Deformation Retrievals for North America and Eurasia from Sentinel-1 DInSAR: Big Data Approach, Processing Methodology and Challenges

• Published in: Canadian Journal of Remote Sensing
• Main Authors: Sergey V. Samsonov, Wanpeng Feng
• Format: Article in Journal/Newspaper
• Language: English; French
• Published: Taylor & Francis Group 2023
• Subjects: Environmental sciences; GE1-350; Technology; T; Arctic; Canada
• Online Access: https://doi.org/10.1080/07038992.2023.2247095; https://doaj.org/article/25fbda15970348d8a598ce407c0f77d5

A fully automated processing system for measuring long-term ground deformation time series and deformation rates frame-by-frame using DInSAR processing technique was developed at the Canada Center for Remote Sensing. Ground deformation rates from 2017 to 2023 were computed over a large territory of North America and Eurasia from more than 220,000 readily available Sentinel-1 images, and the performance and shortcomings of the developed processing system were analyzed. Here, we present the processing methodology and several examples of deformation rate maps and time series produced with this automated system. Examples include the deformation of slow- moving deep-seated landslides in two regions of Canada, subsidence at the Komsomolskoe oil field in the Russian Arctic, the Tengiz oil field in Kazakhstan, multiple large subsiding regions and landslides in northwestern Iran, and two large subsiding regions in the Yellow River Delta and Xinjiang, China. Many deformation processes observed in these deformation rate maps, including large landslides, have previously been unknown to the research community. Systematic radar penetration depth changes were observed in multiple regions and were investigate in detail for 1 Eurasian region. Computed deformation rates for North America and Eurasia are available to the research community and can be downloaded from the data repository.