Ecosystem Performance, Productivity and Sustainability
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:
- Monitoring Arctic and boreal ecosystems through the assimilation of field-based studies, remote sensing, and modelling
- 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
Below are other science projects associated with this project.
Below are publications associated with this project.
Distribution of near-surface permafrost in Alaska: estimates of present and future conditions
Historical and projected trends in landscape drivers affecting carbon dynamics in Alaska
The interacting roles of climate, soils, and plant production on soil microbial communities at a continental scale
Temporal expansion of annual crop classification layers for the CONUS using the C5 decision tree classifier
In situ nuclear magnetic resonance response of permafrost and active layer soil in boreal and tundra ecosystems
Mapping marginal croplands suitable for cellulosic feedstock crops in the Great Plains, United States
Grassland and cropland net ecosystem production of the U.S. Great Plains: Regression tree model development and comparative analysis
An optimal sample data usage strategy to minimize overfitting and underfitting effects in regression tree models based on remotely-sensed data
Near-real-time cheatgrass percent cover in the Northern Great Basin, USA, 2015
Cheatgrass percent cover change: Comparing recent estimates to climate change − Driven predictions in the Northern Great Basin
Evidence for nonuniform permafrost degradation after fire in boreal landscapes
Developing a 30-m grassland productivity estimation map for central Nebraska using 250-m MODIS and 30-m Landsat-8 observations
Distribution of near-surface permafrost in Alaska: estimates of present and future conditions
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:
- Monitoring Arctic and boreal ecosystems through the assimilation of field-based studies, remote sensing, and modelling
- 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
Below are other science projects associated with this project.
Below are publications associated with this project.