Impervious Surface Information Extracting Approach Using Landsat TM Remote Sensing Image

In this paper, we present a new approach to improve extracting accuracy of impervious surfaces. One Landsat TM image of Taiyuan city, Shanxi Province of China was used. After doing test work and analyzing using optimum bands analysis, principal component analysis, and normalized difference impervious surface index, we present the method, optimized band combination. Both unsupervised and supervised classification methods were used to classify the original image, principal component analysis image, normalized difference impervious surface index image, and optimized band combination images we present. The accuracies result of these classifications were assessed by using 256 randomly selected sampling points, and it was found that the overall accuracy the accuracy of optimized band combination method can be reach 87.72%, with the Kappa statistic of 0.85 in impervious surface extraction, it was better than other three methods can get.