期刊
APPLIED GEOGRAPHY
卷 102, 期 -, 页码 47-57出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.apgeog.2018.12.011
关键词
Coastal region; Climate change; k-mean cluster; Mapping tool; Principal component analysis (PCA)
类别
资金
- European Union [603864]
- project on the 'Selection of Area of Intervention in the Coastal Districts of Bangladesh' under Climate Change Adaptation Programme for The Climate Resilient Rural Infrastructure Project of LGED
The coastal region of Bangladesh is highly vulnerable due to its low adaptive capacity, dense population, flat topography and exposure to various natural disasters such as cyclone, storm surges, sea level rise, tidal floods, bank erosion etc. In addition to present vulnerability, climate change will bring detrimental impact on socioeconomic performance, health, and livelihood of the coastal population. This study has been conducted to assess the vulnerabilities of the coastal region of Bangladesh by considering the IPCC framework of vulnerability studies and using multivariate statistical techniques. A total of 31 indicators have been used of which 24 are socio-economic and 7 are natural (exposure) indicators and these indicators have been retrieved from the secondary source. Principal Component Analysis (PCA) has been applied to find unequal weights of all indicators. Afterward, 7 vulnerability groups (Principal Components - PCs) have been retained which eigenvalue greater than one in accordance with Kaiser Criterion. Demographic Vulnerability (PC1), Economic Vulnerability (PC2), Agricultural Vulnerability (PC3), Water Vulnerability (PC4), Health Vulnerability (PCS), Climate Vulnerability (PC6) and Infrastructure' Vulnerability (PC7) are the principle vulnerable groups considering both present (2013) and the future (2050) climate change scenarios. Spatial maps of each group have been generated to assess the regional variation of above mentioned multispectral vulnerability profile across the coastal region of Bangladesh. Climate change will change dramatically the future vulnerability profile which will be alarming for agro-ecological systems of that region. The findings of this study might be useful for policy makers as well as planners.
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