Identification of potential landslides in complex mountainous areas using combine ALOS-2 and Sentinel-1 data

doi:10.13474/j.cnki.11-2246.2026.0111

Abstract

Abstract: Landslide disasters are a severe natural hazard,posing significant threats to human life,property safety,and the ecological environment.The identification of potential landslides using a single SAR dataset often fails to adequately address the trade-off between spatial resolution and temporal resolution.This study integrates the strong penetration capability of ALOS-2 data in areas with moderate vegetation cover and the high temporal resolution of Sentinel-1 data to identify potential landslide hazards.Taking a complex vegetated mountainous region in Guizhou as a case study,the SBAS-InSAR technique is applied for experimentation.The results indicate that the surface deformation rates in the study area ranged from -125.34 to 46.01 mm/a for ALOS-2 data and from -159.42 to 124.44 mm/a for Sentinel-1 data.A total of 48 new landslide hazards are identified,with the complementary strengths of the two datasets significantly enhancing the spatial coverage and applicability of landslide identification.This study provides technical support for the early detection of landslide hazards and disaster prevention and mitigation efforts.

Key words: landslide disasters, fractional vegetation cover, SBAS-InSAR, complex vegetated mountainous areas

CLC Number:

P237

CAO Ruihan, LI Xin, ZHOU Dingjie, XI Wenfei, HUANG Guangcai, WANG Ruiting, GUO Zhen. Identification of potential landslides in complex mountainous areas using combine ALOS-2 and Sentinel-1 data[J]. Bulletin of Surveying and Mapping, 2026, 0(1): 65-71.

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