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Spatially Subsidized Benefits-Based Spatial Decision for Affordable Housing: Prototype and Case Study in China
Chinese cities have experienced unprecedented growth in the past few decades. In this context, the rapid rise of housing prices in Chinese cities makes the affordability of homeownership one of the biggest challenges related to people's livelihood. As a forming part of public housing, affordable housing in China mainly targets medium and low-income urban residents who cannot afford commodity housing. The spatial site selection and layout of affordable housing, which becomes a challenge for urban planners and policymakers, is potentially related to a spatial differentiation and the spread of poverty. In this study, we propose a conceptual model of spatially subsidized benefits (SSBs) of affordable housing by combining affordable housing prices and ordinary commodity housing prices in the same or adjacent location in the city. Moreover, by integrating the multiple digital elevation models (DEMs) with geographic information systems, we design a prototype for the spatial decision support system of affordable housing, which takes into account the cost of land for government, public transport facilities, residents' spatial demand, and the prevention of spatial differentiation. Using the case of Wuhan (China), we simulate the spatial layout of the SSBs of affordable housing in the city under multiple hypothetical scenarios. Our results show that SSBs display clear hierarchical characteristics under different scenarios. The findings indicate that the quantitative spatial decision method based on SSBs can provide effective technical support for Chinese urban planners or policymakers to realize a scientific layout of affordable housing under different scenarios, avoiding the risk of spatially differentiating low-income residents. Further, it also provides some insights into the innovative application of multiple DEMs in urban planning.
Spatially Subsidized Benefits-Based Spatial Decision for Affordable Housing: Prototype and Case Study in China
Chinese cities have experienced unprecedented growth in the past few decades. In this context, the rapid rise of housing prices in Chinese cities makes the affordability of homeownership one of the biggest challenges related to people's livelihood. As a forming part of public housing, affordable housing in China mainly targets medium and low-income urban residents who cannot afford commodity housing. The spatial site selection and layout of affordable housing, which becomes a challenge for urban planners and policymakers, is potentially related to a spatial differentiation and the spread of poverty. In this study, we propose a conceptual model of spatially subsidized benefits (SSBs) of affordable housing by combining affordable housing prices and ordinary commodity housing prices in the same or adjacent location in the city. Moreover, by integrating the multiple digital elevation models (DEMs) with geographic information systems, we design a prototype for the spatial decision support system of affordable housing, which takes into account the cost of land for government, public transport facilities, residents' spatial demand, and the prevention of spatial differentiation. Using the case of Wuhan (China), we simulate the spatial layout of the SSBs of affordable housing in the city under multiple hypothetical scenarios. Our results show that SSBs display clear hierarchical characteristics under different scenarios. The findings indicate that the quantitative spatial decision method based on SSBs can provide effective technical support for Chinese urban planners or policymakers to realize a scientific layout of affordable housing under different scenarios, avoiding the risk of spatially differentiating low-income residents. Further, it also provides some insights into the innovative application of multiple DEMs in urban planning.
Spatially Subsidized Benefits-Based Spatial Decision for Affordable Housing: Prototype and Case Study in China
Zhang, Zuo (author) / Zhou, Min (author) / Luo, Xiang (author) / Huang, Lin (author)
2020-10-23
Article (Journal)
Electronic Resource
Unknown
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