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2022 Vol. 28, No. 2
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LI Lingjing, YAO Xin, ZHOU Zhenkai, WANG Defu. 2022. The applicability assessment of Sentinel-1 data in InSAR monitoring of the deformed slopes of reservoir in the mountains of southwest China: A case study in the Xiluodu Reservoir. Journal of Geomechanics, 28(2): 281-293. doi: 10.12090/j.issn.1006-6616.2021109
Citation: LI Lingjing, YAO Xin, ZHOU Zhenkai, WANG Defu. 2022. The applicability assessment of Sentinel-1 data in InSAR monitoring of the deformed slopes of reservoir in the mountains of southwest China: A case study in the Xiluodu Reservoir. Journal of Geomechanics, 28(2): 281-293. doi: 10.12090/j.issn.1006-6616.2021109
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The applicability assessment of Sentinel-1 data in InSAR monitoring of the deformed slopes of reservoir in the mountains of southwest China: A case study in the Xiluodu Reservoir

  • 1.

    Institute of Geomechanics, Chinese Academy of Geological Sciences, Beijing 100081, China

  • 2.

    School of Water Resources and Environment, China University of Geosciences, Beijing 100083, China

  • 3.

    Key Laboratory of Active Tectonics and Geological Safety, Ministry of Natural Resources, Beijing 100081, China

  • 4.

    Research Center of Neotectonism and Crustal Stability, China Geological Survey, Beijing 100081, China

  • 5.

    College of Engineering and Technology, China University of Geosciences, Beijing 100083, China

  • 6.

    The Third Geoinformation Mapping Institute of Ministry of Natural Resource, Chengdu 610000, Sichuan, China

    • Fund Project: This research is financially supported by the National Natural Science Foundation of China (Grant No.41807299), the Chinese Geological Survey Project (Grant No.DD20221738-2) and the Three Gorges Corporation Project (Grant No.YMJ(XLD)/(19)110)
Received Date:  19 August 2021
Revised Date:  20 January 2022
Publish Date:  28 April 2022
    Abstract

  • Sentinel satellite is widely used in deformed slope identification and monitoring due to its high resolution, stable orbit system, large coverage capacity, short repetition time, and free data download. Since the 1963 catastrophic landslide of Vaiant in Italy, the geologic hazard on bank slopes has been one of the main problems of the reservoir in the mountainous area. Taking the Xiluodu reservoir in the upper reaches of the Jinsha River as the study area, the applicability of the Sentinel-1 SAR data in InSAR monitoring of deformed slopes of reservoir in mountainous areas was evaluated by combining PALSAR-2 and TerraSAR-X data. The results were used to evaluate whether Sentinel-1 data could replace other commercial SAR data under certain conditions. It provides a reference for future applications in related researches. The results show that: About 200 deformed slopes were interpreted by the Sentinel-1 data in the study area, including landslide, rockfall, and bank collapse. According to field investigations, the minimum projected area of deformed slope based on the Sentinel-1 data is about 2400 m2, a size of 35 m (length)×77 m (width), gathered by 16 high-value raster pixels. Overlapping mask shadow phenomenon is severe in the alpine valley area. By comparing SAR data in common satellite radar observation modes, the effective observation area is 70.3% of the ascending Sentinel-1 orbit, 68.9% of the descending Sentinel-1 orbit, 70.4% of the ascending PALSAR-2 orbit, 67.6% of the descending PALSAR-2 orbit, and 52.5% of the descending TerraSAR-X orbit in the intersection area of all SAR data used. Without considering the resolution, it can be concluded that the Sentinel-1 data in the reservoir area has an equal or more excellent observation ability than the other two SAR data. The water level rises from June to early November, and the currounding vegetation develops well, resulting in poor data coherence. Since 2017, the amount of SAR data acquired by Sentinel-1A (1B) has increased, and high-frequency observations can improve the coherence. Therefore, the SAR data can be used to effectively identify the development and change of regional deformed slopes during the water fluctuation cycle. When the SAR data is lacking for a long time, the deformation measured by some pixels between the nearest pair of SAR data could exceed the maximum InSAR measurement range, and the phase period will be lost during the unwrapping. Sentinel-1 SAR data is more suitable for trend identification of continuous small deformations due to its good continuity.

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