Images

A fact sheet that shows the RUSH tool’s characteristics and graphical user interface.

The graphical user interface of the Cloud-based tidal marsh biomass mapping tool that highlights features and map outputs.

The GFSAD is a NASA funded project (2023-2028) to provide highest-resolution global cropland data and their water use that contributes towards global food-and-water security in the twenty-first century. This image was taken after day one of the 4th GFSAD project workshop hosted in Flagstaff, Arizona.

The GFSAD is a NASA funded project (2023-2028) to provide highest-resolution global cropland data and their water use that contributes towards global food-and-water security in the twenty-first century. This image is from the GFSAD project members' 4th workshop hosted in Flagstaff, Arizona where Dr.

A fire stopped through active suppression activities at a fuel break in Idaho. 

Examples of three types of intertidal biofilms observed at study sites with varying pigmentation. (a) Dark gray-greens are indicative of cyanobacteria; (b) Golden brown is indicative of diatoms; (c) Bright green is indicative of chlorophytes.

Western sandpiper foraging on a mudflat. This shorebird, which winters along coasts across the Americas and breeds in northern Alaska), may consume up to 20 percent of their body weight in biofilm per hour when fueling up for migration. 

Maps of (a) chl-a concentration, (b) carbohydrates, (c) lipids, and (d) total organic carbon in southern San Francisco Bay, 15 April 2021, based on final partial least squares regression models and AVIRIS-NG 3.7 m imagery. Base map from Esri and its licensors, copyright 2022.

Map showing estimated light absorption at 440nm, a proxy for the amount of colored dissolved organic matter in south San Francisco Bay waters. Project page: Remote Sensing of Mercury Pollution in South San Francisco Bay.

High-resolution multispectral imagery collected in March 2024 by USGS of NPS vegetation monitoring plots at Palo Alto Battlefield in Brownsville, TX. The black boxes outline the sampling plot perimeter, and the green polygons outline patches of cordgrass (Spartina).

High-resolution multispectral imagery collected in March 2024 by USGS of NPS vegetation monitoring plots at Palo Alto Battlefield in Brownsville, TX. The black boxes outline the sampling plot perimeter, and the green polygons outline patches of cordgrass (Spartina).

High-resolution multispectral imagery collected in March 2024 by USGS of NPS vegetation monitoring plots at Palo Alto Battlefield in Brownsville, TX. The black boxes outline the sampling plot perimeter, and the green polygons outline patches of cordgrass (Spartina).

High-resolution multispectral imagery collected in March 2024 by USGS of NPS vegetation monitoring plots at Palo Alto Battlefield in Brownsville, TX. The black boxes outline the sampling plot perimeter, and the green polygons outline patches of cordgrass (Spartina).

Community members of the SCAT collecting tamarisk beetles on the Reservation (photo by Roy Petrakis, USGS) and USGS scientists teaching at the San Carlos Apache Tribe Summer Youth Practicum for Environmental Protection where the kids were talking about, learning about,  and building NIDS (photo by Christy Sangster Begay, SCAT). 

Community members of the SCAT collecting tamarisk beetles on the Reservation (photo by Roy Petrakis, USGS) and USGS scientists teaching at the San Carlos Apache Tribe Summer Youth Practicum for Environmental Protection where the kids were talking about, learning about, and building NIDS (photo by Christy Sangster Begay, SCAT). 

The USGS Western Geographic Science Center has been partnering with collaborators from the San Carlos Apache Tribe (SCAT) and Bureau of Indian Affairs (BIA) to address natural resource questions since 2004. We work with SCAT Departments of Forestry, Range Management and Environmental Protection. 

FIGURE: A map showing the primary study site, including the San Carlos River and Bylas Reach of the Gila River from Petrakis et al. (2023[LN1] ).

RUSH is a tool for rapid repeat high resolution coastal vegetation maps to improve forecasting of hurricane impacts and coastal resilience.

Examples of high and low temporal resolution. A high-resolution sensor might image an area every day or two, whereas a low-resolution sensor might only image an area on the order of weeks.

This teacup has a moderate amount of dissolved organic material, which absorbs blue light but reflects some red and orange light. The coffee cup has a high amount of dissolved organic matter and appears almost black because of how much light it is absorbing.

Low versus high radiometric resolution. Low resolution is low data storage, meaning only a few shades can be seen (as in the left image), high resolution is more data storage and means more shades can be recorded (right image).