Assessment of flood hotspot at a village level using GIS-based spatial statistical techniques
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The spatial mapping of flood menace extents is crucial for the effective and competent enactment of risk-lessening strategy. We focused on geographical pattern and variation in flood-affected villages in Bongaon sadar sub-division, West Bengal, India, during the period between 1996 and 2016. To appraise the indigenous smoothing and dissimilarity of flood-affected/non-affected villages, GIS-based Voronoi statistics were used. Inverse distance weighting (IDW) is used to interpolate and predict the pattern of flood-affected/non-affected zones across the sub-division. Moran’s I index statistics was considered to appraise spatial auto-correlation among the flood affected and non-affected villages. Getis-OrdGi*(d) statistics was employed to recognize the flood hotspot and cold spot areas within the study site. The higher magnitude of Moran’s I was calculated as 1999–2001, 2004, 2011, 2013, 2015, and 2016. The high Z score was recorded in 1996–1999, 2001–2003, 2011, 2013, and 2014 indicated a spatial clustering of flood-affected villages. The predictive map derived through IDW showed that 7.76% (64.59 km2) area comes under very high threat zones of flood, followed by 16.27% as high risk, 24.49% as medium risk, 23.97% as low risk, and 27.51% as very low risk. This study determines the solicitation of GIS-based prophecy for the impost of revelation mapping, so as to define the latitudinal extent and frequency of areas where most affected villages are located and potential risk areas.
KeywordsGIS Spatial clustering IDW Hotspots Flood assessment Flood prediction Flood control
We extend our thanks to the Department of Geography, Raja N. L. Khan Women’s College (Autonomous), Medinipur, India, for providing necessary facilities and logistic support for conducting the research work.
Conflict of interest
on behalf of all authors states that there is no conflict of interest.
- Chang K (2010) Introduction to geographic information systems, 5th edn. Thomas D. Timp, New York, pp 327–340Google Scholar
- ESRI (2012) ArcGIS 10 Desktop Help Center. Retrieved August 1, (2012), from ArcGIS 10 Desktop Help Center: http://help.arcgis.com/en/arcgisdesktop/10.0/help/index.html
- Ghosh S, Mistri B (2015) Geographic concerns on flood climate and flood hydrology in monsoon-dominated Damodar River Basin, Eastern India. Geogr J Article ID 486740, 16 pages. https://doi.org/10.1155/2015/486740
- Guha-Sapir D, Hoyois Ph, Below R Annual Disaster Statistical Review 2012: The Numbers and Trends. Brussels: CRED; 2013 Available at: http://www.cred.be/sites/default/files/ADSR_2012.pdf
- Majumder R, Ghosh DK, Mandal AC, Patra P, Bhunia GS (2017) An appraisal of geomorphic characteristics and flood susceptibility zone using remote sensing and GIS: A case study in Bongaon Subdivision, North 24 Parganas (West Bengal), India. Int J Res Geogr (IJRG) 3(4):32–40Google Scholar
- Mitchell A (2005) The ESRI guide to GIS analysis, vol 2. ESRI Press, 2005. In this topic Calculations Interpretation Output Best practice guidelines FAQs Potential applications Additional resourcesGoogle Scholar
- Mondal M, Satpati LN.(2012) Morphodynamic setting and nature of bank erosion of the Ichamati River in Swarupnagar and Baduria Blocks, 24 Parganas (N), West Bengal, Indian. J Spat Sci 3.0(2) Winter, Issue 2012, pp 35–43Google Scholar
- Ord JK, Getis A (1995) Local spatial autocorrelation statistics: distributional issues and an application. Geogr Anal 27(4)Google Scholar
- Papathoma-Köhle M, Promper C, Glade T (2016) A common methodology for risk assessment and mapping of climate change related hazards—implications for climate change adaptation policies. Climate 4(8):1–23Google Scholar
- Preston BL, Yuen EJ, Westaway RM, (2011) Putting vulnerability to climate change on the map: a review of approaches, benefits, and risks. Sustain Sci 6(2):177–202Google Scholar
- Sanyal J, Lu XX (2003) Application of GIS in flood hazard mapping: a case study of GangeticWest Bengal, India. Map Asia Conference. Available at: https://www.academia.edu/5476217/Application_of_GIS_in_flood_hazard_mapping_a_case_study_of_Gangetic_West_Bengal_India
- Shivaprasad Sharma SV, Roy PS, Chakravarthi V, Srinivasarao G, Bhanumurthy V (2017) Extraction of detailed level flood hazard zones using multi-temporalhistorical satellite data-sets – a case study of Kopili River Basin, Assam, India. Geomatics, Natural Hazards and Risk 8(2):792–802. https://doi.org/10.1080/19475705.2016.1265014 CrossRefGoogle Scholar
- UNISDR (2015) Global assessment report on disaster risk reduction. making development sustainable: the future of disaster risk management. Geneva, SwitzerlandGoogle Scholar