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The spatial coupling of population and economy is an important indicator that reflects regional differences and measures the coordination degree of industrial layouts and environments. To explore the spatial coupling of population and economic densities and the effect of topography in Anhui Province at a grid scale, a land-use impact model was used to spatialize socio-economic indicators in Anhui Province using 2020 county-level data. Geographical concentration and coupling index were used to quantify the spatial relationship between population and economic densities. Then the effects of topography were assessed. The results show the following: (1) the accuracy of the regression models for the individual counties is generally better than that of the models for the whole region. The population and economic densities predicted by the proposed model reflect actual conditions. (2) Topography has a stronger effect on population density and primary industry density than on secondary and tertiary industry density. Slope has the strongest effect on population and economic densities, followed by topographic relief and elevation. (3) A spatial correlation exists between topographic factors and population and economic densities. Although the spatial relationship between population and economic densities is predominantly of the balanced development type in regions with complex topography, population and economic densities are significantly lower in regions with complex rather than flat topography. In addition, economic development in the northern Anhui region, a flat region, lags behind population aggregation. Efforts should be made to improve the economic level of the southern and northern Anhui regions and the Dabie Mountain region in western Anhui. [ABSTRACT FROM AUTHOR]

Understanding and measuring the relative risk level of a city facing multi-hazards is fundamental to improving its disaster prevention planning and schemes. A comprehensive risk evaluation approach stands at the intersection of risk management and disaster system theory. It is also an important interdisciplinary field of catastrophology, economics, and urban infrastructure planning. We believe that current attempts to define and measure comprehensive urban natural disaster risks have certain limitations. Therefore, we propose an Urban Multi-hazards Risk Assessment Framework (UMRAF) which draws on definitions, methods, and experience from risk management, evaluation of property, the value of statistical life, and disaster system theory. It contains local disaster identification, place-based risk assessment (taking into account more than one hazard at a time), urban anti-disaster capability assessment, and relative composite risk index measurement. In our case study of Xiamen, China, to check the feasibility of our UMRAF, we examined local multi-hazards risk distribution and urban anti-disaster capacity layout. We then expanded and visualised the spatial distribution of the relative composite risk index of each evaluation unit across the city via our analyst tool, thereby helping to tailor measures that can reduce risk at a local level. [ABSTRACT FROM AUTHOR]

Resilience provides an adaptive approach for dealing with environmental change, natural risks and public health emergencies. Urban spatial resilience is an interpretation of resilience in the spatial dimension. However, studies on urban spatial resilience and the relationship between resilience and urban space are limited. This study tries to understand urban spatial systems and to establish an urban spatial resilience theoretical framework by integrating resilience into urban spaces to reduce urban risks. This article describes urban spatial resilience by identifying a set of urban spatial factors that may affect resilience and by linking spatial elements and resilience characteristics. The theoretical framework of urban spatial resilience has been divided into five dimensions here, urban spatial scale resilience, urban spatial structure resilience, urban spatial form resilience, urban spatial function resilience, and urban spatial network resilience. This study considers the advantages of spatial resilience from landscape ecology and urban resilience from urban studies. As a supplement to existing resilience research, this study provides a new perspective on improving the resilience of urban spaces and reduce urban risks, and guides spatial planning practitioners. [ABSTRACT FROM AUTHOR]

The continuous, intense exploitation of resources under rapid industrialization has made the ecological environment of resource-based cities increasingly vulnerability. Negative impacts of over-exploitation include soil erosion, declines in soil fertility, water pollution, and ground collapse—seriously threatening the survival and development of cities. We used Huaibei City, one of the representative coal resource-based cities, as a case study for measuring ecological vulnerability. We considered the interference effects of human mining activities, based on a typical Pressure-Sensitivity-Resilience (PSR) conceptual framework and constructed an ecological vulnerability index (EVI) system that couples natural and human factors. We then evaluated the EVI using the comprehensive index method. Finally, we combined a Bayesian network model with an entropy difference method, to optimize land use to minimize ecological vulnerability. We found that EVI ranged from 0.25 to 077, with highly vulnerable areas mainly concentrated in the southwest and north of the study area. The subset of {Soi = 1, MSA = 1} was selected as the optimal state subset of key variables for spatial pattern optimization, and primary and secondary optimization areas were mainly concentrated in Xiangshan and Duji Districts. This research will help protect the key ecological functional zones in the region, and provide a reference for policy-making in order to improve the comprehensive carrying capacity of resource-based cities. [ABSTRACT FROM AUTHOR]