Abstract
Social vulnerability assessment of natural hazards aims to identify vulnerable populations and provide decision makers with scientific basis for their disaster prevention and mitigation decisions. A new method based on remote sensing is presented here to establish a model of social vulnerability for county-scale regions that lack of relative data. To calculate population density, which is the most important indicator in social vulnerability assessment, first, a statistical model is established to estimate the population on village level. Then a new concept defined as “population density based on land use” is created to replace the arithmetic population density. The former has taken the dynamic human distribution related to land use into account; thus, it can map the population distribution more realistically. The other two indicators are age structure and distance to hospital. The application of this method to the Luogang District of Guangzhou, South China demonstrated its capability of providing high spatial resolution and reasonable social vulnerability for social vulnerability assessment of natural hazards.






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Acknowledgments
This is contribution No. IS-1334 from GIGCAS. This study is financially supported by the project of Finance department in Guangzhou (grant No. GZCY2008FG10008C-2), the science and technology project of Guangzhou (grant No. 2008J1-C051), and the key project of Guangdong province (grant No. 2008A030203003). Thanks are also given to Wu Zhifeng, Zhou Xinjing, Zeng Wei, Gong Jingping, Lv Huiping, Liu Weiping and Lu Wei for their help.
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Zeng, J., Zhu, Z.Y., Zhang, J.L. et al. Social vulnerability assessment of natural hazards on county-scale using high spatial resolution satellite imagery: a case study in the Luogang district of Guangzhou, South China. Environ Earth Sci 65, 173–182 (2012). https://doi.org/10.1007/s12665-011-1079-8
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DOI: https://doi.org/10.1007/s12665-011-1079-8