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Our Western Geographic Science Center (WGSC) priority is to continue the important work of the Department of the Interior and the USGS, while also maintaining the health and safety of our employees and the community. Based on guidance from the White House, the CDC, and state and local authorities, we are shifting our operations to a virtual mode and have minimal staffing within our offices. If you need additional assistance, please contact Susan Benjamin, sbenjamin@usgs.gov.
Anne Wein Wins Bay Area Metro Award!
Congratulations to Dr. Anne Wein, Operations Research Analyst at WGSC, who received a 2019 Bay Area Metro Award for her work as lead researcher for the HayWired earthquake scenario!
Learn moreRemote Sensing and Dryland Management
With the use of remote sensing and spatial analysis, WGSC scientists study dryland vegetation and soils to determine disturbances and help manage recovery.
Learn moreProjects and teams at WGSC
Just a few examples of WGSC projects and science teams.
Global Food Security-Support Analysis Data at 30 m (GFSAD30)
Hazards Societal Consequences and Risk Communication
Land-Use and Climate Change Team (LUCC)
Applied Landscape Ecology and Remote Sensing
Patterns in the Landscape – Analyses of Cause and Effect (PLACE)
News
Media Advisory: A Jaguar’s Field of Dreams – Live Online Public Lecture
The U.S. Geological Survey public lecture series is back and virtual. News reporters are invited to attend to learn how USGS scientists are helping protect one of the only jaguars that lives in the U.S.
New Geo-Narrative explores California’s exposure to volcanic hazards
The first step in mitigating volcanic risk and building community resilience to volcanic hazards is identifying what and who is in harm’s way.
Anne Wein Wins Prestigious 2019 Bay Area Metro Award
Congratulations to Dr. Anne Wein, Operations Research Analyst at WGSC, who received a 2019 Bay Area Metro Award from the Association of Bay Area Governments and the Metropolitan Transportation Commission for her work as lead researcher for the HayWired earthquake scenario.
Publications
Classifying crop types using two generations of hyperspectral sensors (Hyperion and DESIS) with machine learning on the cloud
Advances in spaceborne hyperspectral (HS) remote sensing, cloud-computing, and machine learning can help measure, model, map and monitor agricultural crops to address global food and water security issues, such as by providing accurate estimates of crop area and yield to model agricultural productivity. Leveraging these advances, we used the Earth...
Aneece, Itiya; Thenkabail, Prasad
Global cropland-extent product at 30-m resolution (GCEP30) derived from Landsat satellite time-series data for the year 2015 using multiple machine-learning algorithms on Google Earth Engine cloud
Executive SummaryGlobal food and water security analysis and management require precise and accurate global cropland-extent maps. Existing maps have limitations, in that they are (1) mapped using coarse-resolution remote-sensing data, resulting in the lack of precise mapping location of croplands and their accuracies; (2) derived by collecting and...
Thenkabail, Prasad S.; Teluguntla, Pardhasaradhi G.; Xiong, Jun; Oliphant, Adam; Congalton, Russell G.; Ozdogan, Mutlu; Gumma, Murali Krishna; Tilton, James C.; Giri, Chandra; Milesi, Cristina; Phalke, Aparna; Massey, Richard; Yadav, Kamini; Sankey, Temuulen; Zhong, Ying; Aneece, Itiya; Foley, Daniel Hierarchical clustering for paired watershed experiments: Case study in southeastern Arizona, U.S.A.
Watershed studies are often onerous due to a lack of data available to portray baseline conditions with which to compare results of monitoring environmental effects. A paired-watershed approach is often adopted to simulate baseline conditions in an adjacent watershed that can be comparable but assumes there is a quantifiable relationship between...
Petrakis, Roy; Norman, Laura M.; Vaughn, Kurt; Pritzlaff, Richard; Weaver, Caleb; Rader, Audrey J; Pulliam, H. Ronald