Retrieval of Ground Subsidence by Integrating GPS Observations and Persistent Scatterers INSAR and Using a Small Number of ASAR Images
Qiang Chen(1,2), Xiaoli Ding(1), Linguo Yuan(1), Guoxiang Liu(2) and Ping Zhong(1)
(1) The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China
(2) Southwest Jiaotong University, Chengdu, Sichuan, China
It is well known that persistent scatterers (PS) InSAR relies on a significant number of SAR images (typically 25 or more) covering the same area to derive reliably the deformations of the PS. This often limits the practical applications of the technique as the number of existing SAR images for a given area is often limited. One can always to wait for the images to be acquired but this means delays in getting the desired results. We propose to use all the available interferometric combinations from a given set of SAR images to increase the number of interferograms considering the fact that each interferogram generated in the combinations has its coherence that cannot be considered strictly as a linear combination of the coherence of the other interferograms. We also propose to integrate GPS observations into the PS InSAR solutions as additional constraints to enhance the InSAR results.
Eight Envisat ASAR acquisitions over Hong Kong are used in an experiment. The tropospheirc delays derived from 12 permanent GPS stations in the study area are used to correct the interferograms. A joint observation network consisting of the GPS stations and the PS points identified is then formed. A weighted least square adjustment algorithm is applied to derive the deformations of the PS points based on the network thus formed. The results show that the deformations of the PS points derived from the proposed method are accurate compared to GPS derived values.
Keywords: ESA European
Space Agency - Agence spatiale europeenne,
observation de la terre, earth observation,
satellite remote sensing,
teledetection, geophysique, altimetrie, radar,
chimique atmospherique, geophysics, altimetry, radar,