Landslide Assessment Using Sentinel-I SAR-C Interferometry Technique
| Autor: | Sudhir Kumar Chaturvedi |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | Nature Environment and Pollution Technology, Vol 21, Iss 3, Pp 1201-1207 (2022) |
| Druh dokumentu: | article |
| ISSN: | 0972-6268 2395-3454 |
| DOI: | 10.46488/NEPT.2022.v21i03.025 |
| Popis: | Landslides might remain unknown or unnoticed for a long time in various remote areas due to the unavailability of optical images caused by cloud persistence, which creates difficulties for civil protection rescue operations, and disaster management as well. Rapid crisis response for humanitarian and reconstruction operations in the affected area after such dangerous landslides is necessary. Thus, a rapid detection map is necessary to detect the affected area with damage grade and level for further investigation and human safety protocols. To detect landslide incidents, the unprecedented availability of Sentinel-1 SAR-C band images provides new solutions and better safety reports. In this study, we performed an efficient evaluation of Sentinel-1 SAR C band images before and after landslide incidents. This study provides a comprehensive evaluation based on the advanced space-borne remote sensing technology aiming at SAR products for rapid damage detection and analysis with respect to the interferometric coherence and intensity correlation. We presented the results of a pilot study on the Rudraprayag Uttarakhand massive landslide incident, which includes the different types, sizes, slope expositions, and human safety aspects. Our study and outcomes represent an updated method, which provides a solution for critical terrain rescue operations and an upgraded geomatics map that provides subsidence data with historical data with topographical statistics. Finally, an outlook into the Sentinel-1 SAR-C analysis demonstrates probable solutions to certain constraints, enabling global applicability of the proposed damage assessment methods with the improved accuracy from 50 to 60 % for the obtained temporal resolution datasets. |
| Databáze: | Directory of Open Access Journals |
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