Extraction of Desertification Information Based on SMA——A Case Study in Mu Us Sandland

LI Xiao-song; WU Bo; FAN Wen-yi; WANG Gang; YANG Hong-xiao; WANG Yan

In this study,in order to accurately extract desertification information based on remote sensing data,Spectral Mixture Analysis(SMA) was conducted in a typical area of Mu Us Sandland in semiarid region by taking farmland,sands,psammophytic vegetation,water and salinized land as endmembers.A comparison was made among SMA,TC transformation and supervised classification.The accuracy on the result was validated based on field survey data and compared with NDVI method.The result suggested that SMA could be used for extracting desertification information with an obviously better output based on remote sensing data than NDVI method.

1. Research Institute of Forest Resource Information Techniques, CAF, Beijing 100091, China

2. .Research Institute of Forestry, CAF, Key Laboratory of Tree Breeding and Cultivation, Sate Forestry Administration, Beijing 100091, China

3. College of Forestry, Northeast Forestry University, Harbin 150040, Heilongjiang, China

4. Academy of Forestry Survey and Planning, Harbin 150040, Heilongjiang, China

5. The College of Life Sciences, Beijing Normal Unisviersity, Beijing 100875, China

Received Date: 2005-01-04

Abstract: In this study,in order to accurately extract desertification information based on remote sensing data,Spectral Mixture Analysis(SMA) was conducted in a typical area of Mu Us Sandland in semiarid region by taking farmland,sands,psammophytic vegetation,water and salinized land as endmembers.A comparison was made among SMA,TC transformation and supervised classification.The accuracy on the result was validated based on field survey data and compared with NDVI method.The result suggested that SMA could be used for extracting desertification information with an obviously better output based on remote sensing data than NDVI method.

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Reference (19)

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Extraction of Desertification Information Based on SMA——A Case Study in Mu Us Sandland

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