Construction of Applicability Evaluation Indexes for Sentinel-1A Image in Surface Deformation Monitoring of Mountainous Pipelines
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,Senti-nel-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 corre-lation between image coherence and normalized vegetation index,with Pearson correlation coefficient of-0.972 and Spearman correla-tion 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.
NETL
NSTL
万方数据
