DAI Keren, ZHANG Lele, SONG Chuang, LI Zhenhong, ZHUO Guanchen, XU Qiang. Quantitative Analysis of Sentinel-1 Imagery Geometric Distortion and Suitability Along Qinghai-Tibet Plateau Traffic Corridor[J]. Geomatics and Information Science of Wuhan University, 2021, 46(10): 1450-1460. DOI: 10.13203/j.whugis20210130
Citation: DAI Keren, ZHANG Lele, SONG Chuang, LI Zhenhong, ZHUO Guanchen, XU Qiang. Quantitative Analysis of Sentinel-1 Imagery Geometric Distortion and Suitability Along Qinghai-Tibet Plateau Traffic Corridor[J]. Geomatics and Information Science of Wuhan University, 2021, 46(10): 1450-1460. DOI: 10.13203/j.whugis20210130

Quantitative Analysis of Sentinel-1 Imagery Geometric Distortion and Suitability Along Qinghai-Tibet Plateau Traffic Corridor

  • Objectives The Qinghai-Tibet Plateau traffic corridor is not only a state key project in China, but also the most difficult super project in railway construction history due to the most complex terrain and the active geological structure. Interferometric synthetic aperture radar (InSAR) has proved to be a critical tool for detecting and monitoring geohazards because of its wide coverage, high precision, and high efficiency. Howe-ver, due to its side-looking geometry, InSAR faces serious geometric distortions in mountainous areas, particularly in extremely steep high mountain and gorge areas.
    Methods Utilizing the full open-access Sentinel-1 data, which has the wide coverage and a short revisiting time, we carry out satellite radar geometric distortion and feasibility analysi. Taking into account synthetic aperture radar(SAR) imaging geometry, the variations of the incidence angles across the whole SAR image, and the passive geometric distortions, we present an integrated approach to accurately determine the areas with SAR geometric distortions.
    Results Our results for Sentinel-1 data show that the areas with geometric distortions for observations with a single-orbit (i.e. ascending or descending) reach 31%—35%, whilst the geometric distortion areas reduce to 1.5% for observations with both ascending and descending orbits; furthermore, about 35% of the whole area is suitable for joint analyses with both ascending and descending observations.
    Conclusions The quantitative result also reveals the feasibility to use the Sentinel-1 data to detect and monitor geohazards from the perspective of geometric distortions. It can not only improve the overall understanding of the applicability of Sentinel-1 based InSAR and the InSAR results interpretation in this area, but also provide a guideline for efficiently selecting other satellite SAR datasets for detecting and monitoring geological disasters.
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