Automated mapping of tropical deforestation and forest degradation: CLASlite

被引:216
作者
Asner, Gregory P. [1 ]
Knapp, David E. [1 ]
Balaji, Aravindh [1 ]
Paez-Acosta, Guayana [1 ]
机构
[1] Carnegie Inst Sci, Dept Global Ecol, Stanford, CA 94305 USA
来源
JOURNAL OF APPLIED REMOTE SENSING | 2009年 / 3卷
关键词
ALI; ASTER; deforestation; forest degradation; forest disturbance; Landsat; logging; MODIS; REDD; satellite monitoring; SPOT; UNFCCC; CANOPY DAMAGE; LOGGED FORESTS; TREE COVER; VEGETATION; RECOVERY; DISCRIMINATION; FEEDBACKS; SOILS; LEAF;
D O I
10.1117/1.3223675
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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 km(2), 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 Earth (TM), 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.
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页数:24
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