Journal
INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
Volume 75, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.ijdrr.2022.102933
Keywords
Urban floods; Vulnerability index; Vulnerability mapping; Principal component analysis; Python codesheet; GIS
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The study focuses on assessing vulnerability to urban floods in Nagpur by identifying drivers of vulnerability and using principal component analysis. It visualizes low and high vulnerable zones in the city using GIS.
Amongst all disasters, flood is the most incessant disaster influencing a noteworthy number of individuals all around the world. The developing countries have been profoundly affected by the calamities, due to excessive loss of lives and assets. The city of Nagpur in Maharashtra, India, is prone to water related disasters. In addition, the uncontrolled development has worsened the floods events. The existing physical infrastructure and social attributes have made the population vulnerable to urban floods. The study focuses on conducting a micro-scale i.e., community vulnerability assessment by identifying the drivers of vulnerability. A questionnaire based on the socio-economic and infrastructure characteristics was formulated and a primary survey was conducted. The study involved application of principal component analysis by means of python programming to develop socio-economic and physical infrastructure indices. The analysis enabled component wise and index wise visualization of low vulnerable to high vulnerable zones in Nagpur using Geographic Information System (GIS). The goodness-of-fit for socio-economic and physical infrastructure vulnerability index show R-2 value as 0.7219 and 0.7058 respectively, suggesting the models to be substantial. This robust vulnerability framework can gauge the real conditions of the population thereby assist in developing policies and strategies to reduce the impact of urban floods.
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