DInSAR for a Regional Inventory of Active Rock Glaciers in the Dry Andes Mountains of Argentina and Chile with Sentinel-1 Data

• Published in: Remote Sensing
• Main Authors: Cristian Villarroel, Guillermo Tamburini Beliveau, Ana Forte, Oriol Monserrat, Monica Morvillo
• Format: Text
• Language: English
• Published: Multidisciplinary Digital Publishing Institute 2018
• Subjects: DInSAR; Sentinel 1; rock glacier inventories; mountain permafrost; Dry Andes; Argentina; The Sentinel; permafrost
• Online Access: https://doi.org/10.3390/rs10101588

The Dry Andes region of Argentina and Chile is characterized by a highly developed periglacial environment. In these arid or semi-arid regions, rock glaciers represent one of the main pieces of evidence of mountain creeping permafrost and water reserves in a solid state. However, their distribution, degree of activity, and response to global warming are not yet well understood. In this context, this work aims to show the potential of the Sentinel-1-based interferometric technique (DInSAR) to map active rock glaciers at a regional level. In particular, the paper presents an active rock glacier inventory for the study area, which covers approximately 40,000 km2, ranging from latitude 30°21′S to 33°21′S. A total of 2116 active rock glaciers have been detected, and their elevations show a high correlation with the west-east direction. This result was obtained by using only 16 interferometric pairs. Compared to other remote sensing classification techniques, the interferometric technique offers a means to measure surface displacement (active rock glacier). This results in a reliable classification of the degree of activity compared to other methods, based on geomorphological, geomorphometric, and/or ecological criteria. This work presents evidence of this aspect by comparing the obtained results with existing optical data-based inventories. We conclude that the combination of both types of sensors (radar and optical) is an appropriate procedure for active rock glacier inventories, as both mapping methodologies are complementary.