3/26/2023 0 Comments Gallery stack 3.6.1![]() However, the results were significantly improved by calculating the MTF on coherence and almost reached the success rate of the ALOS-PALSAR-based coherence analysis, even though the improvement of the results with intensity was not possible. S1 was found to have limitations at the site, as single coherence differences provided low-quality results. In addition, the spatial analysis of the classification results was also evaluated to highlight the potential of S1 coherence analysis. Multitemporal analyses of both intensity and coherence were performed along with coherence differences, multitemporal features (MTF) and MTF differences of coherence images. Therefore, 17 ascending and 19 descending S1 images were analysed to test S1 accuracy on landslide detection. This raises the question: Do we need SAR imagery with higher spatial resolution (such as ALOS-PALSAR) or are freely available S1 imagery also suitable for rapid landslide detection? The S1 images could provide suitable material for a comparative analysis and could answer the aforementioned question. ![]() Nevertheless, they expressed a clear need to analyse the capabilities of other sensors (such as S1). Previous studies have successfully exploited high-resolution ALOS-PALSAR image-based intensity and coherence analysis at the 2018 Hokkaido landslides. Despite the increasing number of publications on the role of S1 in landslide detection, there is still a need for research to further clarify the capabilities of the sensor and the applicable image analysis techniques. ![]() Since 2014, Sentinel-1 (S1) Synthetic Aperture Radar (SAR) data have become an important source in the field of displacement detection thanks to regular acquisitions and 7.5 years of temporal coverage at global level. ![]()
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