Three-dimensional movement inversion of Shisha Pangma glacier using Sentinel-1 and Landsat8 images
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摘要:
SAR偏移量技术和光学偏移量技术是冰川运动监测重要的技术手段，但目前对于融合不同平台的影像进行三维形变的研究较少。文章选取2019年11月至2021年1月西藏聂拉木县希夏邦马峰地区的大型冰川作为研究对象，基于方差分量估计融合该研究区的Sentinel-1与Landsat8两种数据进行冰川的三维位移解算，选取了同一时期的光学影像对偏移量估计结果进行对比分析，同时选取稳定区域进行精度评估，分析该方法在冰川运动监测中的适用性和精确性。结果表明，该冰川在2019年11月至2021年1月，联合解算的东西向最大流速为21 cm/d，南北向最大流速为68 cm/d，垂直向最大流速为17 cm/d。对比单一影像获取的冰川位移结果，多影像联合解算方法，能够弥补SAR数据的失相干和光学数据的低质量像元值的不足，获得更加完整和详细的冰川信息，监测结果精度更高。可为利用不同平台的数据联合监测山地冰川的多维度和高精度变化提供参考和技术支持。
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关键词:
- Sentinel-1 /
- Landsat8 /
- 偏移量跟踪技术 /
- 联合解算 /
- 冰川三维监测
Abstract:SAR offset and optical offset are important techniques for glacier movement monitoring, but there are few researches on 3D deformation by integrating images from different platforms. In this paper, large glaciers in The Shisha Pangma area of Nyalam County, Tibet from November 2019 to January 2021 were selected as the research area. Based on variance component estimation, Sentinel-1 and Landsat8 data of the study area were combined for three-dimensional glacier calculation. Optical images of the same period were selected for comparative analysis of the offset estimation results. At the same time, the accuracy of the method was evaluated by selecting the stable area, and the applicability and accuracy of the method in glacier movement monitoring were analyzed. The results show that the maximum velocity of the glacier is 21 cm/day in the east-west direction, 68 cm/day in the north-south direction, and 17 cm/day in the vertical direction. Compared with the glacier displacement results obtained from a single image, the multi-image joint algorithm can compensate for the incoherence of SAR data and the low quality pixel values of optical data, and obtain more complete and detailed glacier information and higher accuracy of monitoring results. This paper can provide reference and technical support for using data from different platforms to jointly monitor multi-dimensional and high-precision changes of mountain glaciers.
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表 1 研究所采用的Sentinel-1数据参数
Table 1. The Sentinel-1 data parameters used in the study
影像编号 采集日期 空间基线/m 时间基线/d 1 2019-12-08 0.00 0 2 2020-01-25 −39.83 48 3 2020-03-13 −112.08 96 4 2020-04-30 −112.19 144 5 2020-06-17 −51.88 192 6 2020-08-04 −33.98 240 7 2020-09-21 −105.59 288 8 2020-11-08 −101.99 336 9 2020-12-26 125.79 384 
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表 2 研究所采用的Landsat8影像参数
Table 2. The Landsat8 imaging parameters used in the study
影像编号 采集日期 太阳高度角/(°) 太阳方位角/(°) 含云量/% 1 2019-11-19 38.52 157.40 1.74 2 2020-01-22 35.61 150.5 4.65 3 2020-02-07 39.10 147.2 3.28 4 2020-11-21 37.78 157.5 2.54 5 2021-01-08 33.93 153.0 4.20 6 2021-01-24 36.10 150.0 1.32
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表 3 研究所采用的Landsat8影像对
Table 3. The Landsat8 image pairs used in the study
Landsat8影像对的日期 太阳高度角差值/(°) 太阳方位角差值/(°) 2019-11-19—2020-02-07 0.58 10.2 2019-11-19—2020-11-21 0.74 0.1 2020-01-22—2020-11-21 2.17 7.0 2020-01-22—2021-01-08 1.68 2.5 2020-01-22—2021-01-24 0.49 0.5 2020-02-07—2020-11-21 1.32 0.5 2020-11-21—2021-01-24 1.68 7.5
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表 4 融合后和同期影像对稳定区域的标准差统计
Table 4. Standard deviation statistics for st able regions after fusion and concurrent images
统计值 融合后结果/(cm·d−1) Landsat8影像对结果/(cm·d−1) 南北向 东西向 南北向 东西向 Roi1 0.56 0.91 1.0 0.99 Roi2 0.48 0.60 0.77 0.84
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