1. Sentinel-1A 影像在山区管道地表形变监测中的 适用性评价指标构建.
- Author
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方迎潮, 赵雪, 陈文乐, 王庆, and 吴森
- Abstract
Sentinel-1A satellite data is characterized by its broad coverage, rapid revisit periods, and cost-effectiveness, allowing for the efficient acquisition of large-scale surface deformation information along pipelines through interferometric synthetic aperture radar ( InSAR) technology. However, with complex terrain, large topographic relief and lush vegetation, phenomena such as layover, shadow, and incoherence commonly arise during monitoring. The applicability of Sentinel-1A satellite data in different sections of the pipeline is different. To evaluate the applicability of Sentinel-1A data in surface deformation measurements, three pipeline sections in varying mountainous terrains were selected as study areas. Correlation analyses were conducted by combining Sentinel-1A data, Sentinel-2 data, and ALOS DEM data, in order to construct applicability evaluation indexes. The results show that the ratio of layover and shadow regions to the total areas in Sentinel-1A images along the pipelines is significantly negatively correlated with the slope, with Pearson correlation coefficient of - 0. 914 and Spearman correlation coefficient of - 1. Likewise, there was a significant negative correlation between image coherence and normalized vegetation index, with Pearson correlation coefficient of - 0. 972 and Spearman correlation coefficient of - 0. 99. Applicability evaluation indexes for slope and vegetation were established for Sentinel-1A data along pipelines in mountainous areas using the method of regression analysis and normalization, which can evaluate the applicability of Sentinel-1A data for deformation monitoring along the mountainous pipelines. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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