A Decision Support System for Monitoring, Reporting and Forecasting Ecological Conditions of the Appalachian National Scenic Trail

Yeqiao Wang, University of Rhode Island, yqwang@uri.edu (Presenter)
Ramakrishna R. Nemani, NASA ARC, rama.nemani@nasa.gov
Fred Dieffenbach, NPS, fred_dieffenbach@nps.gov
Ken Stolte, USDA FS, kstolte@fs.fed.us
Glenn Holcomb, USGS, gholcomb@usgs.gov
Marcia McNiff, USGS, mmcniff@usgs.gov
Matt Robinson, NPS, matt_robinson@nps.gov
Casey Reese, NPS, casey_reese@nps.gov
Roland Duhaime, University of Rhode Island, roland@edc.uri.edu
Christopher Damon, University of Rhode Island, chris@edc.uri.edu
Peter August, University of Rhode Island, pete@edc.uri.edu
Forrest Melton, NASA ARC/CSUMB, forrest.s.melton@nasa.gov
Hirofumi Harshimoto, NASA ARC/CSUMB, hirofumi.hashimoto@gmail
Sam Hiatt, NASA ARC/CSUMB, samhiatt@gmail.com
John Clark, University of Rhode Island, jclark817@gmail.com
Fu Luo, University of Rhode Island, lfu@ele.uri.edu
Brian Mitchell, NPS, brian_mitchell@nps.gov
Charles LaBash, University of Rhode Island, labash@edc.uri.edu
Peter Paton, University of Rhode Island, ppaton@uri.edu
Geri Tierney, SUNY, gtierney@esf.edu

The Appalachian National Scenic Trail (A.T.) traverses most of the high elevation ridges of the eastern United States, extending about 3,676 kilometers across 14 states, from Springer Mountain in Northern Georgia to Mount Katahdin in central Maine. The A.T. and its surrounding protected lands harbor forests with some of the greatest biological diversity in the U.S. The north-south alignment and high elevation setting of the A.T. provide an ideal barometer for early detection of undesirable changes in the ecosystems, from development encroachment to climate change and the effects on phenology, forest conditions and landscape characteristics. This project employs NASA multiplatform remote sensing data, NASA Terrestrial Observation and Prediction System (TOPS) modeling, and in situ measurements to develop a decision support system for monitoring, reporting and forecasting ecological conditions of the A.T. lands. The objectives of this study include: 1. Develop a comprehensive set of seamless indicator data layers consistent with the A.T. environmental “vital signs”; 2. Incorporate in situ observations to complement TOPS data and modeling outputs; 3. Assess historical and current ecosystem conditions and forecast trends by coupling TOPS with habitat models; and 4. Develop an Internet-based implementation and dissemination system for data visualization, sharing, and management to facilitate collaboration and promote public understanding of the A.T. environment. In particular the project focuses on identified vital signs of phenology and climate change, forest health, and landscape dynamics. This study provides the seamless data with spatial coverage and time frequency for the study areas. The extracted information and revealed spatial and temporal landscape patterns help understand the changing A.T. environment. The data products, analysis findings and forecasting results established the reference and knowledge base. The Internet-based toolsets and interfaces provide decision support tools for monitoring, reporting and forecasting ecological conditions of the A.T. lands.

Presentation Type:  Poster

Session:  Science in Support of Decision Making   (Wed 10:00 AM)

Associated Project(s): 

• Wang, Y.Q.: A decision support system for monitoring, reporting and forecasting the ecological conditions of the Appalachian National Scenic Trail ...details

Poster Location ID: 303