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Article

Flood Susceptibility Mapping through the GIS-AHP Technique Using the Cloud

1
Department of Agricultural Engineering, Institute of Agriculture, Visva-Bharati, Sriniketan 731236, India
2
ICAR-NINFET, 12 Regent Park, Kolkata 700040, India
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2020, 9(12), 720; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9120720
Received: 19 August 2020 / Revised: 20 November 2020 / Accepted: 23 November 2020 / Published: 2 December 2020
(This article belongs to the Special Issue Disaster Management and Geospatial Information)
Flood susceptibility mapping is essential for characterizing flood risk zones and for planning mitigation approaches. Using a multi-criteria decision support system, this study investigated a flood susceptible region in Bihar, India. It used a combination of the analytical hierarchy process (AHP) and geographic information system (GIS)/remote sensing (RS) with a cloud computing API on the Google Earth Engine (GEE) platform. Five main flood-causing criteria were broadly selected, namely hydrologic, morphometric, permeability, land cover dynamics, and anthropogenic interference, which further had 21 sub-criteria. The relative importance of each criterion prioritized as per their contribution toward flood susceptibility and weightage was given by an AHP pair-wise comparison matrix (PCM). The most and least prominent flood-causing criteria were hydrologic (0.497) and anthropogenic interference (0.037), respectively. An area of ~3000 sq km (40.36%) was concentrated in high to very high flood susceptibility zones that were in the vicinity of rivers, whereas an area of ~1000 sq km (12%) had very low flood susceptibility. The GIS-AHP technique provided useful insights for flood zone mapping when a higher number of parameters were used in GEE. The majorities of detected flood susceptible areas were flooded during the 2019 floods and were mostly located within 500 m of the rivers’ paths. View Full-Text
Keywords: flood susceptibility; geographic information system (GIS); analytical hierarchy process (AHP); Google Earth Engine (GEE); multi-criteria decision support system flood susceptibility; geographic information system (GIS); analytical hierarchy process (AHP); Google Earth Engine (GEE); multi-criteria decision support system
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MDPI and ACS Style

Swain, K.C.; Singha, C.; Nayak, L. Flood Susceptibility Mapping through the GIS-AHP Technique Using the Cloud. ISPRS Int. J. Geo-Inf. 2020, 9, 720. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9120720

AMA Style

Swain KC, Singha C, Nayak L. Flood Susceptibility Mapping through the GIS-AHP Technique Using the Cloud. ISPRS International Journal of Geo-Information. 2020; 9(12):720. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9120720

Chicago/Turabian Style

Swain, Kishore C., Chiranjit Singha, and Laxmikanta Nayak. 2020. "Flood Susceptibility Mapping through the GIS-AHP Technique Using the Cloud" ISPRS International Journal of Geo-Information 9, no. 12: 720. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9120720

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