Science Inventory



Our research objectives are to: (a) develop new methods using satellite remote sensor data for the rapid characterization of LC condition and change at regional to national scales; (b) evaluate the utility of the new NASA-EOS MODIS (Moderate Resolution Imaging Spectrometer) leaf area index (LAI) measurements for regional scale application with landscape process models (e.g., biogenic emissions and atmospheric deposition); (c) provide remote sensor derived measurement data to advance the development of the next generation of distributed landscape process-based models to provide a predictive modeling capability for important ecosystem processes (e.g., nutrients, sedimentation, pathogens, etc.); and (d) integrate in situ monitoring measurement networks with UAV and satellite based remote sensor data to provide a continuous environmental monitoring capability.


The characterization of land-cover (LC) type, extent, and distribution represent important landscape characterization element required for monitoring ecosystem conditions and for primary data input to biogenic emission and atmospheric deposition models. Current spectral-based characterization and change detection techniques tend to be performance limited in biologically complex ecosystems owing to vegetation phenology induced errors. A primary objective of this research is to develop advanced LC classification and change detection methods to provide better quality landscape characterization products for priority EPA applications.

Currently ecosystem modeling applications are limited by their accuracy, spatial resolution, and predictive capability. Because ecosystems are inherently complex and driven by dynamic processes that are often location specific, dynamic spatially-explicit models coupled to remote sensor derived measurement data are needed to enhance EPA's future modeling capabilities. This research will first include the evaluation of the NASA Earth Observing System (EOS) land products to support priority EPA ecosystem modeling efforts. This research will be a collaborative effort with the EPA modeling community to develop the next generation of remote sensor driven multi-media landscape-based process models for EPA assessment and regulation.

To keep pace with the expanding scope and complexity of EPA's mission the Agency must take advantage of rapidly maturing information technologies (IT) capabilities to significantly expand our monitoring data acquisition capabilities. This research adopts and integrates advanced technologies developed by the Department of Defense (DOD), National Aeronautics and Space Administration (NASA), and the private sector. EPA is collaborating with NASA to develop terrestrial, coastal ocean, and surface-troposphere flux unmanned aerial vehicle (UAV) missions. These missions will combine advanced multi-sensor packages with the extended duration UAV platform capabilities to provide the Agency with a next generation environmental monitoring capability. The ultimate goal is to provide EPA staff with a new data rich environment to significantly increase productivity and enhance the scientific knowledge base to support environmental decision making.

Record Details:

Record Type: PROJECT
Start Date: 10/01/2000
Projected Completion Date: 09/01/2009
OMB Category: Other
Record ID: 11068