Texture Statistics for Sichuan Basin Terrain Morphology Analysis DEM Based

Abstract

Terrain analysis is an important job for terrain classification and geomorphologic mapping in complex terrain context. When Shuttle Radar Topography Mission appeared, enormous account of data, SRTM Digital Elevation Model (abbreviated SRTM DEM), has been sent back to earth. Then automating the analysis of this data and its interpretation represents a challenging test of significant benefit. In this study, we propose combing texture statistics and classification to interpret topography data of Sichuan Basin and landform surround and to identify constituent land-forms of the Sichuan Basin landscape. Our approach used unsupervised image segmentation to divide a landform into a number of spatially extended but topographically homogeneous objects. The objects are classified into predetermined landform classes. We have applied our technique to the Sichuan Basin and mountain surround in Sichuan Province, China. The 80% mean accuracy as a result has shown our algorithm being efficiency and acceptable.