自然灾害社会脆弱性评估研究——以上海市为例

摘要

基于投影寻踪聚类模型(PPC),结合基于实数编码的加速遗传算法(RAGA),对上海市进行了自然灾害社会脆弱性评估的尝试.结果表明:①灾害社会脆弱性最高的为崇明县,其次为宝山区和金山区；②灾害社会脆弱性最低的是黄埔区,其次是徐汇区和静安区；③总体而言,灾害脆弱性较低的地区集中于上海城市中心区,而城市边缘区的社会脆弱性一般较高.%A approach combining with the Projection Pursuit Classification Model (PPC) and Real Coding based Acceleration Genetic Algorithm (RAGA) is used to evaluate social vulnerability. A trial application of this method is made to Shanghai, China. The results show that ( 1) the social vulnerability of Chongming county, Baoshan district and Jinshan district is higher than that in other regions; ( 2) the social vulnerability of Huangpu district is the lowest, and then is Xuhui distric and Jingan district; (3 ) in Shanghai, the social vulnerability of fringe area is higher than that of the center.