Abstract
ABSTRACT Rock glaciers are typical periglacial landforms with tongue or lobate morphological shapes and characterized by the distinct front, lateral margins, and often by ridge-and-furrow surface topography textures as well as kinematic characteristics, widely distributed in alpine environments. Multitemporal Synthetic aperture radar interferometry (MT-InSAR), is a remote sensing technique with demonstrated effectiveness for detecting landform kinematics. However, its application to rock glaciers is challenged by temporal decorrelation and atmospheric phase noises due to complex topography and snow cover. We designed a quadtree segmentation and parallel computing-based MT-InSAR method to improve the quality and efficiency of deformation measurement of rock glaciers. We applied the method to a rock glacier inventory of the Nyainqêntanglha Range, China, derived from high-resolution Gaofen-2 images, to quantify the activity rate of each rock glacier. Results showed that 32.1% (6,389) of the identified rock glaciers exhibited slope-parallel deformation rates exceeding 100 mm/y. The activities of the rock glaciers exhibited strong correlations with their distance to glaciers, precipitation, freeze–thaw magnitude, and permafrost occurrence probability. The results demonstrate the effectiveness of the developed segmentation-parallel MT-InSAR method for monitoring rock glacier deformation over a large region.
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