Qinghai-Tibet Plateau located in southwestern China is one of the important geomorphological units of the country's terrestrial part. Because of its high altitude, vast area, and the mid-latitude location, known as "the third pole", it has close correlation with the biggest monsoon system on the globe which has not only sensitive responding character but significant impact on the global climate change. Hence it becomes one of the hot spots of research. Specific geographical environment, unique sea level elevation and frigid climate condition of the Qinghai-Tibet Plateau make kinds of periglacial geomorphology brand into the geomorphological landscape of the Plateau. Taking the district of 1 ∶ 1,000,000 international standard of Lhasa map sheet (serial number H-46) as an example, this paper explores an information extraction method of periglacial geomorphology on the Qinghai-Tibet Plateau based on multiple source data such as remote sensing data, SRTM, air temperature and ground temperature. In the research, the primitive boundary of periglacial geomorphology is acquired by the indexes such as annual mean temperature of national standard station with a resolution of 1km, annual mean ground temperature and elevation through models. The bound is revised and synthetically processed by using the features such as color, shape and texture of remote sensing images (TM and ETM+ of Landsat). Hence the extent of periglacial geomorphology of the study area is determined. Then the morphological indexes such as relief, elevation and slope of the periglacial geomorphology in the study area are computed by using the SRTM-DEM data. Based on the features such as the completeness of geomorphological units, in virtue of geomorphological expert knowledge and the features of remote sensing images, the indexes are revised by using man-computer mutual intelligentized extraction method.At length quantificational exaction of morphological indexes of periglacial geomorphology in the study area is completed. Finally, the morphological characters of periglacial geomorphology in the study area are integrated and the semi-auto matic remote sensing interpretation result map of periglacial geomorphology in the study area and statistical attribute data are achieved. This research can accomplish remote sensing precise location of geomorphological unit boundary and exact attribute evaluation of geomorhpological types based on multiple source data, which promotes the development of extraction methods of remote sensing geomorphological information. Thus the research method can extend to other areas of the Qinghai-Tibet Plateau and is important in theory and practice.