AN APPROACH TO THE EXTRACTION OF REMOTELY-SENSED INFORMATION OF
FOREST COVERAGE BASED ON PCA/NDVI
DENG Shu-bin 1, WU Hong-gan 2, JIANG Tao 1
1.Shandong University of Science and Technology, Qingdao 266510, China；2.Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing 100091, China
With the Daxinganling area as the experimental site, the authors used the PCA (Principal Components Analysis) to get the first weight and the results of the NDVI (Normalized Difference Vegetation Index), and employed a certain band in the LandSat TM1 to 7 to realize the combination of the wave band, which could enhance the contrast between the forest information and the background information. The study also used the method of maximum likelihood to realize the supervised classification of the images, whose accuracy could exceed 92%. This paper presents two experimental investigation images with different quantities of cloud and different extents of forest coverage. This investigation shows that this method can improve the automation and precision in the extraction of the forest coverage information.
邓书斌, 武红敢, 江涛. 基于PCA/NDVI的森林覆盖遥感信息提取方法研究[J]. 国土资源遥感, 2007, 19(2): 82-85.
DENG Shu-Bin, WU Hong-Gan, JIANG Tao. AN APPROACH TO THE EXTRACTION OF REMOTELY-SENSED INFORMATION OF
FOREST COVERAGE BASED ON PCA/NDVI. REMOTE SENSING FOR LAND & RESOURCES, 2007, 19(2): 82-85.
2007, Vol. 19 
