Abstract

The time-series interferometric synthetic aperture radar (InSAR) techniques has the potential of estimating the land subsidence at a high accuracy of nearly in millimeter scale. The major limitation of the present InSAR methods like persistent scatterer interferometry (PSI) is that they measure land deformation velocities only in the direction of the radar line of sight (LOS). Hence, the real prospects of the deformation velocity, i.e. the horizontal and vertical components of velocity remain uncertain. This study is focusing on retrieving PSI based multi-dimensional land deformation velocity along horizontal and vertical directions in an urban region by using ascending and descending pass Sentinel-1 datasets. The area for this study is Lucknow city in Uttar Pradesh state of India. The estimated LOS velocity vectors from ascending and descending pass time-series datasets are utilized for retrieving multidimensional subsidence velocity. Further, the retrieved time-series land subsidence is correlated to the groundwater level variation during the considered time span.

摘要

时间序列干涉合成孔径雷达 (InSAR) 技术具有以接近毫米级的高精度估计地面沉降的潜力。目前 InSAR 方法（如持续散射体干涉测量法 (PSI)）的主要限制是它们仅在雷达视线 (LOS) 方向测量土地变形速度。因此，变形速度的真实前景，即速度的水平和垂直分量仍然不确定。本研究的重点是通过使用上升和下降通道 Sentinel-1 数据集来检索城市区域沿水平和垂直方向的基于 PSI 的多维土地变形速度。本研究的区域是印度北方邦的勒克瑙市。从上升和下降通过时间序列数据集中估计的 LOS 速度向量用于检索多维沉降速度。此外，检索到的时间序列地面沉降与所考虑时间跨度内的地下水位变化相关。