U.S. Department of the Interior
The USGS presently operates 102 streamgaging stations distributed throughout Alaska. As many of these stations are quite remote, considerable effort is needed to collect periodic measurements and maintain gages. Thus, developing remote sensing methods for measuring streamflow in this vast, largely inaccessible State is valuable for many reasons.
High-resolution hydrographic mapping, which provides essential data for flood mitigation and planning, has been completed on thirteen, 12-digit hydrologic units near Sioux Falls in southeastern South Dakota. A lidar-derived digital elevation model was processed to include culvert locations into the modeled drainage network.
Archival aerial stereo-photographs are a source of information that can be used to create historical topography models for rapidly changing landscapes. Researchers completed a pilot study in Malakoff Diggins State Historic Park (MDSHP), which was once the largest hydraulic mine (1.6 square kilometers) in the Sierra Nevada of California. Legacy impacts in these mined landscapes include remnant steep exposures of highly erodible Eocene-aged auriferous sediments.
The goal of the USGS 3D Elevation Program (3DEP) is to complete nationwide coverage of lidar data for the conterminous United States, Hawaii, and the U.S. territories and interferometric synthetic aperture radar (IfSAR) for Alaska within 8 years—that is, by 2023--contingent upon sufficient funding.
The USGS 3D Elevation Program (3DEP) is managing the acquisition of lidar data across the Nation for high-resolution mapping of the land surface, which is useful for multiple applications. While lidar data are available for many Department of the Interior (as well as other Federal) lands in the U.S., these data are underutilized for vegetation analyses, partly due to the lack of local personnel and software capable of processing and analyzing lidar data.
In late May, the Department of the Interior (DOI) announced that the LANDFIRE (Landscape Fire and Resource Management Planning Tools) Program was the recipient of the 2017 DOI "Environmental Dream Team" award. The award recognizes the program team as exceptional environmental champions and agents of change. Led by the DOI and the U.S.
The Landscape Fire and Resource Management Planning Tools (LANDFIRE) Program developed the original LANDFIRE National product suite using Landsat data (circa 2001) to identify disturbances on the landscape. Although these products were updated regularly (LF 2008, 2010, 2012, and 2014), the base layers themselves are now more than 15 years old. To make the base data current, LANDFIRE is remapping the United States to produce a new product suite.
In 2017, the National Park Service approached the USGS National Unmanned Aircraft Systems (UAS) Project Office to acquire geospatial data in support of developing a flood management plan for the Fort Laramie National Historic Site, Fort Laramie, Wyoming. Originally established as a private fur trading fort in 1834, Fort Laramie evolved into the largest military post on the northern plains and eventually became part of the National Park System in 1938.
High-resolution digital elevation models generated from airborne lidar are often used for studying dynamics specific to barrier islands, including assessing morphology, extracting shorelines, and mapping habitats. While airborne lidar data have revolutionized the spatial scale for which elevations can be realized, elevation uncertainty limitations are often magnified in digital elevation models in coastal settings. For instance, researchers have found digital elevation models produced from airborne lidar can have a vertical uncertainty as high as 60 centimeters in densely vegetated marsh.
There are 88 NPS park units designated as Ocean and Coastal Parks that encompass 11,000 shoreline miles and 2.5 million acres of ocean and Great Lakes waters. Due to the large and complex nature of these park units, managing natural and cultural resources can be difficult. Benthic (meaning ocean floor or lake bottom) habitat maps are a spatially explicit way to identify submerged features.