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
Using satellite vegetation and compound topographic indices to map highly erodible cropland buffers for cellulosic biofuel crop developments in eastern Nebraska, USA
Spatially explicit estimation of aboveground boreal forest biomass in the Yukon River Basin, Alaska
Downscaling 250-m MODIS growing season NDVI based on multiple-date landsat images and data mining approaches
The integration of geophysical and enhanced Moderate Resolution Imaging Spectroradiometer Normalized Difference Vegetation Index data into a rule-based, piecewise regression-tree model to estimate cheatgrass beginning of spring growth
Mapping and monitoring cheatgrass dieoff in rangelands of the Northern Great Basin, USA
Estimating switchgrass productivity in the Great Plains using satellite vegetation index and site environmental variables
Application-ready expedited MODIS data for operational land surface monitoring of vegetation condition
Effects of disturbance and climate change on ecosystem performance in the Yukon River Basin boreal forest
Geostatistical estimation of signal-to-noise ratios for spectral vegetation indices
Spatial variability and landscape controls of near-surface permafrost within the Alaskan Yukon River Basin
Annual crop type classification of the U.S. Great Plains for 2000 to 2011
Distribution and landscape controls of organic layer thickness and carbon within the Alaskan Yukon River Basin
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.