Landslide sensitivity assessment and error correction based on InSAR and random forest method

doi:10.13474/j.cnki.11-2246.2022.0288

Abstract

Abstract: Landslides not only affect the sustainable development of the social economy but also threaten the safety of human life. A landslide sensitivity map (LSM) is considered to be one of the effective means to predict the spatial location of landslides, but the LSM generated by existing methods is affected by false negative errors, so it is difficult to obtain reliable prediction results. This paper proposes an improved LSM method based on InSAR deformation results to solve this problem. The experimental results in Zhouqu county, Gansu province show that the landslide sensitivity grade within the study area has increased by 2.74%. The comparison results between the original LSM and the improved LSM in two specific regions show that the improved method can make a more reliable landslide sensitivity map in the area affected by landslide creep.

Key words: random forest, SBAS-InSAR, landslide sensitivity, false-negative error

CLC Number:

P237

HUANG Long, SUN Qian, HU Jun. Landslide sensitivity assessment and error correction based on InSAR and random forest method[J]. Bulletin of Surveying and Mapping, 2022, 0(10): 13-20.

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