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

Abstract

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.

Monitoring, Prediction, and Evaluation of Mountain Geological Hazards Based on InSAR Technology

“…Short baseline subset method is proposed by Berardino et al on the basis of previous research results. When using this technology to generate interferogram, it requires short spatiotemporal baseline interference pairs, which can effectively reduce temporal decoherence and spatial decoherence [14].…”

Identifying Potential Landslides by Stacking-InSAR in Southwestern China and Its Performance Comparison with SBAS-InSAR

“…The time series InSAR (TS-InSAR) method (e.g., Persistent Scatterer InSAR (PS-InSAR) [15], Small Baselines Subset InSAR (SBAS-InSAR) [16], and Interferometric Point target Analysis (IPTA) [17]) overcome the technical problems of low coherence and atmospheric delay, and have been successfully used in monitoring landslide displacement [18][19][20][21][22][23][24][25][26][27][28][29] and identifying potential landslides [30][31][32]. However, the conventional TS-InSAR algorithms are relatively time-consuming and labor-intensive, especially for the upcoming massive multi-orbit multi-type SAR data.…”

Testing Polygon for Simulated Vertical Displacement Measurements based on Co-located InSAR Corner Reflector and GNSS Station

“…Satellite Synthetic Aperture Radar (SAR) interferometry (InSAR) is an established technology used to monitor deformations of large areas [16] or infrastructure [17]. Interferometry data processing requires the processing of at least two images.…”