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

Construction of Applicability Evaluation Indexes for Sentinel-1A Image in Surface Deformation Monitoring of Mountainous Pipelines

Sentinel-1A卫星数据覆盖范围广、重访周期快、获取成本低,通过合成孔径雷达干涉测量(interferometric synthetic aperture radar,InSAR)技术能够高效获取管道沿线大面积地表形变信息。但是山区管道所处地形复杂、起伏大、植被茂盛,监测中易存在叠掩、阴影、失相干等现象,Sentinel-1A卫星数据在管道不同区段的适用性有差异。为了对Sentinel-1A在山区管道地表形变测量中的适用程度进行评价,以三段不同山区地形的管道为研究区,结合Sentinel-1A数据、Sentinel-2数据、ALOS DEM数据进行相关性分析,构建适用性评价指标。结果显示:管道沿线Sentinel-1A影像的叠掩阴影占总面积的比例与坡度的Pearson相关系数为-0.914,Spearman相关系数为-1,呈显著负相关;影像相干性和归一化植被指数的Pearson相关系数为-0.972,Spearman相关系数为-0.99,呈显著负相关。使用回归分析和归一化的方法建立了山区管道沿线Sentinel-1A数据的坡度适用性指标和植被适用性指标,指标可对山区管道沿线域使用Sentinel-1A数据进行形变监测的适用性进行评价。

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.