A comprehensive assessment of urban vulnerability and its spatial differentiation in China

The urban vulnerability poses a serious challenge to achieving sustainable devel- opment. With the concentration of the population and the economy, cities must manage the higher frequencies and risks of various hazards and are becoming more vulnerable. Re- search on the assessment and regulatory control of urban vulnerability is of great significance for both urbanization quality improvement and sustainable development in China or other countries in the world. Because of the complexity of cities and vulnerability concepts, existing studies have focused on different aspects of urban vulnerability. And the research content of urban vulnerability is scattered and relatively independent, leading to a lack of comparability among the research data and resulting in tremendous difficulties in summarizing the conclu- sions through comparison of independent research data. Therefore the goal of this study was to construct urban vulnerability index （UV/） from the perspective of sustainable development that could assess urban vulnerability comprehensively. In this study, we selected 10 subin- dexes involving 36 specific parameters from four aspects （resources, eco-environmental sys- tems, economics, and social development） to construct a comprehensive index system. We also established the standard values of measurements. Then we take 288 prefecture-level cities in China as a study area and evaluate its overall urban vulnerability and its spatial differentiation. Results indicate that urban vulnerability of China has a remarkable spatial differentiation of both ＂gradient distribution＂ and ＂clustered distribution＂; the extent of urban vulnerability corresponds to city size, the bigger the city, the lower its vulnerability; re- source-based cities are more vulnerable than comprehensive cities; a city＇s economic growth rate does not reflect the extent of its urban vulnerability. Further, we offer a few suggestions to cope with urban vulnerability in China.

Application of fuzzy optimization model in the evaluationof urban flood-waterloggedvulnerabilitybased on the synthetic weight ofgame theory

The evaluation of urban flood-waterlogged vulnerability is very important to the safety of urban flood control. In this paper, the evaluation of consolidated index is used. Respectively, AHP and entropy method calculate the subjective and objective weight of the evaluation indicators, and combine them by game theory. So we can obtain synthetic weight based on objective and subjective weights. The evaluation of urban flood-waterlogged vulnerability as target layer, a single variable multi-objective fuzzy optimization model is established. We use the model to evaluate flood-waterlogged vulnerability of 13 prefecture-level city in Hunan, and compare it with other evaluation method. The results show that the evaluation method has certain adaptability and reliability, and it＇ s helpfid to the construction planning of urban flood control.

The Role of the Spatial Network in Urban Disaster Risk Variations:Reimagining the Notion of Spatial Vulnerability at the Urban Scale

The notion of“spatial vulnerability”is present in most disaster studies with a strong geographical connotation and accordingly is adopted at all scales,including the urban.While enabling mapping and visualizing risk patterns at macroscales,this geocentric foundation fails to capture disaster risk dynamics associated with the urban spatial network—an element that plays a significant role in the everyday and emergency functioning of cities,enabling users'movement and interaction.Yet,urban vulnerability assessment overlooks this aspect and thus leaves urban disaster risk mechanisms partially unexplored.This study investigated the role of the network of urban public open spaces(UPOS)in the creation and progression of urban disaster risk in earthquake-prone settlements.Through a multimethod approach that integrates quantitative and qualitative methods and explores spatial configuration,planning policies,and practices of use of UPOS in everyday and emergency scenarios,our study demonstrated that UPOS configuration plays an active role in urban disaster risk.Urban public open spaces impact risk by influencing the exposure of pedestrians and their capacity for self-protection.The study further reconceptualized spatial vulnerability at the urban scale,as the fraction of vulnerability associated to the spatial network,highlighting the interplay of planning policies and spatial practices in its production and progression.Our findings make the notion of spatial vulnerability less ambiguous at the urban scale,by viewing the variable as an imbalance in capacities and exposure that generates spatially unsafe conditions.This refined conceptualization of spatial vulnerability becomes a lens for a more granular approach to urban disaster risk reduction and city planning by identifying and integrating sociospatial considerations.

Vulnerability to Landslides in the City of Sao Paulo

The City of Silo Paulo is the largest urban occupation in Brazil, covering 1,500 km^2. Its population is approximately 12 million inhabitants, 12% of them living in subnormal agglomerates, the IBGE （Brazilian Agency for Statistics and Geography） denomination for informal settlements, mostly located in fiver floodplain areas or top of hills. The extreme high level of soil sealing and high slopes have a fundamental role to explain the increase the risks of mass movements or landslides, related to precipitation magnitude and duration. This article presents the construction of curves coupling landslides occurrences and precipitation based on the data analysis of different basins in the city of Sao Panlo, considering also the probability and duration of the rainfall event in order to establish a vulnerability index to estimate the vulnerability category of an specific area. Based on the data analysis of instantaneous radar rain records for seven extreme rainfall events where landslides occurrences records were available, it was possible to plot sigmoid curves linking the number of occurrences with the event probability in terms of return period.