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The monitoring of landscape changes can lead to the identification of environmental hot spots, improve process understanding, and provide means for law enforcement. Digital elevation models (DEMs) derived from stereoscopic satellite data provide a systematic synoptic framework that is potentially useful to support these issues. Along-track high-resolution stereoscopic data, provided with rational polynomial coefficients (RPCs), are ideal for the fast and accurate extraction of DEMs due to the reduced radiometric differences between images. In this letter, we assess the suitability of data from the relatively new Cartosat-1 satellite to quantify large-scale geomorphological changes, using the volume estimation of the 2007 Salna landslide in the Indian Himalayas as a test case. The depletion and accumulation volumes, estimated as 0.55 × 106 and 1.43 × 106 m3, respectively, showed a good match with the volumes calculated using DEMs generated only with RPCs and without ground control points (GCPs), indicating that the volume figures are less sensitive to GCP support. The result showed that these data can provide an important input for disaster-management activities.