Determining land subsidence in western Taiwan by using a new approach of weighting PS-InSAR with redundant observations

Jun Fu Ye, Jaan-Rong Tsay

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Since the emerging of the technique of persistent scatterer interferometric synthetic aperture radar (PS-InSAR), diverse algorithms and methods are developed for finding stable scatterers. Also, different models and approaches are proposed for reducing phase errors caused by diverse influencing factors such as atmospheric sphere, topographic characteristics and noise. Then, the terrain surface deformation velocity at each persistent scatterer (PS) is determined. Although PS-InSAR is already widely applied for monitoring low-speed terrain surface deformation velocity component, most researches study mainly on the estimation of linear deformation velocity. Therefore, this paper presents a new approach for improving the data processing of PS-InSAR. Moreover, some ground check data are used to evaluate the quality of PS-InSAR on monitoring terrain surface deformation. In order to increase the robustness of PS-InSAR, the technique of redundant observation in the field of surveying and geomatics is utilized on the one hand. For each computation of PS-InSAR, different sets of SAR images in the same time period are adopted so that the ability of blunder detection is increased. On the other hand, the decorrelation effect caused by diverse factors is taken into account so that different weights are given to all sets of SAR images. Weighting averages are then computed to determine the most probable deformation velocity vectors on all scatterers. Higher outer reliability is expected. Finally, the results are compared with the ground check data determined by high precision levelling. Their quality is thus estimated.

Original languageEnglish
Title of host publication37th Asian Conference on Remote Sensing, ACRS 2016
PublisherAsian Association on Remote Sensing
Pages1086-1092
Number of pages7
Volume2
ISBN (Electronic)9781510834613
Publication statusPublished - 2016
Event37th Asian Conference on Remote Sensing, ACRS 2016 - Colombo, Sri Lanka
Duration: 2016 Oct 172016 Oct 21

Other

Other37th Asian Conference on Remote Sensing, ACRS 2016
CountrySri Lanka
CityColombo
Period16-10-1716-10-21

Fingerprint

Subsidence
Synthetic aperture radar
Monitoring
Surveying

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications

Cite this

Ye, J. F., & Tsay, J-R. (2016). Determining land subsidence in western Taiwan by using a new approach of weighting PS-InSAR with redundant observations. In 37th Asian Conference on Remote Sensing, ACRS 2016 (Vol. 2, pp. 1086-1092). Asian Association on Remote Sensing.
Ye, Jun Fu ; Tsay, Jaan-Rong. / Determining land subsidence in western Taiwan by using a new approach of weighting PS-InSAR with redundant observations. 37th Asian Conference on Remote Sensing, ACRS 2016. Vol. 2 Asian Association on Remote Sensing, 2016. pp. 1086-1092
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Ye, JF & Tsay, J-R 2016, Determining land subsidence in western Taiwan by using a new approach of weighting PS-InSAR with redundant observations. in 37th Asian Conference on Remote Sensing, ACRS 2016. vol. 2, Asian Association on Remote Sensing, pp. 1086-1092, 37th Asian Conference on Remote Sensing, ACRS 2016, Colombo, Sri Lanka, 16-10-17.

Determining land subsidence in western Taiwan by using a new approach of weighting PS-InSAR with redundant observations. / Ye, Jun Fu; Tsay, Jaan-Rong.

37th Asian Conference on Remote Sensing, ACRS 2016. Vol. 2 Asian Association on Remote Sensing, 2016. p. 1086-1092.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Ye JF, Tsay J-R. Determining land subsidence in western Taiwan by using a new approach of weighting PS-InSAR with redundant observations. In 37th Asian Conference on Remote Sensing, ACRS 2016. Vol. 2. Asian Association on Remote Sensing. 2016. p. 1086-1092