InSAR-Based Landslide Location and Monitoring in Alpine Valley Region

Wang, Guijie; Yin, Yueping; Wu, Weilun

doi:10.1007/978-3-319-05050-8_59

Cited by 2 publications

(2 citation statements)

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“…It is determined by the incidence and azimuth angles of the satellite as well as the slope and aspect of each ground point. [47][48][49] A geometric sketch of GLIA is shown in Fig. 5, where θ is the incident angle, which is the angle between the radar wave propagation vector and the vertical direction, ∂ is the local slope angle of the ground point, and θ loc is the GLIA.…”

Section: Ground Local Incidence Angle and Its Calculation Modelmentioning

confidence: 99%

“…Notti et al 47 used various persistent scatterer interferometry techniques to map and monitor landslides in various mountainous environments to improve the extraction density of permanent scatterer. Wang et al 48 and Xie et al 49 also carried out studies on the location and monitoring of landslides in alpine canyon areas by applying InSAR technology.…”

Section: Introductionmentioning

confidence: 99%

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Locating and monitoring of landslides based on small baseline subset interferometric synthetic aperture radar

Wang

Zang

et al. 2019

J. Appl. Rem. Sens.

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Due to the effects of rugged terrain and vegetation cover, improving the locating and monitoring accuracy of time series interferometric synthetic aperture radar (TS-InSAR) in detecting the development of landslides in mountainous and valley areas has become a problem that needs to be solved. Our study uses the ground local incident angle (GLIA) to locate noneffective monitoring areas that are affected by steep terrain as well as to improve the locating accuracy of TS-InSAR technology in the effective coverage area. At the same time, the improved small baseline subset InSAR (SBAS-InSAR) method is used to improve the density of interferometer targets as well as to solve the problem of insufficient permanent scatterers due to the effects of vegetation coverage. A geometric model of GLIA was established. Ascending and descending synthetic aperture radar (SAR) data from the Advanced Land Observation Satellite (ALOS) were used for calculating the value of GLIA. The relationships of the GLIA and the interference characteristics of InSAR data were analyzed, and the locations of noneffective areas were determined. Finally, 19 ascending pass SAR data scenes acquired by the ALOS-1 satellite were processed through using the improved SBAS-InSAR method, and the detailed time series moving displacement information from 2007 to 2011 was mapped in Wudongde hydropower reservoir. Furthermore, the potentially moving landslide areas and landslide hazard areas were located in the effective interference areas. The active Jinpingzi landslide was investigated in detail, and the single-point monitoring results of SBAS-InSAR were compared with the electronic total station (ETS) measurement results. The conclusion shows that the monitoring results of SBAS-InSAR were in agreement with the ground field survey and the single-point ETS monitoring, and the applicability of the model and algorithm proposed was proved. Our study provides a reference for the early identification and high-precision monitoring of landslides in mountainous and valley areas. © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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Section: Ground Local Incidence Angle and Its Calculation Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%