Time-series InSAR-based landslide identification and monitoring in the hilly areas of the northern Qinling Mountains

Yayu Cheng; Jifeng Wu

doi:10.1117/12.3007519

30 August 2023 Time-series InSAR-based landslide identification and monitoring in the hilly areas of the northern Qinling Mountains

Yayu Cheng, Jifeng Wu

Author Affiliations +

Proceedings Volume 12797, Second International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023); 127970J (2023) https://doi.org/10.1117/12.3007519
Event: 2nd International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023), 2023, Qingdao, China

Abstract

In this paper, we selected Sentinel-1 uplinked SAR images of the hilly area in the northern Qinling Mountains and obtained the time-series deformation information of the area based on SBAS-InSAR technology. the monitoring results of InSAR technology showed that the deformation of surface slopes can be used as the prerequisite data for landslide identification, and then combined with optical remote sensing image interpretation, aerial survey data of UAV and field survey to identify potential landslides. Thirty-four landslides were successfully identified and the typical landslide deformation was analyzed. Based on SBAS-InSAR technology, the maximum annual average deformation rate of -20mm/y in the line of sight direction and -30mm/y in the slope direction was observed in the hilly areas of the northern Qinling Mountains, and the potential landslides in the territory are mainly located in the slope areas of the mounded deposits, where the pore space is more developed, the slopes are exposed bedrock, and the vegetation cover and growth are poor, which provide the material basis for landslide development. -30° range and slope direction eastward and southeastward provide the advantageous topographic conditions for landslide development. The uneven distribution of rainfall in time has a serious impact on landslide deformation. The results of the study can be used as the basis for the subsequent regional geological risk evaluation and risk zone delineation, and provide scientific reference for the key monitoring of landslides close to water systems and faults.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

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Yayu Cheng and Jifeng Wu "Time-series InSAR-based landslide identification and monitoring in the hilly areas of the northern Qinling Mountains", Proc. SPIE 12797, Second International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023), 127970J (30 August 2023); https://doi.org/10.1117/12.3007519

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KEYWORDS

Deformation

Rain

Interferometric synthetic aperture radar

Vegetation

Remote sensing

Hazard analysis

Image processing

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