Method for assessing landslide susceptibility of highways in mountainous areas based on optical and SAR remote sensing images

doi:10.6046/zrzyyg.2022320

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Abstract

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.

Keywords landslide susceptibility assessment optical remote sensing SAR mountain highway random forest

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TP79

Issue Date: 21 December 2023

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	Shaohuai YU
	Qiao XU
	Fei YU

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Shaohuai YU,Qiao XU,Fei YU. Method for assessing landslide susceptibility of highways in mountainous areas based on optical and SAR remote sensing images[J]. Remote Sensing for Natural Resources, 2023, 35(4): 81-89.

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https://www.gtzyyg.com/EN/10.6046/zrzyyg.2022320 OR https://www.gtzyyg.com/EN/Y2023/V35/I4/81

Tab.1 Landslide susceptibility assessment factor table

Fig.1 Schematic diagram of random forest model construction

Fig.2 SABS-InSAR processing flow chart

Tab.2 Landslide susceptibility risk level update table

Fig.3 Schematic diagram of the scope and topography of the study area

Fig.4 Remote sensing interpretation map of historical landslides in the study area

Tab.3 Sentinel-1A image information table

Fig.5 Distribution map of deformation rate along the radar line of sight in the study area from 2018 to 2020

Fig.6 Distribution map of deformation rate along the slope in the study area from 2018 to 2020

Fig.7 Landslide susceptibility initial assessment zoning map in the study area

Fig.8 Landslide susceptibility evaluation zoning map in the study area

Fig.9 Comparative analysis chart of landslide susceptibility risk levels in local key areas

Tab.4 Landslide susceptibility evaluation accuracy statistics table

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