500 ft).  The shaded relief image created from a high-resolution (1-m) digital elevation model (DEM) shows the detailed morphology of the crater walls, lava domes, and glacier of Mount St. Helens.  The DEM was created by photogrammetry methods utilizing oblique aerial photographs acquired via helicopter in September 2015.

Sensor: Camera

Platform: Airplane, Helicopter

Author: Angie Diefenbach
Email: adiefenbach@usgs.gov
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Invasives

Climate Landscape Response (CLaRe) Phenometrics Detect Invasive Buffelgrass

The USGS has developed a new and innovative suite of landscape metrics (i.e. “Climate-Landscape Response” or CLaRe metrics) that are proven effective in mapping when and where invasive buffelgrass is green in Saguaro National Park (SNP) near Tucson, Arizona. Buffelgrass fills the interstices between widely-spaced desert plants with a continuous mat of fine fuels, carrying fire throughout the non-fire adapted Sonoran Desert landscape, with the potential to transform the iconic, species-rich, ecosystem into a monotypic grassland. CLaRe phenometrics, derived from gridded climate data and 250-m MODIS data, capture the strength of the landscape greenness response to climate and expose buffelgrass due to its rapid and strong response to recent precipitation. Buffelgrass remains dormant much of the year, but has short windows when it is photosynthetically active and vulnerable to herbicide. By mapping when and where buffelgrass is green, land managers can optimize their treatment activities, saving money. In addition, current results suggest that it is possible to detect nascent populations of buffelgrass comprising less than 5% of the landscape by monitoring the trends of these CLaRe phenometrics.

The ability to monitor and interpret trends in land surface phenology informs science-based land management. The CLaRe metrics capture the landscape response to climate and will complement the current temperate-zone phenometrics; no doubt they will prove broadly useful for many applications, including mapping invasive species (many invasives are observed to respond more rapidly to climate – especially precipitation -  than native vegetation, including buffelgrass, Lehman’s lovegrass and cheatgrass), monitoring ecosystems (capturing trends between temperature-driven and precipitation driven ecosystems), habitat modeling, and vegetation classification.

http://www.mdpi.com/2072-4292/8/7/524

Modeled buffelgrass presence-absence based on the top 20 % of CLaRe ppt123 metrics. CLaRe ppt123 is the correlation between MODIS greenness and the cumulative precipitation for the prior three  8-day periods. For each year shown, all CLaRe ppt123 values were extracted for each mapped vegetation type (based on the SWreGAP classification) and the top 5th of the highest correlations were mapped as buffelgrass presence (left panels). Higher elevation vegetation types that are unsuited for buffelgrass (e.g., Madrean pine-oak forest and woodland) were masked. The composite model (right image) maps buffelgrass presence if 2 of 3 sub-models mapped buffelgrass presence. Validation results show the composite model has an overall accuracy of 83 % and correctly maps 46 % of known buffelgrass patches.

Modeled buffelgrass presence-absence based on the top 20 % of CLaRe ppt123 metrics. CLaRe ppt123 is the correlation between MODIS greenness and the cumulative precipitation for the prior three  8-day periods. For each year shown, all CLaRe ppt123 values were extracted for each mapped vegetation type (based on the SWreGAP classification) and the top 5th of the highest correlations were mapped as buffelgrass presence (left panels). Higher elevation vegetation types that are unsuited for buffelgrass (e.g., Madrean pine-oak forest and woodland) were masked. The composite model (right image) maps buffelgrass presence if 2 of 3 sub-models mapped buffelgrass presence. Validation results show the composite model has an overall accuracy of 83 % and correctly maps 46 % of known buffelgrass patches.

Sensor: Multispectral (approx. 4-12 bands)

Platform: Satellite

Author: Cynthia SA Wallace
Email: cwallace@usgs.gov
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Detection of Invasive Plant Populations

The USGS Fort Collins Science Center in collaboration with researchers at Colorado State University is using Landsat imagery from different seasons to locate invasive vegetation species on public lands that are of concern to resource managers.  Land managers need to know where invasive species are established on the landscape to be able to undertake measures to kill or remove them, but the vast expanses of potentially infested territory preclude repeated, comprehensive field surveys. The research team developed multitemporal and multispectral distribution models for invasive species using Landsat 8 imagery corresponding to both species’ phenology and time of field data collection.  Strategically using imagery from times of the year when the phenology of the invasive species differed from that of the native community types allowed correlative species distribution models to accurately locate invasive populations on the landscape.  For example in southwestern Wyoming, cheatgrass greens up earlier in the season and goes to seed and turns brown before the native vegetation.  By leveraging this asynchronicity,  the scientists were able to detect patches of cheatgrass with >40% cover within a burned area of concern.  A tamarisk distribution in southeastern Colorado and at Havasu National Wildlife Refuge was successfully mapped using the same methods. 

https://www.fort.usgs.gov/science-tasks/2190

Preliminary models to detect tamarisk in southeastern Colorado using four different model algorithims commonly used in species distribution modeling (boosted regression tree [BRT]; random forest; multivariate adaptive regression splines [MARS]; generalized linear model [GLM]).

Preliminary models to detect tamarisk in southeastern Colorado using four different model algorithims commonly used in species distribution modeling (boosted regression tree [BRT]; random forest; multivariate adaptive regression splines [MARS]; generalized linear model [GLM]).

 

Sensor: Multispectral (approx. 4-12 bands)

Platform: Satellite

Author: Catherine Jarnevich
Email: jarnevichc@usgs.gov
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Dynamic Monitoring of Ecosystem Performance (Cheatgrass)

Cheatgrass is an invasive annual grass that alters fire regimes when it spreads into western U.S. sagebrush ecosystems. The increased frequency and intensity of wildfires and the higher probability of stand-replacing events not only threatens lives and property, but also degrades critical sagebrush ecosystems for wildlife habitat such as sage-grouse.  To characterize the dynamics and spread of this invasive grass across the landscape, USGS scientists have developed a machine learning, phenology–based algorithm using Moderate Resolution Imaging Spectroradiometer (MODIS) 250-m Normalized Difference Vegetation Index (NDVI) data to map the percent cover of cheatgrass in the northern Great Basin for 2000–2015. A spatially explicit time series of cheatgrass cover was used to track the historical incidence of cheatgrass die-offs as well as to identify areas prone to cheatgrass expansion. Maps of areas vulnerable to future cheatgrass invasion have been produced as well as near-real-time maps of existing cheatgrass (as of late June of the current year)  to facilitate habitat preservation and identify wildfire potential.  The team at EROS has also supplemented National Land Cover Database (NLCD) USGS/BLM rangeland mapping components with site potential maps and 30-m NDVI maps downscaled from MODIS data for critical phenological periods when Landsat data are unavailable.  Plans are to expand cheatgrass mapping into Wyoming and the central Great Basin, leveraging NLCD USGS/BLM high-resolution field sample block map products for model calibration and validation.

http://lca.usgs.gov/lca/epa_cheatgrass/index.php

Near-real-time cheatgrass cover prediction in the northern Great Basin.

Near-real-time cheatgrass cover prediction in the northern Great Basin.

Sensor: Multispectral (approx. 4-12 bands)

Platform: Satellite

Author: Bruce Wylie
Email: wylie@usgs.gov
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Remote Sensing Missions & Data

Declass-3 Availability

The Cold War era Keyhole (KH) satellite surveillance system, KH-9 Hexagon, operated from 1971 to 1984, recording imagery at a resolution of 2-4 feet along a swath 425 miles wide.  As with the precedessor CORONA system, images were recorded on rolls of photographic film, which were subsequently ejected from the orbiting satellite in a capsule.  Military aircraft recovered each capsule as it re-entered the Earth’s atmosphere by snagging its attached parachute with grappling hooks. Most of the image collection was declassified in 2011.  The first 1,700 Declass-3 redacted images of the KH-9 Hexagon mission were digitized and released through the online USGS EarthExplorer image portal on September 15, 2015.  As of July 2016, there are now more than 15,000 scenes available to the public. The collection being worked is a subset that was previously held by the USGS Advance Systems Center (ASC) in Reston, Virginia.  All of the Declass-3 frames are being offered as on-demand film scans at $30 per image (7-micron scans for black and whites and 14-micron for color infrared images).  

EarthExplorer screen capture of the Declass-3 collection for the period ending June 30, 2016.

EarthExplorer screen capture of the Declass-3 collection for the period ending June 30, 2016.

http://www.space.com/12996-secret-spy-satellites-declassified-nro.html

http://forum.nasaspaceflight.com/index.php?topic=17198.0

Sensor: Multispectral (approx. 4-12 bands)

Platform: Satellite

Author: Ryan Longhenry
Email: rlonghenry@usgs.gov
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Earth as Art 4: A Fusion of Science and Art

At first glance, science and art might seem like an unlikely pairing. Yet throughout history, the intersection of these two fields has often resulted in science-based works of sublime beauty. Consider Leonardo da Vinci’s sketches and models of his ingenious flying machines. Naturalist John J. Audubon’s detailed paintings of North American birds. Maps meticulously penned by ancient—and modern—cartographers.  And stunning images of the Earth’s surface taken by orbiting satellites. Thirty-seven such images form the new Earth as Art 4 (EAA4) collection, the USGS’s most recent installment of its Earth as Art exhibits.

Earth-observing Landsat satellites capture hundreds of images of the planet’s surface every day. Their primary purpose is scientific:  to document the condition of the Earth’s land areas, day after day and year after year, to help reveal how those areas are changing over time. The vast Landsat archive, maintained at the USGS Earth Resources Observation and Science (EROS) Center, is an unparalleled digital record of how continents, islands, and coastlines have altered as a result of natural and human impacts since 1972. From their vantage point in space, Landsat satellites view the Earth and its geographic features— deserts, mountains, river valleys, glaciers—from a perspective few humans ever experience.  The Landsat sensors detect particular wavelengths, or bands, of both visible and invisible (infrared) light.

When different bands are combined in Landsat images,  striking patterns, colors, and shapes emerge from nature, transforming an image of a section of the Earth’s surface into what more closely resembles a gorgeous work of abstract art. Landsat 8, the most recent Landsat satellite, which was launched by NASA in 2013, acquired all the images in the EAA4 collection. The entire collection can be accessed and downloaded at the Earth as Art 4 website.

http://eros.usgs.gov/imagegallery

The cloud patterns in this image cast eerie shadows on the landscape of southern Egypt. The clouds appear red and the desert below hazy blue in this infrared rendition.

The cloud patterns in this image cast eerie shadows on the landscape of southern Egypt. The clouds appear red and the desert below hazy blue in this infrared rendition.

Sensor: Multispectral (approx. 4-12 bands)

Platform: Satellite

Author: Janice Nelson
Email: jsnelson@usgs.gov
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Free Landsat Data Prove Their Worth for Observing Earth

At four decades of uninterrupted data acquisition, Landsat images represent the longest continuous record of Earth’s land surface as seen from space.  Scientists and resource managers have long leveraged this unparalleled, ever-lengthening time series to monitor a diverse range of Earth system processes and phenomena. Since late 2008, when the Department of Interior opened the Landsat archive to all users free of charge, nearly 40 million Landsat scenes have been downloaded through the USGS portal—and the rate of downloads is increasing.

The ability to access the full Landsat archive at no cost has also fueled the creation of purpose-driven data applications—known on mobile devices as “data apps”—that provide environmental and societal benefits.  Researchers around the world in government, in the private sector, and at universities and institutions have generated data applications that can serve commercial endeavors in agriculture and forestry, enable land managers to work more efficiently, and help to define and address critical climate and environmental issues.

To give a few examples of Landsat’s many commercial applications, Landsat data have been used to track the use of irrigation water, to assist drought-stricken California grape growers, and to contribute to the success of a forestry start-up company. As an indication of widespread public interest in Landsat data, third party avenues to the data and innovative ways to use these data are available from Amazon, Esri, and Google.

In the United States, the Federal Government invests about $3.5 billion annually in civil Earth observations and data (including Landsat and other satellites such as weather and GPS) across multiple agencies, while optimizing related investments that are also made by State, local, and Tribal governments, academia, and industry. The information derived from Earth observations supplies the foundation for scientific advances in many fields and enables multiple Federal agencies and partners to carry out their missions. Federal investments in various aspects of Earth observations are conservatively estimated to add $30 billion to the U.S. economy each year by providing Americans with critical knowledge about natural resources, climate and weather, disaster events, land use change, ecosystem health, ocean trends, and many other  Earth-related phenomena.

https://landsat.usgs.gov/

free data-graph

Sensor: Multispectral (approx. 4-12 bands), Thermal

Platform: Satellite

Author: Thomas Holm
Email: holm@usgs.gov
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Improving High-Resolution Gridded Climate Data

TopoWx ("Topography Weather," Oyler et al. 2015, Oyler et al. 2016) is a gridded dataset of daily minimum and maximum air temperature for the conterminous U.S. at 800-m resolution.  The values are interpolations based on elevation variables and MODIS land skin temperature, which are designed to capture locally relevant topoclimatic spatial patterns as well as regional climate variability and trends. The TopoWx product was produced by the Numerical Terradynamics Lab at the University of Montana with funding from the DOI North Central Climate Science Center (NC CSC). TopoWx is publicly available and being used by stakeholders. The NC CSC is actively utilizing these data in their ongoing analysis of understanding the impacts of a changing climate on species and habitats of concern to DOI.

http://www.ntsg.umt.edu/project/TopoWx

TopoWx maximum temperature departure from average for the 2014 calendar year.

TopoWx maximum temperature departure from average for the 2014 calendar year.

Sensor: Multispectral (approx. 4-12 bands), Thermal

Platform: Satellite

Author: Jeff Morisette
Email: morisettej@usgs.gov
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Landsat Space Operations—Extending Satellite Missions

Operating a vehicle that is orbiting the Earth 438 miles overhead at 17,000 miles per hour is not your average day job.  Managing the Landsat satellites that are daily imaging the Earth’s surface  is part of the USGS program’s responsibilities.  Each mission is designed to endure the extremes of the space environment through robust design including some system redundancies.  Landsat 5’s distinguished 29-year mission demonstrated not only the benefits of redundant design features but also the value of a skilled and creative flight operations team.  Landsat 7 and Landsat 8 are the current missions to continue this challenge of maximizing mission life.

While Landsat 5 was designed for a 3-year mission life, both Landsat 7 and Landsat 8 were designed for a minimum 5-year mission life.  Landsat 7 has collected over 2 million scenes after 17 years in orbit.  By chance Landsat 5 and by design Landsat 8 were each launched with additional fuel that is required for the spacecraft to maintain a precise orbit for Earth imaging.  Landsat 7 is now drawing down its fuel reserve late in the mission.  The flight operations team has investigated a number of options to optimize fuel use with the goal of maximizing Landsat 7’s operational life. Landsat 7 successfully performed its 19th inclination maneuver that positions the satellite to potentially continue its mission into 2020—more than 21 years following its launch. The Landsat 8 spacecraft was designed for a 5-year design life; however, due to time constraints, its thermal imaging instrument, known as the Thermal Infrared Sensor (TIRS), was designed for a 3-year life. 

The USGS Landsat team, along with NASA and the spacecraft vendors, continued to meet the challenges of space operations in 2016 and will continue to build on that record in the future.  Additional time added to a mission’s operation provides more imagery for operational and science applications, a benefit to users and the American taxpayer.

https://landsat.usgs.gov/

Sensor: Multispectral (approx. 4-12 bands), Thermal

Platform: Satellite

Author: James Lacasse
Email: jmlacasse@usgs.gov
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Landsat Vital in LANDFIRE 2014 Update

LANDFIRE, the Landscape Fire and Resource Management Planning Tools Program, is a vegetation, fire, and fuel characteristic mapping program that provides information for strategic fire and resource management planning and analysis. It is managed by the U.S. Department of Agriculture Forest Service and the U.S. Department of the Interior, in partnership with The Nature Conservancy. LANDFIRE National, LANDFIRE’s first national extent spatial dataset describing existing and potential vegetation type and structure, surface and canopy fuels, and fire regimes, was completed in 2009. Since then, the existing vegetation, fuel, and fire regime layers of the dataset have been updated three times. The fourth and latest update, LF 2014, is in progress at the USGS Earth Resources Observation and Science Center.

Landsat imagery plays a vital role in developing these LANDFIRE datasets.  Multitemporal Landsat imagery is used to quantify annual landscape disturbances nationwide.  The disturbance data are then combined with vegetation transition models to produce updated existing vegetation data layers, which are then used to update fuels and fire regimes data. Improvements in image compositing and tiling algorithms, plus faster, lower cost computing hardware, have enabled many more Landsat images to be utilized in LANDFIRE updates.  Thus far, more than 100,000 Landsat scenes have been processed for the LF 2014 update, including both Landsat 7 Enhanced Thematic Mapper Plus and Landsat 8 Operational Land Imager imagery.  Because Landsat scenes are reliable and highly calibrated, LANDFIRE products are consistent, comprehensive, and standardized, providing quality input to multiple fire, fuel, and natural resource applications.

http://www.landfire.gov

Landsat imagery is vital to LANDFIRE data production. The graph above shows the number of Landsat scenes used to develop the LANDFIRE products listed.

Landsat imagery is vital to LANDFIRE data production. The graph above shows the number of Landsat scenes used to develop the LANDFIRE products listed.

Sensor: Multispectral (approx. 4-12 bands), Thermal

Platform: Satellite

Author: Kurtis Nelson
Email: knelson@usgs.gov
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National Land Cover Database - Shrub and Grassland Mapping

The USGS and the Bureau of Land Management (BLM) are working to develop a suite of shrub and grassland products to study changes in wildlife habitat and landscapes in the western United States. The nine products in the suite—shrub, sage, herbaceous, bare ground, etc.—are based on extensive fieldwork and high-resolution satellite imagery, and then upscaled to show percent cover of each component for 30-m Landsat pixels.

This suite of products will serve as a basis for the USGS and BLM to study habitats of western species, such as sage-grouse, and to study changes in the western landscape. The products will also be incorporated into the production of the National Land Cover Database (NLCD) 2016, enhancing the accuracy of the Shrub, Grassland, and Barren classes.

For more information on the NLCD and to download NLCD data, including shrub and grassland products, visit http://www.mrlc.gov/.

http://www.mrlc.gov/

Shrub cover is one of nine components in a suite of products under development by the USGS and BLM. Component proportions are field measured and then extrapolated to satellite imagery pixels. Development of each component product includes independent validation, cross validation, and a spatial absolute error model prediction.

Shrub cover is one of nine components in a suite of products under development by the USGS and BLM. Component proportions are field measured and then extrapolated to satellite imagery pixels. Development of each component product includes independent validation, cross validation, and a spatial absolute error model prediction.

 

Sensor: Multispectral (approx. 4-12 bands)

Platform: Satellite

Author: Collin Homer
Email: homer@usgs.gov
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National Land Cover Database – 2016 Strategy

The USGS, working in partnership with the Federal interagency Multi-Resolution Land Characteristics (MRLC) Consortium, is developing the National Land Cover Database (NLCD) 2016. NLCD serves as the definitive moderate resolution land cover database for the U.S., developed from Landsat data at a 30-m pixel resolution. NLCD 2016 will feature new products of labeled land cover and fractional cover products of urban imperviousness, tree canopy, shrub canopy, grass canopy, and bare ground. In addition, previous NLCD labeled land cover releases from 2001, 2006, and 2011 will be re-harmonized with NLCD 2016 to ensure all products are spatially coherent and consistent among all four epochs for accurate capture of land cover change across time. NLCD 2016 will represent the most accurate and detailed NLCD products delivered to date.

For more information on NLCD and to download NLCD data, including shrub and grassland products, visit http://www.mrlc.gov/.

The National Land Cover Database (NLCD) 2016 will be based on Landsat imagery from seven time periods in a complex modeling process that will result in accurate, spatially coherent, and consistent land cover and land cover change products.

The National Land Cover Database (NLCD) 2016 will be based on Landsat imagery from seven time periods in a complex modeling process that will result in accurate, spatially coherent, and consistent land cover and land cover change products.

Sensor: Multispectral (approx. 4-12 bands)

Platform: Satellite

Author: Collin Homer
Email: homer@usgs.gov
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Requirements, Capabilities and Analysis for Earth Observations—An Overview

The USGS Land Remote Sensing (LRS) Program is partnering with Federal agencies to document user requirements for Earth Observation (EO) data and the benefits that these data provide to Federal programs. The Requirements, Capabilities, and Analysis for Earth Observation (RCA-EO) project was established to help the USGS and other federal agencies take full advantage of United States and international EO capabilities, and develop requirements-driven, prioritized investment decisions for new EO systems, products, and services.

The USGS RCA-EO project, along with the National Oceanic and Atmospheric Administration (NOAA), has jointly developed a unified database-driven information infrastructure and analysis suite called the Earth Observation Requirements Evaluation System (EORES) to support Requirements, Capabilities and Analysis.

The RCA-EO project elicits stake holder needs to document: (1) Requirements: What needs to be observed, such as land surface temperature or vegetation condition, including where and when it is needed and how accurate it must be; (2) Capabilities: What EO capabilities exist or are needed to satisfy the requirements, including what is observed, where it is observed, how often, and how accurately. RCA-EO utilizes these requirements and capabilities stored and managed in the EORES along with additional tools to perform (3) Analysis:  What activities exist or can be designed to help guide management decisions by those who manage or develop EO systems, products, and services, and to help users of these same products and services.

During the past year, RCA-EO made considerable progress on EORES and within all three focus areas. (1) Requirements: Completing the value-tree information (VTI) elicitation for the USGS (including 27 programs, over 500 subject matter experts, and 345 key products and services), and making excellent progress eliciting user Requirements. (2) Capabilities: Completing the initial population of the capabilities database; (3) Analysis: Establishing an operations concept and workflow for analysis.  Additionally, RCA-EO made excellent progress on development of the EORES application, which will have met initial baseline operational capability this year.  RCA-EO data and infrastructure has provided substantial support to the USGS as well as the Administration’s National Plan for Civil Earth Observations and the associated current Earth Observation Assessment 2016.  RCA-EO information analyses will continue to help the USGS inform decisions for future land imaging missions and EO science pursuits.

From a national perspective, RCA-EO analyses will provide a better understanding of EO systems and their benefits to society, and can inform the development of more responsive and cost-effective EO systems. Preliminary results are shown below, summarizing the impact of remote sensing on USGS programs and the usage of Landsat within the USGS.  Understanding user community needs and capturing their enduring user requirements is a critical step toward developing a way forward in the world of Earth observation systems.

RCA-EO project videos and information can be viewed at http://remotesensing.usgs.gov/rca-eo/.

Histograms show the contribution of remotely sensed data toward the research conducted in the USGS programs listed. Landsat data are shown as a subset of total data use.

The contribution of remotely sensed data for research conducted in the USGS programs. Landsat data are shown as a subset of total data use.

Sensor: Multispectral (approx. 4-12 bands)

Platform: Satellite

Author: Gregory Stensaas; Greg Snyder
Email: stensaas@usgs.gov; gsnyder@usgs.gov
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Requirements, Capabilities and Analysis for Earth Observations—Landsat Impacts

The USGS initiated the Requirements, Capabilities and Analysis for Earth Observations (RCA-EO) activity in the Land Remote Sensing (LRS) program to provide a structured approach to collect, store, maintain, and analyze user requirements and Earth observing system capabilities information. RCA-EO enables the collection of information on current key Earth observation products, services, and projects, and to evaluate them at different organizational levels within an agency in terms of how reliant they are on Earth observation data from all sources, including spaceborne, airborne, and ground-based platforms. Within the USGS, RCA-EO has engaged over 500 subject matter experts in this assessment and evaluated the impacts of more than 1,000 different Earth observing data sources on 345 key USGS products and services. Among Earth observing systems that support all seven USGS mission areas, Landsat is ranked fourth among all systems and second among remote sensing systems. The majority of USGS users are satisfied with current Landsat data but desire higher spatial and temporal resolution, easier data processing, and improved data access. Using the Landsat example, RCA-EO has demonstrated that it offers a unique opportunity to understand the impact of Earth observations on USGS mission areas, programs, and key products and services, from which analysts can infer gaps in user needs and guide decisions on system improvements or new sensor design to improve user satisfaction in the USGS and beyond.  RCA-EO activity is seen as an enduring need given that rapidly increasing observation capability and capacity will lead to changing user requirements over shorter periods.

http://remotesensing.usgs.gov/rca-eo/analysis

Impact of Landsat on USGS mission areas and programs

Impact of Landsat on USGS mission areas and programs

Sensor: Multispectral (approx. 4-12 bands)

Platform: Satellite

Author: Zhuoting Wu
Email: zwu@usgs.gov
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Sustainable Land Imaging—USGS Initiates Landsat 9 Development

An extensive interagency study documenting the societal benefits of hundreds of Earth observing systems revealed that Landsat is the second most impactful space system, topped only by Global Positioning Satellite (GPS) systems. This finding led the Administration to commit to a Sustainable Land Imaging (SLI) program, extending the current NASA-USGS Landsat partnership for another two decades. The SLI program includes the immediate initiation of a Landsat 9 mission, which is modeled after Landsat 8, and a sustained multi-year technology development and system innovation effort in order to evaluate new measurement technologies for a follow-on mission to Landsat 9.  Under the SLI program, the USGS and NASA will continue to work together to ensure sustained access for another 20 years to land remote sensing observations for U.S. and global research and operational users. 

Landsat 9 will be an improved version of Landsat 8, with more redundancy and a broader suite of operational products that capitalize on recent developments in processing and utilizing analysis-ready data to deliver more customer-friendly information products to monitor, assess, and predict land surface change.  These products are designed to serve a larger set of customers across the USGS, DOI, and the civil community than the current Landsat 7 and 8 products.  It is planned that Landsat 9 be launched in late 2020 to ensure a smooth handoff with Landsat 7 and continue providing the weekly coverage required by tens of thousands of current Landsat users. 

The responsibilities for Landsat 9 project implementation are largely divided between mission segment areas: NASA is responsible for the development of the space segment and launch segment, and the USGS is responsible for the development of the ground segment. The USGS is also responsible for Landsat 9 mission operations after completion of the on-orbit checkout period, including image data collection, management, and distribution. The Landsat 9 project scope includes overall project management and system engineering for the ground segment development, including coordination with NASA for overall mission development and science coordination. The ground segment activities consist largely of the evolution of the current Landsat ground system capabilities necessary to support Landsat 9.

For more information, contact USGS EROS, Jim Nelson, jnelson@usgs.gov.

Sensor: Multispectral (approx. 4-12 bands), Thermal

Platform: Satellite

Author: Jim Nelson
Email: jnelson@usgs.gov
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The Land Processes Distributed Active Archive Center: An Enduring Partnership

The USGS provides land data products to the public and remote sensing community that support a variety of activities, including natural resource management and inter-disciplinary Earth system science. To accomplish this service, on August 28, 1990, the USGS and NASA entered into a partnership that established the Land Processes Distributed Active Archive Center, or LP DAAC, at the USGS Earth Resources Observation and Science (EROS) Center.  A 65,000-square-foot addition was constructed to accommodate “the DAAC” as it came to be called.  This specialized NASA archive added a new dimension to EROS in that the DAAC would be processing, archiving, and distributing remotely sensed land imagery acquired primarily by the MODIS and ASTER sensors on board NASA’s Earth Observing System (EOS) Terra and Aqua satellites.  Twenty-five years later, officials from the DOI, USGS, and NASA headquarters joined EROS staff in celebrating the DAAC’s 25th anniversary on August 27–28, 2015.

From the start, the LP DAAC has been a source of great pride and innovation.  Since 1990, this NASA-USGS partnership has brought numerous technological advances to the USGS.  For example, the LP DAAC can house multiple large datasets in one archive, manage an archive entirely on spinning disk, and implement new database technologies that allow for faster ingesting of data.  Over the years, every advance has been focused on improving the ability to mine the vast NASA archives and develop new services that scientists can use to learn more about our changing Earth.   

https://lpdaac.usgs.gov/

EROS Press Conference, August 28, 1990.

EROS Press Conference, August 28, 1990.

Sensor: Multispectral (approx. 4-12 bands), Thermal

Platform: Satellite

Author: Chris Doescher
Email: cdoesch@usgs.gov
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Training in Advanced Remote Sensing Technologies for Tribal Land Management

A USGS research team led by Dennis Dye of the Western Geographic Science Center gave a 3-day technical training course on land remote sensing to staff of the San Carlos Apache Tribe’s Forest Resources Program in San Carlos, Arizona.  The training supports the Tribe’s objectives for using ground-based observing systems (science-quality “phenocams” and other sensors) and airborne laser scanning (lidar) to support improved monitoring, analysis, and management of their natural resources. The course was sponsored by the USGS Technical Training in Support of Native American Relations (TESNAR) Program.

Participants in the USGS-sponsored training course on applications of ground-based remote sensing and airborne lidar for resource management on the San Carlos Apache Reservation in Arizona.

Participants in the USGS-sponsored training course on applications of ground-based remote sensing and airborne lidar for resource management on the San Carlos Apache Reservation in Arizona.

Sensor: Camera, HDR-LVIS, Lidar (terrestrial or bathymetric)

Platform: Airplane, Ground based / sensor web / web cam

Author: Dennis G. Dye
Email: ddye@usgs.gov
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Users, Uses, and Value of Landsat Imagery

Landsat data are an invaluable resource of moderate-resolution satellite imagery available to the public for free through the USGS.  These data, available from 1972 through the present, have been used in countless studies, including monitoring land use change, deforestation, glacier recession, sea ice extent, invasive species, and population growth.   To help assess the uses and value of Landsat imagery, social scientists at the USGS Social and Economic Analysis (SEA) Branch of the Fort Collins Science Center in Colorado are leading a long-term study, which includes surveys and case studies of Landsat imagery users. A series of surveys provides longitudinal data on how the users and uses of the imagery are changing over time in response to changes in the provision of the imagery, which include the shift to online access (including the development of the full-resolution browse), the no-cost downloading policy, and the launch and decommission of different Landsat satellites.  The results allow analysts to explore the value of the imagery. Multiple case studies that focus on the use and benefits of Landsat imagery in water, agriculture, forestry, and private sector technological applications provide context and depth to complement the more quantitative survey data. In 2016, a report on the results of the most recent 2014 survey of Landsat users was published (https://pubs.usgs.gov/of/2016/1032/ofr20161032.pdf). Additional analysis of the 2014 survey data, as well as 2015 user data from the USGS Earth Resources Observation and Science (EROS) Center, was completed to help inform the collection of Landsat 10 requirements.

https://www.fort.usgs.gov/landsat-study

 “Earth as Art” Landsat image of the Great Salt Desert in Iran.

“Earth as Art” Landsat image of the Great Salt Desert in Iran.

Sensor: Multispectral (approx. 4-12 bands), Thermal

Platform: Satellite

Author: Holly Miller
Email: millerh@usgs.gov
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USGS Partners with European Space Agency to Deliver Copernicus Earth Data

The USGS and the European Space Agency (ESA) have established an innovative partnership to enable USGS storage and redistribution of Earth observation data acquired by Copernicus program satellites. The ESA-USGS collaboration will serve scientific and commercial customers who are interested in the current conditions of forests, crops, and water bodies across large regions and in the longer term environmental condition of the Earth. Data acquired by the European Union’s Sentinel-2A satellite launched in June 2015 are highly complementary to data acquired by USGS/NASA Landsat satellites since 1972. The agreement is part of a broader understanding between the European Union and three U.S. Federal science agencies—NASA, the National Oceanic and Atmospheric Administration (NOAA), and the USGS—that was signed in October 2015. All parties are committed to the principle of full, free, and open access to Earth observation satellite data produced by the European Union’s Sentinel program and by the respective U.S. agencies. An ESA article (http://www.esa.int/Our_Activities/Observing_the_Earth/Sentinel_data_wanted) further describes the cross-Atlantic collaboration.

Dr. Suzette Kimball, Director of the USGS, has stated that "Free and open access to Landsat and Sentinel-2 data together will create remarkable economic and scientific benefits for people around the globe.”  Sentinel data are available at no cost from the Copernicus Scientific Data Hub. Additionally, in order to expedite data delivery around the globe, users may also download both Sentinel-2 and Landsat data at no charge in a familiar digital environment from USGS access systems such as EarthExplorer. Presently, only selected Sentinel data are available from the USGS in an early testing phase. Timely access to all Sentinel data will follow as the procedures for data transfer, user access, and data delivery continue to be optimized at the USGS Earth Resources Observation and Science (EROS) Center.

The MultiSpectral Instrument (MSI) sensor on board Sentinel-2A acquires 13 spectral bands that parallel and complement data acquired by the USGS Landsat 8 Operational Land Imager (OLI) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+). Unlike the Sentinel-2 satellites, Landsat satellites also include a capability to collect thermal infrared data, which is used in a variety of water and agricultural monitoring applications. NASA has published an online comparison of Sentinel-2A and Landsat bandwidths.

https://eros.usgs.gov/sentinel-2

This Sentinel-2A false color image shows agricultural structures in the Abruzzo region of central Italy. The area imaged above is 20-km across.

This Sentinel-2A false color image shows agricultural structures in the Abruzzo region of central Italy. The area imaged above is 20-km across.

Sensor: Multispectral (approx. 4-12 bands)

Platform: Satellite

Author: Douglas Binnie
Email: binnie@usgs.gov
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Using Imagery to Crowdsource The National Map and U.S. Topo Maps

The National Map Corps (TNMCorps) is a crowdsourced mapping project that relies on volunteers to assist the USGS National Geospatial Program by collecting and editing manmade structures data for The National Map. Through their participation, volunteers from around the Nation are enhancing the USGS’s ability to provide the Nation with accurate mapping information.

Over the past two decades, the USGS has promoted several volunteered geographic information (VGI) mapping projects, including TNMCorps. The results of several pilot projects from 2010 to 2012 led to a phased, nationwide expansion of the current crowdsourcing project. As of August 2013, volunteers have been collecting and updating 10 structure feature types (including schools, fire stations, cemeteries, and others) in all 50 states.

TNMCorps incorporates a variety of strategies to motivate and engage volunteers while simultaneously facilitating focused data collection resulting in high quality data.  These strategies include a tiered editing process, map challenges, virtual recognition badges, social media engagement, monthly newsletters, and regular news releases.  Volunteers from the general public include youth from various organizations such as the 4-H and scouting, retirees, students, and anyone with an interest in contributing to The National Map.

It is easy to get started.  After walking through a simple registration process, volunteers begin editing using a Web-based mapping platform. The primary base layer uses The National Map Web services and consists primarily of 1-m resolution digital orthophoto imagery provided by the USDA National Aerial Imagery Program (NAIP) and is supplemented by high-resolution orthoimagery over urban areas. Volunteers collect and improve the structures data by adding new features, removing obsolete points and correcting existing data. Fellow volunteers peer-review the edits, which are then incorporated into The National Map and ultimately into U.S. Topo maps. As of May 2016, over 1,500 users have made more than 210,000 contributions to TNMCorps.

http://nationalmap.gov/TheNationalMapCorps/index.html

USGS TMNCorps volunteer contributions from August 8, 2012, to June 2, 2016.

USGS TMNCorps volunteer contributions from August 8, 2012, to June 2, 2016.

Sensor: Camera

Platform: Airplane

Author: Elizabeth McCartney
Email: emccartney@usgs.gov
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Water

A 20-year High-Resolution Geostationary Operational Environmental Satellite (GOES) Solar Insolation—Evapotranspiration Dataset for Water Resource Management

The USGS collects evapotranspiration data needed by Federal, State, and local agencies for planning and operating water-resources projects and regulatory programs. Over 20 years of reference evapotranspiration (RET) and potential evapotranspiration (PET) were computed for all five water management districts in the State of Florida. These maps represent potential daily atmospheric water use at 2-km resolution from June 1, 1995, to December 31, 2015. Incoming solar radiation (insolation) is a primary driver of ET in Florida. Insolation maps from the Geostationary Operational Environmental Satellite (GOES) are used to compute PET and RET, and the insolation maps are well calibrated by using ground-based pyranometers. As expected, PET and RET generally increase from north to south due to enhanced solar radiation in south Florida.  Key hydrologic features that affect regional weather patterns, such as Lake Okeechobee and the Gulf of Mexico, also are reflected in the results.  Planned enhancements include (1) a historical extension to 1985, (2) use of spatially continuous forecast or reanalysis model fields to improve representations of temperature, humidity, and wind speed, and (3) incorporation of “blue-sky” albedos from the Moderate Resolution Imaging Spectroradiometer (MODIS) to improve estimates of net radiation.

http://fl.water.usgs.gov/et/

Statewide GOES PET/RET maps

 

Sensor: GOES satellite

Platform: Satellite

Author: W. Barclay Shoemaker
Email: bshoemak@usgs.gov
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Characterizing Watershed Resiliency to Ecological Drought Impacts

Understanding and predicting streamflow permanence in response to increasing aridity is the essential first step to mitigating ecological drought and subsequent management of systems that will be resilient in the face of climate change. The objective of this project is to substantially improve the ability of land managers to identify ecologically important headwater streams resilient to drought conditions, enabling them to focus their limited rehabilitation and conservation resources on watersheds necessary to support populations of threatened aquatic species.  The understanding and available measurements of water availability in the headwaters at a landscape extent in the Northwest United States is surprisingly incomplete. Analysis of the National Hydrography Dataset (NHD), a primary source for mapping and classifying streams and water availability, revealed that classifications were correct only about 50% of the time. One goal of the proposed project is to create the Headwaters Intermittency Prediction (HIP) tool. Land managers can use this tool to provide predictions of flow permanence for user-selected headwater streams. The project can also be expanded to predict flow permanence of any stream in the Northwest with near daily/weekly updates based on remote sensing (e.g., snow extent) data availability.  The ecological value of the HIP tool will be shown by incorporating HIP output into existing vulnerability assessments for native trout across the Northwest, providing novel insights into the potential consequences of spatial variation in water availability for these species. HIP will also be a timely management tool.

Sensor: Multispectral (approx. 4-12 bands)

Platform: Satellite

Author: Kyle Blasch
Email: kblasch@usgs.gov
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Coastal National Elevation Database: Sandy-CoNED and Wetland Extent Mapping

Quantitative high-resolution coastal elevation information is required to build integrated topobathymetric elevation models, inventory wetland and agricultural land resources, and identify inundation hazard zones caused by floods, hurricanes, and sea-level rise.  Many applications of geospatial data in coastal environments require detailed knowledge of near-shore topography and bathymetry, as physical processes in the coastal environments are controlled by the geomorphology of both “over-the-land” topography and “underwater” bathymetry.  Light detection and ranging (lidar) enables the rapid collection of accurate elevation data over large areas.  During the last decade, airborne laser altimetry has been widely applied to map coastal geomorphology, leading to improved knowledge of coastal geomorphic processes. 

The Coastal National Elevation Database (CoNED) applications project, supported by the USGS Coastal and Marine Geology Program (CMGP), is constructing high-resolution integrated topobathymetric elevation models from disparate lidar and acoustic bathymetric datasets aligned both vertically and horizontally to common reference systems.  Topobathymetric digital elevation models (TBDEMs) are merged renderings of both topography (land elevation) and bathymetry (water depth).  Topobathymetric models provide a required seamless elevation product for several science application studies such as shoreline delineation, coastal inundation mapping, sediment-transport, sea-level rise, storm surge models, tsunami impact assessment, and analysis of the impact of various climate change scenarios on coastal regions. 

One high visibility application of these data  is the USGS Hurricane Sandy synthesis project. Hurricane Sandy severely impacted the eastern United States coast, altering the topography, bathymetry, and ecosystems of this heavily populated region.  The USGS is developing high-resolution (1-m) three-dimensional (3D) topobathymetric models from Cape Cod to the Outer Banks in North Carolina that integrate dozens of high-resolution lidar and bathymetric surveys acquired by numerous sources.  Pre- and post-Hurricane Sandy remote sensing lidar data are being used to construct wetland extent geospatial products that will enable predictive sediment-transport flow modeling across wetlands in the Forsythe National Wildlife Refuge in New Jersey.

Extreme storm events like Hurricane Sandy and other natural hazards can impact the spatial distribution of land and water in coastal wetlands and change the capacity of the ecosystem to provide services such as water-quality enhancement, protection of populated areas from storm surge flooding, and habitat for fish, shellfish, and other wildlife. TBDEMs will help inform the nature of these changes.

http://topotools.cr.usgs.gov/coned/index.php

Coastal National Elevation Database—wetland extent mapping research.

Coastal National Elevation Database—wetland extent mapping research.

Sensor: Lidar (terrestrial or bathymetric)

Platform: Lidar (terrestrial or bathymetric)

Author: Jeffrey Danielson
Email: daniels@usgs.gov
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Estimates of Consumptive Water Use

Consumptive water use of irrigated and non-irrigated lands was estimated at 30-m resolution in the Klamath Basin, Oregon, using Landsat thermal imagery with the Mapping Evapotranspiration at High Resolution and Internalized Calibration (METRIC) procedure. Because ground surfaces with large evapotranspiration (ET) rates are cooler than ground surfaces that have less ET, irrigated fields appear on images as being cooler than non-irrigated fields. Both the rate and spatial distribution of ET can be efficiently and accurately quantified independent of the crop development stages or the specific crop type. By comparing ET of these two land uses, an estimate of the amount of consumptive water use for irrigated land can be made. Furthermore, the method can detect differences in consumptive use of water by non-irrigated crops that use shallow groundwater near streams, non-irrigated crops that are a distance above the groundwater system, and irrigated crops. The information can be used by water resource managers to manage water rights in the Klamath Basin.

http://dx.doi.org/10.5066/F72J68ZW

Sensor: Thermal

Platform: Satellite

Author: Jon Haynes
Email: jhaynes@usgs.gov
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Future Land-use Related Water Demand in California

Water shortages in California are a growing concern given persistent drought conditions, earlier spring snowmelt, projected future climate warming, and currently mandated water use restrictions. Increases in population and land use requirements in coming decades will place additional pressure on already limited available water supplies. USGS scientists used a state-and-transition simulation model to project future changes in developed (municipal and industrial) and agricultural land use to estimate associated water use demand from 2012–2062. Under current efficiency rates, total water use was projected to increase 1.8 billion m3 (+4.1%) driven primarily by urbanization and shifts to more water intensive crops. Only if currently mandated 25% reductions in municipal water use are continuously implemented would water demand in 2062 balance to water use levels in 2012. This is the first modeling effort of its kind to examine regional water demand related to land use incorporating historical trends of both developed and agricultural land uses.

http://geography.wr.usgs.gov/LUCC/mediterranean_california_land_change_a...

Projected land use and land cover (LULC) change for the historical period (1992–2012) and the projected period (2012–2062) in California’s Central Valley and Oak Woodlands regions under a business-as-usual scenario. The 2012 and 2062 LULC maps represent one out of 40 possible Monte Carlo iterations modeled for each time step.

Projected land use and land cover (LULC) change for the historical period (1992–2012) and the projected period (2012–2062) in California’s Central Valley and Oak Woodlands regions under a business-as-usual scenario. The 2012 and 2062 LULC maps represent one out of 40 possible Monte Carlo iterations modeled for each time step.

Sensor: Camera

Platform: Airplane

Author: Tamara Wilson
Email: tswilson@usgs.gov
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Hindcasting Turbidity in Lake Clark National Park

National Park Service (NPS) water clarity data were recently combined with Landsat remote sensing data to hindcast turbidity trends in Lake Clark for a 30-year time period (1985–2014). Lake Clark is a glacially influenced nursery lake for sockeye salmon, located in the headwaters of Bristol Bay, Alaska, the most productive wild salmon fishery in the world. Water clarity is a key water-quality property in salmon-bearing lakes. Decreases in water clarity due to increases in glacial runoff have been shown to reduce salmon production by lowering the abundance of prey such as zooplankton. Anecdotal accounts suggest that Lake Clark water clarity is decreasing over time, but no long-term measurements exist to substantiate these observations.

This study addressed that data gap by reconstructing long-term, lakewide water clarity for Lake Clark using the Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) surface reflectance products and in-situ water clarity data. No significant change was detected in the mean annual turbidity of Lake Clark for the time period examined. However, a significant positive trend in May turbidity was found between 2000 and 2014, which could represent an advance in the timing of initial sediment input to the lake via glacial meltwater runoff.

This study demonstrates the utility of hindcasting turbidity in a glacially influenced lake using the Landsat surface reflectance products. It may also provide a framework for reconstructing turbidity records in lakes that lack in-situ observations, and it can be a starting point for predicting future water clarity conditions based on projected climate scenarios.

http://www.mdpi.com/2072-4292/7/10/13692

Lake Clark as seen from Landsat 7 on September 6, 1999. This "true" color composite utilizes band 1 as blue, band 2 as green, and band 3 as red, and is adjusted to highlight contrasts in water clarity. Light blue water represents sediment-laden water. The darker the water, the less suspended sediment. The image exquisitely demonstrates the prominent sediment plume that was the subject of this study. The plume originates from the northeastern end of the lake (top right corner) and extends to the southwest.

Lake Clark as seen from Landsat 7 on September 6, 1999. This "true" color composite utilizes band 1 as blue, band 2 as green, and band 3 as red, and is adjusted to highlight contrasts in water clarity. Light blue water represents sediment-laden water. The darker the water, the less suspended sediment. The image exquisitely demonstrates the prominent sediment plume that was the subject of this study. The plume originates from the northeastern end of the lake (top right corner) and extends to the southwest.

Sensor: Multispectral (approx. 4-12 bands)

Platform: Satellite

Author: Carson Baughman
Email: cbaughman@usgs.gov
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Mapping the 2010 BP Oil Spill in the Gulf of Mexico Using AVIRIS Hyperspectral Imaging

Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data collected over the BP oil spill in the Gulf of Mexico (GOM) during May and July 2010 were used to create quantitative maps of oil spill thickness, oil-to-water ratio, areal coverage, and volume.  Due to the immense size of the spill, AVIRIS could only cover a portion of the spill on any given day.  Two days on which AVIRIS data were collected had favorable sea surface conditions (i.e., low sun glint from waves) allowing an accurate determination of oil volume in thick emulsions.  Approximately one-third of the core spill was imaged on May 17 with a much smaller portion imaged on July 9.  The AVIRIS data, which span ultraviolet to near-infrared wavelengths in 224 contiguous spectral channels, were analyzed for indications of water-in-oil emulsions by comparing them to reference spectra using the USGS Tetracorder spectral matching algorithm. Reference spectra included the weathered crude oil from the Macondo well and 76 spectra of synthetic emulsions with varied oil:water ratios.   Results showed the maximum depth of penetration is about 6 mm for emulsions up to 30 wt% water and decreased depth of penetration (2 to 4 mm) with greater wt% water contents.  Ship-based observations during the oil spill suggest emulsions can be as thick as 20 mm; hence AVIRIS would only be probing at most the top 6 mm of those plumes.

AVIRIS data cubes collected over the spill were analyzed by least-squares spectral fitting to the 76 selected emulsion spectra and the weathered crude oil spectrum.  Other reference spectra were also used in the spectral analysis to locate and mask non-water and non-emulsion pixels. These spectra included a Sargasso Weed spectrum measured in situ in the GOM to locate pixels dominated by vegetation as well as spectra of wood, plastic, and paint usually associated with the decks of ships and oil platforms.  Tetracorder maps for each of the 76 synthetic emulsion spectra and the weathered crude oil spectrum were produced.  The aerial extent was calculated using AVIRIS pixel sizes, which varied from 8 to 3 m on a side depending on aircraft altitude.  The volume of oil was then calculated using the areal fraction of emulsion that covered each pixel along with the spectrally determined oil:water ratio and emulsion thickness.  

Crude oil upwelling from the leaking Macondo well in July 2010.  Elongated brown emulsion plumes form as wind and currents carry oil from upwelling centers.

Crude oil upwelling from the leaking Macondo well in July 2010.  Elongated brown emulsion plumes form as wind and currents carry oil from upwelling centers. 

Sensor: Unspecified sensor

Platform: Unspecified platform

Author: Gregg Swayze
Email: gswayze@usgs.gov
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Mapping Water Use: Landsat and America’s Water Resources

Water, one of the Nation’s most important natural resources, has long been considered inexhaustible. Yet changes in land use, climate, and population demographics are placing unprecedented demands on America’s water supplies. As droughts rage and aquifers dwindle, people may wonder: Is there enough water to meet all of our needs?  Landsat satellites are helping to answer that question.

Using Landsat satellite data, scientists with the USGS have helped to refine a technique called evapotranspiration (ET) water-use mapping to measure how much water crops are using across landscapes and through time. These ET water-use maps are created using a computer model that integrates Landsat and weather data. Crucial to the process is Landsat’s thermal (infrared) band. Thanks to that thermal band with its 100-m resolution, water-use maps can be created at a scale detailed enough to show how much water crops are using at the level of individual fields anywhere in the country.

ET water-use maps can show how much water crops are using in a single day or during an entire growing season. Drawing on the vast Landsat satellite image archive, it is also possible to create maps that span decades to reveal long-term trends in water use. USGS scientists can map water use at different scales to address different water resource questions and concerns. Field-scale maps, for example, are powerful tools for estimating and managing water consumption on irrigated croplands. Basin-scale water-use maps assist in understanding water balance and availability in river basins and watersheds. These large-area maps are useful for:

•             Estimating water use by different sectors within a watershed.

•             Resolving disputes regarding water rights and allocations.

•             Evaluating aquifer depletions and quantifying net groundwater pumping.

This pair of ET water-use maps shows crop water use in California’s San Joaquin Valley in 1990 (left) and 2014 (right). Comparing the maps reveals changes in irrigation patterns during this period. Notice, for example, that water use intensified in many places (increase in blue areas) and some irrigated lands (green in 1990) transitioned out of agricultural production (reddish brown) by 2014.

This pair of ET water-use maps shows crop water use in California’s San Joaquin Valley in 1990 (left) and 2014 (right). Comparing the maps reveals changes in irrigation patterns during this period. Notice, for example, that water use intensified in many places (increase in blue areas) and some irrigated lands (green in 1990) transitioned out of agricultural production (reddish brown) by 2014.

Sensor: Multispectral (approx. 4-12 bands), Thermal

Platform: Satellite

Author: Gabriel Senay
Email: senay@usgs.gov
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Satellite-based Water Use Mapping

The USGS is applying satellite remote sensing resources and expertise to quantify evapotranspiration (ET) for the National Water Census and WaterSMART (Sustain and Manage America’s Resources for Tomorrow) initiative. Work developed at the USGS Earth Resources Observation and Science (EROS) Center is focused on understanding and quantifying the spatial and temporal distribution of water consumption, i.e., water that is used by the soil and vegetation complex and returned to the atmosphere in the form of evaporation and transpiration, which makes it unavailable for other uses. The USGS works collaboratively with stakeholders to enable powerful technical capabilities within a geographical context by targeting efforts in watersheds or basin-level Focus Area Studies, where the resulting tools and information can soon become the basis for monitoring and assessing water use across the Nation.

Changes in climate, land use, and water demand are placing increased pressure on the Upper Rio Grande Basin’s (URGB) limited water resources, necessitating careful water management decisions. Accordingly, in collaboration and coordination with the USGS New Mexico Water Science Center, maps of estimated water use were created for the 2015 growing season in the URGB using freely available Landsat thermal (infrared) imagery and weather data.  By planning today for water tomorrow, this work helps to ensure the research is timely and relevant in a regional and national context.

Determining remotely sensed ET and agricultural consumptive use from Landsat allows for temporal evaluation with a critical spatial component to see trends at the level of individual fields and across entire landscapes. Water use maps can allow insight into crop-specific productivity, drought implications, and water budget analyses, which can include surface and groundwater, and environmental flow. The USGS EROS develops and shares these ET products with USGS Water Science Centers that are responsible for compiling water use data every 5 years. Similarly, researchers at the North Central Climate Center and  the Bureau of Reclamation are evaluating these products for their usefulness for continual scientific analyses and agro-hydrologic modeling.

http://water.usgs.gov/watercensus/

2015 Annual Evapotranspiration Map of the Upper Rio Grande River Basin.

2015 Annual Evapotranspiration Map of the Upper Rio Grande River Basin.

Sensor: Thermal

Platform: Satellite

Author: Gabriel Senay
Email: senay@usgs.gov
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Spectral Analysis of Colored Dissolved Organic Matter (CDOM)

Colored dissolved organic matter (CDOM) is the humic-rich, optically active fraction of dissolved organic matter that is present in natural waters from the decomposition of detritus and other organic material. Also known as chromophoric dissolved organic matter, yellow substance, humic color, and gelbstoff, CDOM is an important measure of water quality and has important implications for drinking water, aquatic ecosystems, and metal transport. The Operational Land Imager (OLI) aboard Landsat 8 includes several technical improvements that create the potential for better monitoring of water quality from space.  These improvements include increased radiometric resolution (from 8 to 16 bits), and the addition of a coastal aerosol band (433–453 nm), which is especially useful for monitoring water-quality properties, such as CDOM. In addition, the development of a surface reflectance product by the USGS Earth Resources Observation and Science (EROS) Center provides consistent, high-quality atmospheric correction of Landsat 8 data.  Data from the Advanced Land Imager (ALI), the prototype for the OLI, during and after Hurricane Sandy show promising results in terms of areas of expected high CDOM before and after the hurricane.  In addition, testing of Landsat 8 data against corrected CDOM data from USGS streamgage stations shows promising relationships that could lead to new satellite-based monitoring of colored dissolved organic matter.

http://www.sciencedirect.com/science/article/pii/S0025326X1630128X

Colored dissolved organic matter (CDOM) gradients extracted from Advanced Land Imager (ALI) multispectral data for September 12, 2011 (a) and November 21, 2012 (b). Points indicate locations of wastewater treatment facilities that failed during Hurricane Sandy, releasing untreated and partially treated sewage into New York and New Jersey  waterways. Red areas indicate high levels of CDOM.

Colored dissolved organic matter (CDOM) gradients extracted from Advanced Land Imager (ALI) multispectral data for September 12, 2011 (a) and November 21, 2012 (b). Points indicate locations of wastewater treatment facilities that failed during Hurricane Sandy, releasing untreated and partially treated sewage into New York and New Jersey  waterways. Red areas indicate high levels of CDOM.

Sensor: Multispectral (approx. 4-12 bands)

Platform: Satellite

Author: Terry Slonecker
Email: tslonecker@usgs.gov
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Water - Groundwater

Assessing Geologic Controls on Groundwater Discharge

Streams in the Loup River Basin in the Sand Hills of Nebraska are sensitive to groundwater withdrawals because of the close hydrologic connection between groundwater and surface water.  Groundwater discharge constitutes over 90% of streamflow in the Loup River Basin.  The Upper and Lower Loup Natural Resources Districts, in cooperation with the USGS, received a grant from the Nebraska Environmental Trust to study the temporal and spatial characteristics of surface water/groundwater interaction within the basin.  Four stream reaches, totaling approximately 320 river miles, have been identified by the Upper and Lower Loup Natural Resources Districts as priority reaches where additional information is needed.  Currently, groundwater discharge is estimated from suveys completed in 2006, where streamflow was measured by conducting seepage runs at various points along a stream’s reach, often up to 15 miles apart.  However, streams in the Loup River Basin are known to receive substantial inflows from focused discharge, or groundwater discharged from springs.  Furthermore, the influence of various climatic and land use changes on groundwater discharge patterns is unknown.  This is the first study to sytematically map these areas of focused groundwater discharge and examine impacts of climate and land use change.

During fall 2015, airborne infrared imagery was collected over the two stream reaches prior to ice up.  During that time, warmer thermal anomalies in stream-surface temperatures are indicative of focused groundwater discharge.  Early results indicate zones of focused groundwater discharge were detected along the Dismal, the North Fork of the South Loup, and the upper South Loup Rivers.  Most areas of focused groundwater discharge were typically small (less than 0.1 ft3 per second); however, some discharge points on the Dismal River exceeded 2 ft3 per second.  A zone of focused groundwater discharge was detected downstream of the USGS streamgage at Arnold.  Here, the South Loup River incises into Pliocene-age gravel deposits and over a 15-mile reach where the additional groundwater discharge increases streamflow more than a factor of two.  Along this reach, a thermograph collected from a self-logging temperature sensor prior to ice up was shifted toward higher temperatures when compared to thermographs from other stream reaches, indicating groundwater discharge constituted a higher proportion of total streamflow.

http://ne.water.usgs.gov/projects/GWSWInteraction/index.html

Aerial thermal image of the Dismal River above the streamgage near Thedford, Nebraska.

Aerial thermal image of the Dismal River above the streamgage near Thedford, Nebraska.

Sensor: Thermal

Platform: Airplane

Author: Christopher Hobza
Email: cmhobza@usgs.gov
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Microgravity Measurement of Groundwater Storage Change

Groundwater is an important source of water for human use, especially in the arid Southwest. Changes in the amount of groundwater stored in an aquifer are typically estimated by observing groundwater-level change in a well and multiplying the observed change by an assumed value of aquifer porosity, which is the void space that contains groundwater in a subsurface rock formation. USGS scientists are leveraging microgravity measurements as a way to calculate aquifer proosity. These measurements capture subsurface changes in mass that are caused by groundwater-level changes in an aquifer. Repeated measurements of gravity at a network of sites at the land surface can be used to measure changes in the mass of groundwater at the water table. Combined with water-level measurements in nearby wells, the change in groundwater mass can be used to calculate the porosity of an aquifer.

The project has established a network of microgravity stations in southeastern Albuquerque, New Mexico, where groundwater levels declined by as much as 120 feet from 1950 to 2008, but have risen since 2008 when changes in groundwater pumping were implemented. The amount of water stored in the aquifer changes as water levels change, but without microgravity measurements the volume of groundwater storage change has to be estimated based on an assumed porosity value. Given microgravity measurements at a site where water-level measurements are also available, the porosity of the aquifer can be calculated and used to  obtain a better estimate of the volume of groundwater storage change at that site. When microgravity and water-level measurements are made at enough sites, the groundwater storage change can be extrapolated to an entire well field. In addition, if the porosity of the aquifer is known, gravity measurements can be made at a site without a well to estimate how much and how quickly the groundwater level is changing.

https://www.youtube.com/watch?v=3IV1xVLIVM0

Sensor: Gravity

Platform: Ground based / sensor web / web cam

Author: Nathan Myers
Email: nmyers@usgs.gov
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Use of Airborne, Surface, and Borehole Electromagnetics to Evaluate Groundwater Resources

Airborne, surface, and borehole geophysical surveys were conducted as a major component of a  groundwater resource exploration study of arid basins at Fort Irwin National Training Center (NTC) in the Mojave Desert in eastern California. To plan for the long-term water availability at the NTC, water resources are being evaluated in undeveloped groundwater basins underlying the NTC. Most of the undeveloped basins have little to no lithologic or historical hydrologic data, a common scenario for remote, mountainous, and arid regions.  To supplement the sparse hydrogeologic observations, two basin- to regional-scale airborne electromagnetic (AEM) and aeromagnetic surveys were conducted over the NTC using different survey designs, providing varying degrees of data density between basins. AEM surveys were compared to available data in each basin and included a combination of ground-based transient electromagnetic surveys, borehole geophysical and lithologic data, geologic  cross sections, and previously published estimates of basin-fill thickness derived from gravity data.  These data have been used to define subsurface geologic structure, locate faults, and refine the hydrostratigraphic framework of individual basins. A 3D geohydrologic framework model is under development using AEM-derived parameter zones that are constrained by hydrostratigraphic interpretations of borehole hydrologic and lithologic data. A groundwater-flow model is being developed to test different hydraulic properties estimated for the AEM-derived zones to provide a loosely constrained steady-state model. Although the steady-state models are based on sparse data, they can provide general constraints, including available water supply and effects of groundwater withdrawal, which can be used for more informed management decisions.

https://pubs.er.usgs.gov/publication/ofr20131024G

Maps show AEM flightlines and inverted AEM data at two depths for Leach Basin, California.

Maps show AEM flightlines and inverted AEM data at two depths for Leach Basin, California.

Sensor: Airborne electromagnetic survey (AEM)

Platform: Helicopter

Author: Jill Densmore
Email: jidensmo@usgs.gov
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Water Availability and Land Subsidence in California

Groundwater basins in California are being used as local reservoirs to supplement water supplies. Water managers need more information on the relationship between land subsidence and water extraction. Studies are being conducted in the San Joaquin Valley, the Coachella Valley, and at the Army’s Fort Irwin National Training Center (NTC) in California to provide important information for various Federal, State, and local stakeholders to manage and minimize the impacts of land subsidence upon water-conveyance infrastructures and water deliveries in the two valleys, and upon aircraft runways at the NTC. The studies use conventional and persistent scatter Interferometric Synthetic Aperture Radar (InSAR) remote sensing data derived from several satellites and Global Positioning System (GPS) data to measure land-surface elevation changes, which are then compared to groundwater levels and local geology. In the San Joaquin Valley, subsidence was detected in about half of the valley and includes parts of the California Aqueduct, Delta-Mendota Canal, the San Joaquin River, the Eastside Bypass, the Friant-Kern Canal, and numerous local canals; maximum subsidence rates approached 300 mm per year, and about 12,000 km2 was affected by at least 25 mm during 2008–2010; GPS data indicate those rates have continued through 2015. In the Coachella Valley, as much as 610 mm of subsidence during 1995–2010 was measured using InSAR. By 2015, however, GPS data indicate that subsidence in some parts of the valley has been arrested as groundwater levels rose in response to increased artificial groundwater recharge and decreased demand. In Fort Irwin’s Bicycle Basin, about 425 mm of subsidence during 1992–2015 was measured or estimated using InSAR; the differential subsidence across the basin has caused ground fissuring on and near the runway.

http://ca.water.usgs.gov/land_subsidence/california-subsidence-studies.html

Subsidence contours derived from interferograms generated from the Advanced Land Observing Satellite (ALOS) and the Environmental Satellite (ENVISAT) showing subsidence in the San Joaquin Valley, California, during 2008–2010.

Subsidence contours derived from interferograms generated from the Advanced Land Observing Satellite (ALOS) and the Environmental Satellite (ENVISAT) showing subsidence in the San Joaquin Valley, California, during 2008–2010.

Sensor: IFSAR / SAR / Radar

Platform: Ground based / sensor web / web cam, Satellite

Author: Michelle Sneed
Email: micsneed@usgs.gov
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