SBAS-InSAR-based long time-series deformation monitoring and landslide hazard identification in the Baihetan reservoir area

doi:10.6046/zrzyyg.2024370

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Abstract

The reservoir area of the Baihetan hydropower station (also referred to as the Baihetan reservoir area) suffers from frequent geologic hazards. However, there is a lack of monitoring studies on the central area and lower reaches of the hydropower station. Based on the ascending and descending synthetic aperture Radar (SAR) images from the Sentinel-1A satellite, this study performed deformation monitoring and landslide hazard identification in the Baishitan-Yezhutang section of the Baihetan reservoir area using the small baseline subset-interferometric synthetic aperture Radar (SBAS-InSAR) method supported by the generic atmospheric correction online service for InSAR (GACOS). Moreover, this study conducted cross-validation of deformation data from ascending and descending SAR images for low-slope zones. It investigated the spatial distribution of landslide hazards and the movement patterns of typical hazard sites in the study area. Finally, it examined the impacts of factors influencing geologic hazards on the distribution of these hazard sites. The results indicate that the deformation data from ascending and descending SAR images for low-slope zones can be used for cross-validation. Based on the deformation detection results from time-series InSAR and the optical images from Google Earth, 16 landslide hazards were identified, including 14 slow-moving landslides and two significant deformation hazards induced by human engineering activities. Integrating the data of ascending and descending SAR images validated the reliability of deformation results and also enhanced the effectiveness of landslide hazard identification. The analysis of the movement patterns at typical hazard sites indicates a correlation between deformation acceleration and seasonal rainfall. The statistical analysis of factors influencing geologic hazards in the study area reveals that the formation of hazard sites is driven by multiple factors, with varying dominant factors and degrees of influence across different hazards.

Keywords Baihetan hydropower station SBAS-InSAR deformation monitoring hazard identification factors influencing geologic hazards

ZTFLH:	TP79
	P237

Issue Date: 31 December 2025

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	Bing YU
	Chunyu ZHANG
	Jinri WANG
	Guoxiang LIU
	Keren DAI
	Deying MA

Cite this article:

Bing YU,Chunyu ZHANG,Jinri WANG, et al. SBAS-InSAR-based long time-series deformation monitoring and landslide hazard identification in the Baihetan reservoir area[J]. Remote Sensing for Natural Resources, 2025, 37(6): 156-168.

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https://www.gtzyyg.com/EN/10.6046/zrzyyg.2024370 OR https://www.gtzyyg.com/EN/Y2025/V37/I6/156

Fig.1 Location and SAR data coverage of the study area

Fig.2 Geological map of the study area

Tab.1 Main parameters of Sentinel-1A data

Fig.3 Comparison of differential interferograms before and after GACOS atmospheric delay correction

Fig.4 Interfering pairs connectivity

Fig.5 Line-of-sight deformation rate results of the study area

Fig.6 Cross-validation of ascending and descending deformation rates

Fig.7 Result of hidden hazard points

Tab.2 Detailed information of potential hazards

Fig.8 Potential landslide deformation characteristics of Feiwo

Fig.9 Potential landslide deformation characteristics of Miansha Village

Fig.10 Potential landslide deformation characteristics of Liucheng village

Fig.11 Potential landslide deformation characteristics of Banpo

Fig.12 Influencing factors of hidden hazards

Fig.13 Relationship between geological hazards and influencing factors

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