An MT-InSAR Data Partition Strategy for Sentinel-1A/B TOPS Data

Remote Sensing - Tập 14 Số 18 - Trang 4562
Yuexin Wang1, Guangcai Feng1, Zhixiong Feng2, Yuedong Wang1, Xiuhua Wang1, Shuran Luo3, Yinggang Zhao1, Hao Lu1
1School of Geosciences and Info-physics, Central South University, Changsha 410083, China
2Guangzhou Urban Planning and Design Survey Research Institute, Guangzhou 510060, China
3Guangdong Research Institute of Water Resources and Hydropower, Guangzhou 510635, China

Tóm tắt

The Sentinel-1A/B satellite launched by European Space Agency (ESA) in 2014 provides a huge amount of free Terrain Observation by Progressive Scans (TOPS) data with global coverage to the public. The TOPS data have a frame width of 250 km and have been widely used in surface deformation monitoring. However, traditional Multi-Temporal Interferometric Synthetic Aperture Radar (MT-InSAR) methods require large computer memory and time when processing full resolution data with large width and long strips. In addition, they hardly correct atmospheric delays and orbital errors accurately over a large area. In order to solve these problems, this study proposes a data partition strategy based on MT-InSAR methods. We first process the partitioned images over a large area by traditional MT-InSAR method, then stitch the deformation results into a complete deformation result by correcting the offsets of adjacent partitioned images. This strategy is validated in a flat urban area (Changzhou City in Jiangsu province, China), and a mountainous region (Qijiang in Chongqing City, China). Compared with traditional MT-InSAR methods, the precision of the results obtained by the new strategy is improved by about 5% for Changzhou city and about 15% for Qijiang because of its advantage in atmospheric delay correction. Furthermore, the proposed strategy needs much less memory and time than traditional methods. The total time needed by the traditional method is about 20 h, and by the proposed method, is about 8.7 h, when the number of parallel processing is 5 in the Changzhou city case. The time will be further reduced when the number of parallel processes increases.

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Remote Sensing

Tập 14 Số 18

4562

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