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• W2002892934 abstract "Coastal systems are characterized by high geophysical and biophysical sensitivity due to their special environment. The ecosystems along China's coast are especially vulnerable to the accelerated sea-level rise and associated multi-hazards such as storm surges and coastal flooding due to their low-lying topography, highly developed economy, and high-density population. To ensure a better management of China's coastal areas, it is crucial to develop adequate nationwide coastal vulnerability assessment models. This paperpresents our design and procedure of assessing the vulnerability of China's entire coast using eight factors. Techniques of geographic information systemand remote sensing were used to integrate the best available, spatially-disaggregated national data on critical impact elements. A comprehensive coastal vulnerability index(CVI) was then calculated by integrating the differentially weighted rank values of the variables. In the finalstep, the coastline was segmented into 4vulnerability levels: low, moderate, high and very high. The results generated from the segmentation show that 35% of the entire coast has high or very high vulnerability, mostly along Bohai Bay, the North Jiangsu coastal plain, the Yangtze River and the Yellow River Delta, and the western coast of Taiwan. The geographical distribution of the vulnerability grade proves to be reasonable. Findingsfurtherreveal that large amounts of land and population wouldbe vulnerable to inundation by coastal flooding from sea level rise and storm surge without effective measures. Finally, some suggestions are presented for decision makers and other concerned stakeholders to develop appropriate coastal zonemanagement and mitigation measures." @default.
• W2002892934 created "2016-06-24" @default.
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• W2002892934 date "2013-06-01" @default.
• W2002892934 modified "2023-10-11" @default.
• W2002892934 title "Assessment of vulnerability to sea-level rise for China's Coast" @default.
• W2002892934 cites W1567074055 @default.
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• W2002892934 doi "https://doi.org/10.1109/geoinformatics.2013.6626181" @default.
• W2002892934 hasPublicationYear "2013" @default.
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