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Journal of Applied Remote Sensing

Automated mapping of tropical deforestation and forest degradation: CLASlite
Author(s): Gregory Paul Asner; David E. Knapp; Aravindh Balaji; Guayana Paez-Acosta
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Paper Abstract

Monitoring deforestation and forest degradation is central to assessing changes in carbon storage, biodiversity, and many other ecological processes in tropical regions. Satellite remote sensing is the most accurate and cost-effective way to monitor changes in forest cover and degradation over large geographic areas, but the tools and methods have been highly manual and time consuming, often requiring expert knowledge. We present a new user-friendly, fully automated system called CLASlite, which provides desktop mapping of forest cover, deforestation and forest disturbance using advanced atmospheric correction and spectral signal processing approaches with Landsat, SPOT, and many other satellite sensors. CLASlite runs on a standard Windows-based computer, and can map more than 10,000 km2, at 30 m spatial resolution, of forest area per hour of processing time. Outputs from CLASlite include maps of the percentage of live and dead vegetation cover, bare soils and other substrates, along with quantitative measures of uncertainty in each image pixel. These maps are then interpreted in terms of forest cover, deforestation and forest disturbance using automated decision trees. CLASlite output images can be directly input to other remote sensing programs, geographic information systems (GIS), Google EarthTM serif}, or other visualization systems. Here we provide a detailed description of the CLASlite approach with example results for deforestation and forest degradation scenarios in Brazil, Peru, and other tropical forest sites worldwide.

Paper Details

Date Published: 1 August 2009
PDF: 24 pages
J. Appl. Remote Sens. 3(1) 033543 doi: 10.1117/1.3223675
Published in: Journal of Applied Remote Sensing Volume 3, Issue 1
Show Author Affiliations
Gregory Paul Asner, Stanford Univ. (United States)
David E. Knapp, Stanford Univ. (United States)
Aravindh Balaji, Stanford Univ. (United States)
Guayana Paez-Acosta, Stanford Univ. (United States)


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