Extraction of urban impervious surface information from TM image
LI Weina1,2, YANG Jiansheng3, LI Xiao1,2, ZHANG Jilong2,4, LI Shiwei1,2
1. School of Information and Communication Engineering, North University of China, Taiyuan 030051, China;
2. Opto-Electronic Information and Instrument Engineering Technology Research Center of Shanxi Province, North University of China, Taiyuan 030051, China;
3. Department of Geography Ball State University Muncie, IN 47036, USA;
4. Key Laboratory of Instrumentation Science & Dynamic Measurement of Ministry of Education, North University of China, Taiyuan 030051, China
Based on analyzing the theory of the Optimum Band Combination, Principal Component Analysis (PCA) and NDISI, this paper presents an improved method, i.e., "experimental layer stack", to extract impervious surface of Taiyuan city, Shanxi Province, from Landsat TM image. Both unsupervised and supervised classification methods were used to classify the original multi-band image, PCA image, NDISI and experimental band combination images. The accuracies of the classification were assessed using 256 sampling points randomly selected from Google Earth high resolution image of Taiyuan. By comparison and analysis, the authors found that the experimental B combination method obtained the highest overall accuracy of 87.72% with the Kappa coefficient of 0.85.
李玮娜, 杨建生, 李晓, 张记龙, 李世伟. 基于TM图像的城市不透水面信息提取[J]. 国土资源遥感, 2013, 25(1): 66-70.
LI Weina, YANG Jiansheng, LI Xiao, ZHANG Jilong, LI Shiwei. Extraction of urban impervious surface information from TM image. REMOTE SENSING FOR LAND & RESOURCES, 2013, 25(1): 66-70.
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2013, Vol. 25 
