Identification of landslide hazards based on multi-source remote sensing technology:A case study of the Changli area in Hunan Province

doi:10.6046/zrzyyg.2023008

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Abstract

Due to the intricate geographical and geological environment, the mountainous-hilly area of Changli in northern Hunan Province is challenged by numerous, widespread, scattered, and frequent landslide hazards, which constitute the most significant geologic hazard that causes casualties and economic losses. The multi-source remote sensing technology integrating InSAR, optical remote sensing, LiDAR, and GIS is currently a high-feasibility and high-precision landslide hazard identification and monitoring technology, meeting the requirements for macroscale and timeliness. This study identified and extracted landslide hazards in the Changli area based on InSAR deformation rate data, multispectral images, and DEM data. First, two decision tree classification methods were employed to classify the land use types based on multispectral images, facilitating the observation of land use types and their distributions in the Changli area. Then, five topographic factors, including elevation, slope, aspect, undulation, and curvature, were extracted from DEM data to evaluate the landslide risk in the Changli area. Then, five topographic factors, such as elevation, slope, aspect, undulation and curvature, are extracted from DEM data to evaluate the landslide risk in the study area. Furthermore, the time-series surface microdeformation of the Changli area was measured based on SBAS-InSAR technology. Finally, landslide hazards were extracted and delineated in the GIS by combining risk assessment results and deformation rates. Additionally, based on the classification and regression tree (CART) results and the river system distribution in the Changli area, risk inference was conducted on zones with deformation rates exceeding -0.01 m/a except the delineated landslide hazard sites. This study identified several small-scale landslide hazards with high concealment in vegetation-covered and bare zones, delineating their spatial distribution ranges, which covered an area of 0.126 km². The multi-source remote sensing technology proved effective, demonstrating certain practical application value.

Keywords landslide hazard DEM data decision tree classification SBAS-InSAR Changli area in Hunan

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Issue Date: 14 June 2024

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	Lijun ZHANG
	Sirui HE
	Jiandong ZHANG
	Guangxiong PENG
	Zhibin XU
	Jiancheng XIE
	Kai TANG
	Jiancai BU

Cite this article:

Lijun ZHANG,Sirui HE,Jiandong ZHANG, et al. Identification of landslide hazards based on multi-source remote sensing technology:A case study of the Changli area in Hunan Province[J]. Remote Sensing for Natural Resources, 2024, 36(2): 173-187.

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https://www.gtzyyg.com/EN/10.6046/zrzyyg.2023008 OR https://www.gtzyyg.com/EN/Y2024/V36/I2/173

Fig.1 Geographical and geological map of the study area

Fig.2 Schematic diagram of research technical route

Tab.1 List of normalized index formulas

Fig.3 Decision tree classification rule diagram

Fig.4 Decision tree classification result

Fig.5 Slope and aspect distribution image

Fig.6 Distribution image of slope height and topographic relief

Fig.7 Distribution image of slope curvature

Fig.8 Raw data and spatial-temporal baseline chart

Fig.9 SBAS-InSAR technical flow chart

Fig.10 DEM data and InSAR deformation rate data

Fig.11 Potential landslide with visual interpretation in landslide danger area

Fig.12 Evaluation criteria for landslide risk factors

Fig.13 Location of potential landslide

Tab.2 Verification results of some potential landslide hazard

Fig.14 Comparison diagram of CART decision tree classification and deformation rate

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