HR: 09:15h
AN: IN41B-05    [Abstracts]
TI: Remote Sensing and Ecosystem Modeling for Protected Area Management
AU: * Melton, F
EM: forrest.s.melton@nasa.gov
AF: California State University Monterey Bay, 100 Campus Center, Seaside, CA 93955, United States
AU: * Melton, F
EM: forrest.s.melton@nasa.gov
AF: NASA Ames Research Center, Mail Stop 242-4, Moffett Field, CA 94035, United States
AU: Michaelis, A
AF: California State University Monterey Bay, 100 Campus Center, Seaside, CA 93955, United States
AU: Michaelis, A
AF: NASA Ames Research Center, Mail Stop 242-4, Moffett Field, CA 94035, United States
AU: Votava, P
AF: California State University Monterey Bay, 100 Campus Center, Seaside, CA 93955, United States
AU: Votava, P
AF: NASA Ames Research Center, Mail Stop 242-4, Moffett Field, CA 94035, United States
AU: Milesi, C
AF: California State University Monterey Bay, 100 Campus Center, Seaside, CA 93955, United States
AU: Milesi, C
AF: NASA Ames Research Center, Mail Stop 242-4, Moffett Field, CA 94035, United States
AU: Hashimoto, H
AF: California State University Monterey Bay, 100 Campus Center, Seaside, CA 93955, United States
AU: Hashimoto, H
AF: NASA Ames Research Center, Mail Stop 242-4, Moffett Field, CA 94035, United States
AU: Hiatt, S
AF: NASA Ames Research Center, Mail Stop 242-4, Moffett Field, CA 94035, United States
AU: Nemani, R
AF: NASA Ames Research Center, Mail Stop 242-4, Moffett Field, CA 94035, United States
AB: Managers of U.S. national parks and international protected areas are under increasing pressure to monitor changes in park ecosystems resulting from climate and land use change within and adjacent to park boundaries. Despite great interest in these areas and the fact that some U.S. parks receive as many as 3.5 million visitors per year, U.S. and international protected areas are often sparsely instrumented, making it difficult for resource managers to quickly identify trends and changes in landscape conditions. Remote sensing and ecosystem modeling offer protected area managers important tools for monitoring of ecosystem conditions and scientifically based decision-making. These tools, however, can generate large data volumes and can require labor-intensive data processing making them difficult for protected area managers to use. To overcome these obstacles, the Terrestrial Observation and Prediction System (TOPS) is currently being applied to automate the production, analysis, and delivery of a suite of data products from NASA satellites and ecosystem models to assist managers of U.S. national parks. TOPS uses ecosystem models to combine satellite data with ground-based observations to produce nowcasts and forecasts of ecosystem conditions. We are utilizing TOPS to deliver data products via a browser-based interface to NPS resource managers in near real- time for use in landscape monitoring and operational decision-making. Current products include measures of vegetation condition, ecosystem productivity, soil moisture, snow cover, climate, and fire occurrence. The use of TOPS component models and technologies streamlines the data processing chain and automates the process of ingesting and synthesizing heterogeneous data inputs. In addition, we describe the use of TOPS to automate the identification of trends and anomalies in ecosystem conditions, enabling protected area managers to track park-wide conditions daily, identify significant changes, focus monitoring efforts, and improve decision making through infusion of NASA data.
UR: http://ecocast.arc.nasa.gov
DE: 0439 Ecosystems, structure and dynamics (4815)
DE: 0466 Modeling
DE: 0480 Remote sensing
DE: 1632 Land cover change
SC: Earth and Space Science Informatics [IN]
MN: 2007 Fall Meeting