ForWarn is a satellite-based forest monitoring tool that is being used to detect and monitor disturbances to forest conditions and forest health. It has been developed through the synergistic efforts, capabilities and contributions of four federal agencies, including the US Forest Service Eastern Forest and Western Wildland Environmental Threat Assessment Centers, NASA Stennis Space Center (SSC), Department of Energy's (DOE) Oak Ridge National Laboratory (ORNL) and US Geological Survey Earth (USGS) Earth Research Observation System (EROS), as well as university partners, including the University of North Carolina Asheville's National Environmental Modeling and Analysis Center (NEMAC). This multi-organizational partnership is key in producin...
Forest ecosystems fulfill a whole host of ecosystem functions that are essential for life on our pla...
This case study shows the promise of computing current season forest disturbance detection products ...
National but locally relevant forest disturbance datasets are required to implement successful conse...
The USDA Forest Services Asheville, North Carolina-based Eastern Forest Environmental Threat Assessm...
Forest threats across the US have become increasingly evident in recent years. Sometimes these have ...
U.S. forests occupy approx 751 million acres (approx 1/3 of total land). Several abiotic and biotic ...
The National Early Warning System (EWS) is a coordinated effort to bring cutting-edge monitoring and...
U.S. forests occupy approx. 751 million acres (approx. 1/3 of total land). These forests are exposed...
Forest inventory, forest stress, and standardization and calibration studies are presented. These in...
This presentation discusses MODIS NDVI change detection methods and products used in the ForWarn Ear...
A 3D forest monitoring system, called FORSAT (a satellite very high resolution image processing plat...
The DEVELOP program is a student run and led internship program that creates pilot demonstration pro...
A 3D forest monitoring system, called FORSAT (a satellite very high resolution image processing plat...
Forests provide a large range of beneficial services, including tangible ones such as timber and rec...
Near real time forest disturbance detection maps from MODIS NDVI phenology data have been produced s...
Forest ecosystems fulfill a whole host of ecosystem functions that are essential for life on our pla...
This case study shows the promise of computing current season forest disturbance detection products ...
National but locally relevant forest disturbance datasets are required to implement successful conse...
The USDA Forest Services Asheville, North Carolina-based Eastern Forest Environmental Threat Assessm...
Forest threats across the US have become increasingly evident in recent years. Sometimes these have ...
U.S. forests occupy approx 751 million acres (approx 1/3 of total land). Several abiotic and biotic ...
The National Early Warning System (EWS) is a coordinated effort to bring cutting-edge monitoring and...
U.S. forests occupy approx. 751 million acres (approx. 1/3 of total land). These forests are exposed...
Forest inventory, forest stress, and standardization and calibration studies are presented. These in...
This presentation discusses MODIS NDVI change detection methods and products used in the ForWarn Ear...
A 3D forest monitoring system, called FORSAT (a satellite very high resolution image processing plat...
The DEVELOP program is a student run and led internship program that creates pilot demonstration pro...
A 3D forest monitoring system, called FORSAT (a satellite very high resolution image processing plat...
Forests provide a large range of beneficial services, including tangible ones such as timber and rec...
Near real time forest disturbance detection maps from MODIS NDVI phenology data have been produced s...
Forest ecosystems fulfill a whole host of ecosystem functions that are essential for life on our pla...
This case study shows the promise of computing current season forest disturbance detection products ...
National but locally relevant forest disturbance datasets are required to implement successful conse...