Abstract
Landslides are a large threat that generate important damage, economic losses and human fatalities worldwide. Identifying terrain deformations related to these phenomena is critical to reduce their impact. In particular, the population of the Indian Himalayas are menaced by landslides, which regularly endanger villages and vital transport axes. Here we present the monitoring of instabilities on some urbanized areas of Sikkim State testing the capabilities of Remote Sensing techniques, and particularly Multi-temporal analysis of Synthetic Aperture Radar data. The main municipalities of Sikkim State have been analysed, covering the most inhabited areas where landslide effects could be more dramatic for the local population. We illustrated the results obtained over the capital, Gangtok, and Namchi. These cases have been analysed thanks to the global availability of Sentinel-1 SAR data. The main multi-temporal interferometric techniques have been applied, Small Baseline Subset (SBAS) and Persistent Scatterers (PS) depending on the extension and density of the urban areas. These techniques allow to map and measure surface deformations with a millimetre sensitivity, providing the temporal evolution of the deformation trends. This is fundamental to identifying activation/re-activation of landslides and analyse eventual correlation with external factors. In case of Gangtok, a strong relation with the rainy season was easily identified. Advantages and limitation of these techniques in such arduous areas are discussed.
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Acknowledgements
The authors gratefully acknowledge Swiss Development Cooperation (SDC) that supported this project in the framework of the projects implemented in India since 2015: “Strengthening State Strategies for Climate Action (3SCA)”.
The authors also kindly acknowledge the European Space Agency (ESA) for making available the Sentinel-1 images in the framework of Copernicus activities.
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Tessari, G., Kashyap, D., Holecz, F. (2021). Landslide Monitoring in the Main Municipalities of Sikkim Himalaya, India, Through Sentinel-1 SAR Data. In: Casagli, N., Tofani, V., Sassa, K., Bobrowsky, P.T., Takara, K. (eds) Understanding and Reducing Landslide Disaster Risk. WLF 2020. ICL Contribution to Landslide Disaster Risk Reduction. Springer, Cham. https://doi.org/10.1007/978-3-030-60311-3_19
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DOI: https://doi.org/10.1007/978-3-030-60311-3_19
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