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Fine Scale Assessment of Forest Cover Change over South America using Landsat Data
Chengquan
Huang, University of Maryland, cqhuang@umd.edu
(Presenter)
Joe
Sexton, UMD, jsexton@umd.edu
Raghuram
Narasimhan, UMD, raghu28@umd.edu
Kuan
Song, UMD, kuan@umd.edu
Jeffrey
Masek, NASA GSFC, jeffrey.g.masek@nasa.gov
DoHyung
Kim, UMD, rsgis@umd.edu
Danxia
Song, UMD, dxsong@umd.edu
XP
Song, UMD, xpsong@umd.edu
Min
Feng, UMD, feng.tank@gmail.com
Saurabh
Channan, UMD, schannan@umd.edu
Bin
Tan, ERT/NASA GSFC, btan@ertcorp.com
John
R.
Townshend, University of Maryland, jtownshe@umd.edu
Land cover change is one of the most important drivers of changes in the Earth System. Of all land cover changes, deforestation is one of the most significant because of the magnitude of the resultant transformations in biophysical and ecological properties. Forest cover change is highly relevant to many studies of pressing environmental issues, including the global carbon cycle, changes in the hydrological cycle, an understanding of the causes of changes in biodiversity and in understanding the rates and causes of land use change. As such, a number of national and international programs call for routine monitoring of global forest changes.
Accurate characterization of forest change requires Landsat-class resolution data sets, because many changes, especially those resulting from anthropogenic factors, occur at hectare or sub-hectare scales. This poster reports on an assessment of forest cover change using Landsat data over the South America continent, which is part of a larger, ongoing global forest cover change mapping activity. We have produced surface reflectance products using Global Land Survey (GLS) Landsat images acquired around1990, 2000, and 2005, and are currently using them to produce forest cover change products. These products will be validated comprehensively, and will be used to calculate land cover and forest change rates for different countries and critical ecosystems and biomes. First derived using a wall-to-wall mapping approach at Landsat resolutions, these estimates will be compared with estimates derived using other means, including those published by the Food and Agriculture Organization (FAO).
Presentation Type: Poster
Session: Global Change Impact & Vulnerability
(Tue 11:30 AM)
Associated Project(s):
Poster Location ID: 212
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