Land Use and Land Cover (LULC) changes are environmental processes that modify the land surface and affect a broad range of socioeconomic, biologic, geologic, and hydrologic systems. The goals of this project are to analyze contemporary LULC using Landsat satellite data and develop a systematic approach to identify causes of land change at regional and national scales. The objectives will be met by developing a methodology for integrating data from multiple data sources.
Climate and Land Cover Change
The USGS Cascades Volcano Observatory utilizes oblique and vertical aerial photography to monitor topographic changes at Mount St. Helens volcano.
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 Landsat-based, 30-m pixel resolution, land cover database for the Nation. 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.
Barrier islands are dynamic environments due to their position at the land-sea interface. Storms, waves, tides, currents, and relative sea-level rise are powerful forces that shape barrier island geomorphology and habitats (for example, beach, dune, marsh, and forest). Hurricane Katrina in 2005 and the Deepwater Horizon oil spill in 2010 are two major events that have impacted habitats and natural resources on Dauphin Island, Alabama.
Marsh canopy structure indicators of leaf area index (LAI) and leaf angle distribution (LAD) were mapped yearly from 2009 to 2012 in the Barataria Bay, Louisiana, coastal region – an area severely impacted by the 2010 Deepwater Horizon (DWH) oil spill. The mapping relied on summer collections of NASA's UAVSAR polarimetric synthetic aperture radar (PolSAR) image data.
The USGS has produced datasets that contain probabilities of hurricane-induced erosion for each 1-km section of the Gulf of Mexico coast in response to category 1–5 hurricanes. The analysis is based on a storm-impact scaling model that uses observations of beach morphology combined with sophisticated hydrodynamic models to predict how the coast will respond to the direct landfall of category 1–5 hurricanes.
An automated shoreline identification method was developed using standard image processing, geographic information system (GIS) techniques (https://woodshole.er.usgs.gov/project-pages/DSAS/version4/), and 2-m synthetic aperture radar (SAR) HH amplitude data. The development used five NASA Uninhabited Aerial Vehicle SAR (UAVSAR) images collected in summer and one in fall from 2009 to 2012.
Substantial loss of coastal wetland caused by the Deepwater Horizon (DWH) oil spill was documented for the first time in recent publications (http://onlinelibrary.wiley.com/doi/10.1002/2016GL070624/full). Those results demonstrated that the 2010 DWH oiling exacerbated wetland shoreline erosion, that erosion magnitude increased with oiling severity, and that oil-related erosion differed from storm-related shoreline erosion.
One measure of a society’s security is access to food, which is produced by a functioning, viable agricultural system that has access to sufficient water. An important metric to monitor for characterizing agricultural system viability and optimizing water use in agricultural areas is the amount of cropland left fallowed or unplanted. Fallowed croplands are difficult to model from remotely sensed data because they have many expressions; for example, they can be managed and remain free of vegetation or be abandoned and become weedy.
Climate variability and ballooning populations are putting unprecedented pressure on agricultural croplands and their water use, which are vital for ensuring global food and water security in the 21st century. In this context, there is a need to produce consistent and accurate global food security support-analysis data (GFSAD) at fine spatial resolution that are generated routinely (e.g., every year).