This paper is focused on the method for extracting glacier area based on ENVISAT ASAR Wide Swath Modes （WSM） data and digital elevation model （DEM） data, using support vector machines （SVM） classification method. The digitized result of the glaci- er coverage area in the western Qilian Mountains was extracted based on Enhanced LandSat Thematic Mapper （ETM＋） imagery, which was used to validate the precision of glacier extraction result. Because of similar backscattering of glacier, shadow and wa- ter, precision of the glacier coverage area extracted from single-polarization WSM data using SVM was only 35.4%. Then, texture features were extracted by the grey level co-occurrence matrix （GLCM）, with extracted glacier coverage area based on WSM data and texture feature information. Compared with the result extracted from WSM data, the precision improved 13.2%. However, the glacier was still seriously confused with shadow and water. Finally, DEM data was introduced to extract the glacier coverage area. Water and glacier can be differentiated because their distribution area has different elevations; shadow can be removed from the classification result based on simulated shadow imagery created by DEM data and SAR imaging parameters; finally, the glacier coverage area was extracted and the precision reached to 90.2%. Thus, it can be demonstrated that the glacier can be accurately semi-automatically extracted from SAR with this method. The method is suitable not only for ENVISAT ASAR WSM imagery, but also for other satellite SAR imagery, especially for SAR imagery covering mountainous areas.
In a mountainous region, the glacier area and length extracted form the satellite imagery data is the projected area and length of the land surface, which can’t be representative of the reality; there are always some errors. In this paper, the methods of calculating glacier area and length calculation were put forward based on satellite imagery data and a digital elevation model (DEM). The pure pixels and the mixed pixels were extracted based on the linear spectral un-mixing approach, the slop of the pixels was calculated based on the DEM, then the area calculation method was presented. The projection length was obtained from the satellite imagery data, and the elevation differences was calculated from the DEM. The length calculation method was presented based on the Pythagorean theorem. For a glacier in the study area of western Qilian Mountain, northwestern China, the projected area and length were 140.93 km2 and 30.82 km, respectively. This compares with the results calculated by the methods in this paper, which were 155.16 km2 and 32.11 km respectively, a relative error of the projected area and length extracted from the LandSat Thematic Mapper (TM) image directly reach to -9.2 percent and -4.0 percent, respectively. The calculation method is more in accord with the practicality and can provide reference for some other object’s area and length monitoring in a mountainous region.
