Assessing the landslide susceptibility of highways in precarious mountainous areas can provide crucial information for the geologic route selection of highways. Conventional landslide susceptibility assessment methods ignore the application of surface deformation data and other dynamic data, leading to low-accuracy assessment results. Hence, this study proposed a landslide susceptibility assessment method for mountain highways based on optical and SAR remote sensing images. With the Longwuxia-Gongboxia section of the Yanhuang Highway in Qinghai Province as the study area, this study extracted various static factors of landslides from high-resolution QuickBird satellite images and calculated the initial risk level of landslide susceptibility within the route area using a random forest model. Afterward, this study obtained the surface deformation factors, which directly reflect the dynamic changes of landslides, based on the long-time-series Sentinel-1A images. Finally, this study corrected the initial landslide susceptibility risk level based on the surface deformation factors, generating a landslide susceptibility assessment zoning map. As demonstrated by engineering practice, the method proposed in this study yielded a high-accuracy landslide susceptibility assessment zoning map for the mountain highway by combining data on both static and dynamic factors of landslides, thus providing accurate information for subsequent geologic route selection of the highway.
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2023, Vol. 35 
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