| Autor: |
Kajal Kumar Mandal, Kesavan Dharanirajan, Muraree Lal Meena, Toushif Jaman, Sohel Rana |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Natural Hazards Research, Vol 4, Iss 3, Pp 470-485 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2666-5921 |
| DOI: |
10.1016/j.nhres.2023.11.008 |
| Popis: |
Social vulnerability assessment is a dynamic process, which varies from place to place. In the present study, the social vulnerability index (SVI) of Malda district has been prepared because of several impacts of flood inundation. The flood inundation layer has been generated using multi-temporal remote sensing data. The flood inundation layer is prepared from real-time Synthetic Aperture Radar (SAR) data. For social vulnerability assessment, the most efficient indicators are household composition, age & sex composition, and underprivileged population (SC& ST). Economic and educational data has been collected from the Census of India Handbook 2011. All these data are combined with the district's village database on the GIS platform. The weightage overlay analysis method is applied to generate the social vulnerability index of the study area, where the multi-influencing factor (MIF) technique has been used for determining the influencing factors. The social vulnerability index has categories into Very High (4%), High (37%), Moderate (32%) and Low (27%). The social vulnerability index is being further intersected with the flood inundation layer to build a database for the most vulnerable area of this district. It has been observed that 70 villages are in Very High zones, 662 villages are in High, 578 villages are in Moderate and 479 villages are in Low zones. This study will help the disaster manager and stakeholders about the vulnerable situation of the study area and also depict the importance of geospatial techniques in disaster management. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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