基于DEM和遥感技术的绥德县黄土崩滑危险区段识别及易发性评价

doi:10.19388/j.zgdzdc.2024.114

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Abstract Suide County is located in the hinterland of the Loess Plateau in northern Shaanxi, with great loess fluctuation and intense human activity, which leads to the development of collapse and landslide disasters and seriously threatens the safety of local people's lives and properties. Suide County was taken as the study area to identify the prone and dangerous sections of loess collapse and landslide using high-precision Digital Elevation Model (DEM) (2 m×2 m) and high-resolution remote sensing images (0.2 m). A comprehensive identification and verification of loess collapse and landslide was conducted in the study area, and an information quantity model was used to construct the evaluation of loess collapse and landslide susceptibility based on the verified hidden danger point data. The results showed that 3 529 dangerous sections with threatening objects were identified based on DEM and remote sensing technology, and 3 116 hidden danger points of loess collapse and landslide were confirmed through field verification, with an accuracy rate of 88.30%. The study area has an extremely high susceptible area of 131.32 km², a high susceptible area of 275.35 km², and a moderately susceptible area of 335.74 km², those three mainly distributed in steep slopes, high slopes, and slopes with strong human engineering activities in sheets along the loess ridge and hill area. Besides, 75.80% of the hidden dangers of loess collapse and landslide is distributed in extremely high, high, and medium susceptible areas, and the susceptibility evaluation results are reliable. The research results have further improved the precise identification ability of loess collapse and landslide in Suide County, and the evaluation results could provide the basis for disaster prevention and reduction work and national spatial planning in Suide County, which have certain reference significance for the precise identification of loess collapse and landslide in other similar geological environment areas.

Key words： DEM remote sensing hidden dangers identification of loess collapse and landslide susceptibility evaluation Suide County

Received: 11 January 2024

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	WANG Shibao
	LI Chenglong
	WANG Na

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WANG Shibao,LI Chenglong,WANG Na. Identification and susceptibility evaluation of loess collapse and landslide risk zones in Suide County based on DEM and remote sensing technology[J]. , 2024, 11(6): 93-99.

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http://journal25.magtechjournal.com/Jwk_dzdc/EN/10.19388/j.zgdzdc.2024.114 OR http://journal25.magtechjournal.com/Jwk_dzdc/EN/Y2024/V11/I6/93

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