研究目的
To develop and apply a new method for mapping two-dimensional deformation field time-series of large slopes by coupling DInSAR-SBAS with MAI-SBAS to overcome the limitations of conventional DInSAR in detecting north-south displacements.
研究成果
The proposed method effectively maps and quantifies landslide displacement fields, with validation showing RMSE of ±0.95 cm for vertical and ±10.5 cm for north-south displacements. It is suitable for monitoring large-scale slopes, particularly in north-south directions, but future work should integrate additional techniques for east-west measurements.
研究不足
The method is sensitive to displacements in vertical and north-south directions but cannot measure east-west displacements accurately. It requires improvements in offset-tracking based SBAS for comprehensive 3D deformation monitoring.
1:Experimental Design and Method Selection:
The study uses a combination of DInSAR-SBAS and MAI-SBAS techniques to process SAR data for landslide monitoring. DInSAR-SBAS involves generating differential interferograms with small baselines and using SVD for time series inversion, while MAI-SBAS involves azimuth band splitting and interferometry to measure along-track displacements.
2:Sample Selection and Data Sources:
11 L-band ALOS PALSAR SAR images from 2007 to 2011 of the Fushun west open-pit mine in China are used. GPS data from two stations (CP01 and CP02) are used for validation.
3:List of Experimental Equipment and Materials:
SAR data from ALOS PALSAR sensor, GPS receivers, SRTM-3 DEM, GAMMA software for data processing, GAMIT/GLOBK software for GPS data processing.
4:Experimental Procedures and Operational Workflow:
Data processing includes image pair selection with baseline thresholds, coregistration, interferogram generation, phase unwrapping using 3D MCF algorithm, error correction for topographic and atmospheric effects, and inversion using SBAS to obtain displacement time series.
5:Data Analysis Methods:
Displacement results are compared with GPS measurements using root mean square error (RMSE) analysis, and optical satellite images are used for additional validation.
独家科研数据包,助您复现前沿成果,加速创新突破
获取完整内容