REMOTE SENSING CLASSIFICATION OF SURFACE FEATURES ON THE ROIG(E) PLATEAU

All materials have their characteristic spectral absorption peaks in remote sensing data.So missing and mixing of information that usually occurred in previous remote sensing classification may be greatly reduced by spectral identification.In order to solve the problem of the remote sensing classification of surface features on the Roigü Plateau, the spectral angle mapper classification of surface features was for the first time used in the ETM multispectral pansharp images.The steps of the classification are as follows:setting the standard of remote sensing data →selecting the swatches in the training area →using the minimum noise fraction rotation (MNF) to reduce the dimension and remove noises →using the pixel purity index (PPI) to purify the swatches →using the n-D visualizer to regroup the swatches →using the spectral angle mapper (ASM) to identify surface features.The classification results are as follows:the total accuracy of the class accuracy evaluation is 0.806 and the Kappa coefficient is 0.785.These accuracies conform to the technical requirements of 1:50 000 detailed land survey.