Social Vulnerability Assessment Of Natural Disasters In Shanghai Based On Community Scale

Climate change and the urbanization exacerbated the damage of natural disasters for human beings. Hazard, exposure and vulnerability are three essential concepts of disaster risk. Recent years there come to greater importance to the vulnerability which is viewed as the potential loss of human society for natural disasters. There have valuable attempts in assessing social vulnerability at different spatial scales from national level to regional level or subnational level, while few studies had been conducted at the local level assessment of social vulnerability, which on the other hand play vital roles for local disaster risk management.In order to discuss the characteristics of social vulnerability in community level, this paper chose Shanghai as study area which not only can make up the insufficient understanding of spatial heterogeneity for social vulnerability in urban, but also make for the disaster risk management in Shanghai and promote the sustainable development of the city. As one of the most developed cities in China, Shanghai is also facing the threats of natural disasters, meanwhile the loss caused by disasters in Shanghai increasingly intensifying.Firstly, this article provided a detailed overview for the study area, including the geographic background, social-economic background and natural disaster feature. Then in order to give more specific information for the following part about social vulnerability assessment, this paper analyzed the flood variations characteristics in Shanghai. Secondly, on the base of So VI, the realities of Shanghai’s situation and data availability, this paper finished the selection of indexes which ultimately constituted the social vulnerability assessment via factor analysis. Thirdly, this paper gave a detailed analysis for the six So VI factors which were represented the social vulnerability of Shanghai, and then gave a spatial description for these factors. Fourthly, this paper used several spatial analysis tools, namely the global Moran’s I, the local Moran’s I, and Hot Spot Analysis(local Getis-Ord Gi* statistic), to detect the spatial patterns within the scores of So VI. Finally, this paper used K-means cluster analysis to partition the social vulnerability types for all the neighborhood committees in Shanghai which will be beneficial to detect the real meaning of neighborhood-level assessment of social vulnerability to natural hazards. The main results of this paper are as follows:(1) Based on the NFDS, Mann-Kendall tests and correlation analysis were applied to detect possible changes in flood frequencies. The statistical analysis showed that firstly June-September witnessed 92% of the total floods registered by NFDS, secondly annual flooding and the monthly floods in the three most flood-prone months, JuneAugust, increased significantly over 1949-2009, thirdly urban waterlogging had a strong increasing trend, whereas overbank flood had a decreasing trend and agricultural waterlogging had a slightly increasing trend. These result shows the severe threat of natural hazard in Shanghai. Besides reduce the social vulnerability is one of the most important measure for disaster risk management. Under the circumstances it is necessary to assess the social vulnerability to natural hazard in Shanghai for a fine scale considering the obvious spatial heterogeneity of Shanghai.(2) This study analyzed the neighborhood committee level of social vulnerability to natural disasters in Shanghai which was based on socioeconomic and demographic profile of 5432 neighborhood committees. Six factors represented for the social vulnerability of Shanghai which were on the base of So VI, namely general population, special population, residential characteristic, facilities, children and low rent house. The spatial pattern of So VI in Shanghai shows, there has obvious spatial difference in Shanghai, the distribution of Shanghai’s social vulnerability to natural disasters at neighborhood committee level from the central urban area to suburbs was following the pattern: high-low-high.(3) The spatial pattern of Shanghai’s social vulnerability is: the distribution of Shanghai’s social vulnerability to natural disasters at neighborhood committee level from the central urban area to suburbs was following the pattern: high-low-high. The result of global Moran’s I index indicated the clustering of So VI in Shanghai was strong. The result of local Moran’s I showed the HH clusters appear in the inner city, most area in Chongming, south part in Pudong, northeast part in Fengxian, north part Qingpu, the HL cluster scattered and fragmentary distribute in the suburbs, the LH pattern merely distribute in the northwest part of Qingpu, the distribution of LL which mostly appear in the suburbs and some peripheral areas like the northeast part of Pudong and the central area of Songjiang. The local G-statistic detected the inner city are hot spot, and around the inner city are a loop of the not significant area, then the cold spot distributes in the suburbs and scattered and fragmentary distribute in some peripheral areas, afterwards in peripheral area, the hot spot distribute in southeast and west part of Shanghai, and Chongming.(4) Based on the six factors, K-means cluster analysis was applied to partitioned the social vulnerability types for all neighborhood committees in Shanghai, finally six different types of social vulnerability committees were partitioned in this paper.Therefore, the social vulnerability to natural hazard in Shanghai significant spatial pattern. The result indicated that the distribution of Shanghai’s social vulnerability to natural disasters at neighborhood committee level from the central urban area to suburbs was following the pattern: high-low-high, which highly related with the distribution of different characteristic person: the central urban area gathered the high rate of the elderly; while high education young and the middle-aged person living within the Shanghai inner ring/suburban; correspondingly low education and low income migrants are resided in the suburbs. Thus we can speculate social vulnerability was affected by the spatial distribution of different populations especially in education, age and economic statue aspect. Although the social vulnerability of the central urban area and some suburbs in Shanghai both shown high, while the feature of those areas exhibited quite different. The central urban mainly influenced by aging populations and buildings in fragile circumstance. Yet in high vulnerability’s suburbs, the dominating factors were the low education level and low economic status, beyond that some areas were impacted a large proportion of the elderly like Chongming county.