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Coastal Social Vulnerability and Risk Analysis for Cyclone Hazard Along the Andhra Pradesh, East Coast of India

  • K. K. Basheer Ahammed
  • Arvind Chandra PandeyEmail author
Article
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Abstract

People around the world are prone to frequent and intensive hazards due to the global climate change scenario and human interventions. Particularly, the coastal communities are always prone to various long-term coastal hazards like sea-level rise, shoreline changes, and short-term hazards like tsunami cyclone and storm surge. Coastal Andhra Pradesh state is consisting of 9 district and 670 villages and also having 3.43 Million Population (69.3%). Andhra Pradesh has a vast 972 km long coastline and total coastal area spread over 92,906 km2 comprising the nine coastal districts. Andhra Pradesh state is prone to various natural hazards, especially cyclone and associated storm surges. There is an extreme loss of life and damage to properties caused by these cyclones. During the past 40 years Andhra Pradesh coast experienced more than 62 cyclones including depression, cyclone surge, and severe cyclone surges. Among these cyclones, there were 32 cyclones which affected the Krishna–Godavari region, comprising four districts, namely East Godavari, West Godavari, Krishna, and Guntur. Therefore, these four districts have been considered for this social vulnerability study to identify the cyclone vulnerable villages. Geospatial applications are used in this study for spatial and non-spatial data processing and spatial analysis. The study indicated that half of the study area (3121.07 km2) lying moderately risk zone and around 7% of the study area observed high vulnerability. This study revealed that the use of geospatial application is most reliable and cost-effective approach for vulnerability and risk mapping and analysis. The result obtained from the present study may serve the baseline information for disaster management planning in the area.

Keywords

Climate change Natural hazard Tropical cyclone Vulnerability Risk GIS 

Küsten Soziale Anfälligkeit und Risikoanalyse für Zyklon Gefahr entlang der Andhra Pradesh, Ostküste von India

Zusammenfassung

Menschen auf der ganzen Welt anfällig aufgrund des globalen Klimawandels und menschlicher Eingriffe häufigen und intensiven Gefahren ausgesetzt. Insbesondere die Küstengemeinden sind immer verschiedenen langfristigen Küstengefahren ausgesetzt, z. B. dem Anstieg des Meeresspiegels, Änderungen der Küstenlinie und kurzfristigen Gefahren wie Tsunami-Wirbelstürmen und Sturmfluten. Der Küstenstaat Andhra Pradesh besteht aus 9 Distrikten und 670 Dörfern und hat 3.43 Millionen Einwohner (69.3%). Andhra Pradesh hat eine 972 km lange Küste und eine GesamtküsteKüstengebietnfläche von 92,906 km , die die neun Küstenbezirke umfasst. Der Bundesstaat Andhra Pradesh ist verschiedenen Naturgefahren ausgesetzt, insbesondere dem Wirbelsturm und den damit verbundenen Sturmfluten. Durch diese Zyklone kommt es zu extremen Lebens- und Sachschäden. In den letzten 40 Jahren erlebte die Küste von Andhra Pradesh mehr als 62 Wirbelstürme, darunter Depressionen, Wirbelstürme und schwere Wirbelstürme. Unter diesen Wirbelstürmen befanden sich 32 Wirbelstürme, die die Region Krishna-Godavari betrafen und vier Distrikte umfassten, nämlich East Godavari, West Godavari, Krishna und Guntur. Daher wurden diese vier Bezirke für diese Studie zur soziale Verwundbarkeit in Betracht gezogen, um die Wirbelsturm gefährdeten Dörfer zu identifizieren. In dieser Studie werden georäumliche Anwendungen für die räumliche und nicht räumliche Datenverarbeitung und räumliche Analyse verwendet. Die Studie ergab, dass die Hälfte des Untersuchungsgebiets (3121.07 km ) in einer mäßigten Risikozone liegt und rund 7% des Untersuchungsgebiets eine hohe Verletzlichkeit. Diese Studie ergab, dass die Verwendung von georäumliche ist der zuverlässigste und kostengünstigste Ansatz für die Kartierung und Analyse von Schwachstellen und Risiken. Das Ergebnis dieser Studie kann Grundlinie für die Planung des Katastrophenschutzes in der Region dienen. Das Ergebnis dieser Studie kann Dienen als Grundlinie information für die Planung des Katastrophenmanagement in der Bereich.

Notes

Acknowledgements

The authors would like to thank Global Risk Data Platform (GRDP) and IMD for making available the historical cyclone data bank. And they would also like to acknowledge Census of India for providing village-level population data. The authors also would like to acknowledge Central university of Jharkhand for proving facility and opportunity to do this research work.

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Copyright information

© Deutsche Gesellschaft für Kartographie e.V. 2019

Authors and Affiliations

  1. 1.Department of GeoinformaticsCentral University of JharkhandRanchiIndia

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