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A time-series InSAR processing chain for wide-area geohazard identification

Author

Listed:
  • Zhike Zhang

    (Yunnan Normal University)

  • Ping Duan

    (Yunnan Normal University)

  • Jia Li

    (Yunnan Normal University)

  • Deying Chen

    (New Coordinate Technology Co., Ltd.)

  • Kang Peng

    (Yunnan Normal University)

  • Chengpeng Fan

    (Yunnan Normal University)

Abstract

Time-series InSAR technology has been widely applied to the identification of various types of surface deformation information, but its traditional processing chain of being applied to the detection, extraction and monitoring of wide-area geohazards requires a large amount of disk space, computing resources and processing time and has high requirements for data, personnel and equipment, which makes it difficult to promote its application in wide-area geohazard identification. Based on this background, this study constructs a time-series InSAR processing chain that makes it easy to achieve fast detection and effective extraction and monitoring of wide-area geohazards. First, the well-coherent HyP3 InSAR online service interferometric dataset is selected for time-series InSAR processing to detect the wide-area surface deformation rate. Then, the deformation anomaly regions in the wide-area range are extracted by combining multi-threshold segmentation and aggregation point (polygon) analysis methods. And then, the original Sentinel-1A SLC data are subjected to interferometric processing and time-series InSAR analysis using the open-source desktop program EZ-InSAR in the extracted typical small-area deformation anomaly regions of interest to obtain more refined deformation information. Nanjian County, Yunnan Province, China, is used as the study area, and a total of 119 potential geohazards with deformation anomalies were detected and extracted in this region, approximately half of which coincided with the results of the field survey and visual interpretation of optical images. The processing chain considers the advantages of wide-area detection of InSAR online service datasets and the advantages of raw resolution of SAR SLC data, and the data and software used are open source with low hardware requirements, which is expected to provide an effective processing chain for wide-area creep geohazard identification.

Suggested Citation

  • Zhike Zhang & Ping Duan & Jia Li & Deying Chen & Kang Peng & Chengpeng Fan, 2023. "A time-series InSAR processing chain for wide-area geohazard identification," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 118(1), pages 691-707, August.
    • Handle: RePEc:spr:nathaz:v:118:y:2023:i:1:d:10.1007_s11069-023-06024-8
    DOI: 10.1007/s11069-023-06024-8
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    References listed on IDEAS

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    1. Matthias Schlögl & Karlheinz Gutjahr & Sven Fuchs, 2022. "The challenge to use multi-temporal InSAR for landslide early warning," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 112(3), pages 2913-2919, July.
    2. Huizhi Duan & Yongsheng Li & Bingquan Li & Hao Li, 2022. "Fast InSAR Time-Series Analysis Method in a Full-Resolution SAR Coordinate System: A Case Study of the Yellow River Delta," Sustainability, MDPI, vol. 14(17), pages 1-20, August.
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