Study on InSAR image fusion for improved visualization of active landslides in alpine valley areas: A case in the Batang Region, China

Abstract

InSAR observation with a wide range and high sensitivity is one of the main techniques for active landslide identification, but due to the influence of the SAR satellite side-view imaging method and observation angle, single-track images in alpine valley areas facing geometric distortion, such as shadowing, layover, and foreshortening, which leads to ineffective observation in some areas. Combining the ascending and descending observation results is expected to compensate for this deficiency to a large extent. This work constructs a pixel-level image fusion method to achieve the fusion of InSAR ascending and descending orbit deformation results, consisting of three algorithms: the DMPI (decision matrix-guided pixel-level InSAR image fusion algorithm), the DMFS (deformable median filter based on decision feedback), and the QSDS (superpixel-based dual-space InSAR image fusion quality evaluation algorithm). To verify the effect, the Batang section of the Jinsha River with high mountain canyon terrain and frequent active landslides is selected. The results show that using the DMPI fused InSAR ascending and descending orbit images can improve spatial perception by enhancing the texture gradient value of remote sensing images by a maximum of two orders of magnitude, compared with the single-track InSAR observation images. Meanwhile, the number of landslides identified increased by 31.5%, and the total area increased by 50.9% on average, improving the accuracy of target detection and identification. In noise reduction, DMFS improves fusion image readability and feature detail by removing SPN (salt and pepper noise) while preserving target edge detail. Furthermore, the QSDS which can evaluate the quality of InSAR fusion images from the perspective of human eye vision, provides an adequate basis for determining the interpretability of InSAR images. This fusion method can partially improve the question of incomplete ground observation due to radar line of sight occlusion in the high mountain canyon area, thus better presenting the InSAR observation results and helping to comprehensively and conveniently interpret the InSAR deformers.