This study continues an effort that exploits the combination of two key datasets, the Landsat historical record and plot records from the US Forest Service (USFS) Forest Inventory and Analysis (FIA) program, for the purpose of developing a quantitative understanding of forest disturbance patterns in North America. The primary goals of this study are to: 1) Wall-to-Wall Annual Assessment of US Forest Disturbance History between 1985 and 2010. This approach not only reduces the errors encountered in early sampling efforts but also test automation of processing and analysis procedures which have previously been carried out in a handcrafted fashion. 2) The products of this comprehensive analysis, maps and statistics, will be subjected to a rigorous validation to provide quantitative assessments of the accuracy of these products. This will support interested users in understanding reliability our analysis. 3) An investigation of the satellite-observed forest recovery trajectories will be carried out in comparison to USFS Forest Inventory Analysis measurement. This work supports extended use of forest disturbance history analysis by linking the observed forest recovery with field measured growth dynamics. 4) The team will evaluate various attributes of the disturbance analyses, including the recovery trajectories and spatial patterns of the disturbed forest areas, to evaluate how successfully the causal factors that led to the observed disturbances may be extracted from the Landsat observations. http://www.geogresearch.umd.edu/goward/
Institutitional Principal Investigators:
Dr. Chengquan Huang, Dept Geographical Sciences, Uuiversity of Maryland
Dr. Jeffery Masek, Biospheric Sciences, NASA Goddard Spaceflight Center, Greenbelt MD
Dr. Warren Cohen, Pacific Northwest Research Station, US Forest Service, Corvallis, Oregon
Dr. Gretchen Moisen, Rocky Mountains Research Station, US Forest Service, Ogeden UT
Dr. Rama Nemani, NASA Ames Researh Center, Moffet Field CA.
Project Manager: Karen Schleeweis, Dept Geogaphcal Sciences, University of Maryland
