Detailed analysis of forest disturbance results derived from Landsat time series stacks (LTSS)
Nancy
E.
Thomas, Department of Geography, University of Maryland, nthomas1@umd.edu
(Presenting)
Chengquan
Huang, Department of Geography, University of Maryland, cqhuang@umd.edu
Samuel
N.
Goward, Department of Geography, University of Maryland, sgoward@umd.edu
Scott
L.
Powell, U.S.D.A. Forest Service, Pacific Northwest Research Station, scott.powell@oregonstate.edu
Karen
Schleeweis, Department of Geography, University of Maryland, ska1@umd.edu
Khaldoun
Rishmawi, Department of Geography, University of Maryland, rishmawi@umd.edu
Robert
E.
Kennedy, U.S.D.A. Forest Service, Pacific Northwest Research Station, robert.kennedy@oregonstate.edu
Through a NASA funded project – “North American Forest Disturbance and Regrowth since 1972 (NAFD)”, Landsat time series stacks (LTSS) have been assembled for 29 locations selected to represent forest dynamics in the United States. The LTSS have been used to automatically map forest disturbance and regrowth with a nominal temporal interval of 2 years from 1972 to 2005. This poster will present a detailed analysis of the results we have derived for the TM/ETM+ era of the Landsat missions – from 1984 to 2005. Several methods of map validation are used to assess the disturbance map results, including visual inspection of all disturbance maps and targeted field reconnaissance. We also incorporate FIA nation-wide field observations by plotting stand age derived from disturbance maps against FIA determined stand age. An additional method of map validation utilizes visual analysis of high-resolution aerial photography for one point in time along with visual interpretation of the full Landsat time series to label sample points derived from a stratified random sample of the change maps. This in-depth visual analysis was performed for 7 of the 29 sample LTSS, chosen to represent different disturbance regimes. Results for these LTSS are provided in standard error matrix form, with overall accuracies ranging from 69% to 85%. We analyze the resulting errors of commission and omission for each LTSS, and present examples to illustrate the strengths and weaknesses of the disturbance algorithm.
NASA Carbon Cycle & Ecosystems Active Awards Represented by this Poster: