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Ecosystem Performance, Productivity and Sustainability
Science Center Objects
Remotely-sensed data forms the backbone of the large-scale maps, models and assessments created at EROS to advance the understanding of Ecosystem Performance, Productivity and Sustainability.
Detailed data from cooperators with site-specific flux towers are integrated to create models of a land cover type - grassland, for example – which can be simulated across a region. Tasks describe exchanges of Gross Primary Productivity (GPP) and Net Ecosystem Exchange (NEE) in the Northern Great Plains and other regions.
Cooperation with the Bureau of Land Management (BLM), universities, and others provides the ground data to develop and validate pixel-specific models of ecosystem performance based on the remote sensing archive, climate, and site potential.
This modeling, EROS’ rich archival resources and the research team’s special ability to combine near real-time, remotely-sensed data with other large spatial data sets, also allows for the evaluation, mapping, and dynamic monitoring of ecosystem performance.
The work is funded through the USGS Land Change Science (LCS) Program, which strives to understand the nation's most pressing environmental, natural resource, and economic challenges by providing the information and tools necessary and identifying possible solutions.
Additional funding comes from USGS National Land Imaging program, BLM, and the U.S. Fish and Wildlife Service (FWS).
EROS’ remote sensing ecology projects include permafrost and biomass mapping in Alaska, the study of invasive grass in the Great Basin, and the identification of lands with the potential for biofuels feedstock. Follow these links for more detailed information on those projects:
- Quantitative modeling and mapping of near-surface permafrost and organic layer thickness in Alaska
- Estimation of aboveground biomass in Interior Alaska
- Mapping aboveground boreal forest biomass in the Yukon River Basin, Alaska
- Cheatgrass Dieoff Time-series Dynamics, 2000-2010
- Identifying Lands Suitable for Biofuel Feedstock Crops by Dynamic Modeling of Ecosystem Performance
- Carbon Flux Quantification in the Great Plains