HR: 14:10h
AN: B23F-03    [Abstracts]
TI: Pan-Tropical Forest Clearing, 2000-2005
AU: * Hansen, M
EM: matthew.hansen@sdstate.edu
AF: South Dakota State University, Wecota Hall, Box 506B, Brookings, SD 57007, United States
AU: Potapov, P
EM: peter.potapov@sdstate.edu
AF: South Dakota State University, Wecota Hall, Box 506B, Brookings, SD 57007, United States
AU: Pittman, K
EM: kyle.pittman@sdstate.edu
AF: South Dakota State University, Wecota Hall, Box 506B, Brookings, SD 57007, United States
AU: Loveland, T
EM: loveland@usgs.gov
AF: USGS-EROS, 47914 252nd Street, Sioux Falls, SD 57198-0001, United States
AU: Stehman, S
EM: svstehma@syr.edu
AF: State University of New York College of Environmental Science and Forestry, 322 Bray Hall One Forestry Drive, Syracuse, NY 13210-2788, United States
AB: Quantifying rates of tropical forest cover clearing allows for improved biogeochemical cycle and climate change modeling, management of forestry and agricultural resources, and biodiversity monitoring. As a result, there is a critical need to monitor forest clearing over large areas in a timely manner. While the use of satellite-based observations for monitoring tropical deforestation is well established, consistent and timely monitoring of the entire humid tropics has not been implemented and limits the effective management of this important resource. This paper presents a probability sampling approach employing multi-resolution satellite data to provide timely, synoptic estimates of humid tropical forest cover loss. Biome-wide change indicator maps were created using moderate spatial resolution imagery for 2000 to 2005 from the MODerate Resolution Imaging Spectroradiometer sensor (MODIS). A sample of 183, 18.5km by 18.5km blocks of high spatial resolution image pairs from the Landsat Enhanced Thematic Mapper Plus sensor was used to determine biome-wide area of forest clearing. The sampling strategy employed the MODIS data in the design to stratify the blocks and also in the analysis via a survey sampling regression estimator of forest clearing. This statistically rigorous sampling strategy provides a biome-level clearing estimate with known uncertainty. Forest was defined as greater than 25% canopy cover and change was measured without regard to forest land use. All tree cover assemblages that met the 25% threshold, including intact forests, plantations, and forest regrowth, were defined as forests. Forest area cleared for the biome is estimated to be 1.53% with a standard error of 0.106%. This translates to an estimated area cleared of 29.4 million hectares with a standard error of 2.1 million hectares representing a 2.54% reduction in year 2000 forest cover. Rates of clearing are on a par with those from the 1990's. Regional variation is pronounced, with 48% of forest clearing occurring in Brazil and nearly two-thirds overall in Latin America. Indonesia accounts for 12% of total biome forest cover loss and Asia as a whole one-third. Africa, while a center of widespread, low-intensity selective logging, contributes only 5% to the estimated loss of humid tropical forest cover. Nearly one-third of all clearing occurs in less than 4% of the biome area. Forest clearing as a percentage of year 2000 forest cover for Brazil (3.9%) and Indonesia (3.5%) easily outpaces the rest of Latin America (1.5%), the rest of Asia (2.7%) and Africa (0.7%).
DE: 0410 Biodiversity
DE: 0480 Remote sensing
SC: Biogeosciences [B]
MN: 2007 Fall Meeting