Sources/Usage: Public Domain. View Media Details

The postdoctoral fellows will work from the USGS Earth Resources Observation and Science (EROS) Center near Sioux Falls, SD or Santa Barbara, CA.

Each position will focus on research to improve the quality and value of LCMAP operations though the integration of new data sources, the development of improved methods, and the study of the interplay of climate variables and land surface change.

LCMAP identifies land surface changes through time. LCMAP products are intended for studies on phenological cycles, land change related to disturbances like fires, floods or forest disease, or studies on gradual change like woody encroachment or urban growth. LCMAP supports real-world decisions for American farmers, ranchers, firefighters, and water and land managers looking to use natural resources effectively while protecting lives and livelihoods.

Research proposals for the first position should focus on land surface change detection, with investigation of rapid change detection, the use of earlier Landsat data, data from other satellite sensors like those onboard the European Space Agency’s Sentinel-2, as well as other methods that could improve LCMAP’s change detection. Current opportunities include:

• increasing the timeliness of land change detection,
• integrating additional satellite data sources,
• improving the consistency of change detection algorithms across space and time,
• and testing and implementing additional change detection algorithms

Heather Tollerud, a research physical scientist who leads LCMAP’s Research and Development team, emphasized that the first fellowship would appeal to researchers with an interest in algorithm development.

More information on the first position and details on how to apply are available at this link.

The second available fellowship zeroes in on the interactions of climate variables with land surface change. The successful candidate will work with both the LCMAP team and Chris Funk, a climatologist who works with the USGS Early Warning team while directing the Climate Hazards Center at the University of California-Santa Barbara.

Proposals should focus on outlooks for satellite observations through statistical, machine learning, or other approaches and evaluating the skill of these algorithms in a variety of geographic locations. Previous work has used surface reflectance values from systems like Landsat to forecast short-term outlooks for indices like Normalized Difference Vegetation Index (NDVI). For this fellowship, the goal will be to predict the surface reflectance values themselves, opening the door to numerous derived products to support fire danger prediction, ranching decisions, rangeland management and more.

“This could help land managers to know what to look for in the coming season,” Tollerud said. “In order to do that, we’d want to look at the past surface reflectance history, but also at the climate history.”

More information on the second position and details on how to apply are available at this link.

The closing date for proposals on each fellowship is January 4, 2021.