Literature DB >> 15736876

Mapping tropical deforestation in Central Africa.

Quanfa Zhang1, Didier Devers, Arthur Desch, Christopher O Justice, John Townshend.   

Abstract

The NASA Landsat Pathfinder Humid Tropical Deforestation Project was to map deforestation activities in the humid tropics using datasets from both the Landsat TM (Thematic Mapper) and MSS (Multispectral Scanner System). In Central Africa, its effort had been constrained by the availability of cloud-free satellite coverage, especially for the 1970s Landsat MSS imagery. Here, we reported the deforestation rate and its spatial variability in the region using 18 pairs of co-registered Landsat TM imagery from the 1980s to 1990s. Of the total classified area of 416,000 km2, there were approximately 217,000 km2 of dense forest and 24,000 km2 of degraded forest in the 1980s. A total of 1012 km2 of forest, including 542 km2 of dense forest and 470 km2 of degraded forest, were cleared annually with an annual deforestation rate of 0.42%, varying among scenes ranging from 0.03 to 2.72%. Additionally, an average of 0.12% (ranging from 0.01 to 0.77% among scenes) or 257 km2 of dense forest was degraded annually. Regression analyses indicated that extensive deforestation occurred in areas with larger forest cover, including dense and degraded forests. Image interpretation also confirmed the hypothesized relationship between deforestation and forest accessibility. The annual clearance of the dense forest was significantly related to the rural population density, and there was a positive relationship between the dense forest degraded during the 1980s-1990s and the degraded forest area in the 1980s.

Mesh:

Year:  2005        PMID: 15736876     DOI: 10.1007/s10661-005-9132-2

Source DB:  PubMed          Journal:  Environ Monit Assess        ISSN: 0167-6369            Impact factor:   2.513


  3 in total

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Journal:  Proc Natl Acad Sci U S A       Date:  2002-10-16       Impact factor: 11.205

  3 in total
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10.  Forest Cover Estimation in Ireland Using Radar Remote Sensing: A Comparative Analysis of Forest Cover Assessment Methodologies.

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