Landslide Inventory in the Downstream of the Niulanjiang River with ALOS PALSAR and Sentinel-1 Datasets

Abstract

Landslide inventory and deformation monitoring is an essential task for human life and property security during the exploitation process of hydroelectric power resources. Synthetic Aperture Radar Interferometry (InSAR) is recognized as an effective tool for ground displacement monitoring with the advantages of wide coverage and high accuracy. In this study, we mapped the unstable slopes in the downstream of the Niulanjiang River with 22 ALOS PALSAR SAR images acquired from 2007 to 2011, and 90 Sentinel-1 SAR images from 2015 to 2019. A total of 94 active slopes are identified using a displacement map from the two datasets based on Small BAseline Subset (SBAS) InSAR analysis. By comparing the results from ALOS PALSAR and Sentinel-1 data stacks, we find that the number of active slopes increased dramatically. Several impact factors, e.g., earthquake, concentrated rainfall, and construction of hydropower stations, are discussed through time series analysis of typical landslides. Furthermore, nonlinear displacement of natural unstable slopes are found to be correlated with rainfall. A climate-driven model is used to qualify the relationship between rainfall and landslide displacement. Our results can provide valuable information for landslide detection and prevention.