Research on residential care services and nursing staff in urban communities based on spatial accessibility: Taking Guangzhou’s old city as an example

Research on residential care services and nursing staff in urban communities based on spatial accessibility: Taking Guangzhou’s old city as an example, Undergraduate Innovation and Entrepreneurship Project.

This project aims to focus on two aspects: first, how to carry out the assessment of the benefits of urban regeneration green space services; second, whether the benefits of regenerated green space are reflected in human behavior perceptions? Under the framework of the study of human-land relationship theory, the green space maintained in the process of urban regeneration development is defined as stable green space, and the cumulative part transformed from construction land and maintained as green space all the time is defined as regenerated green space. Combined with the community unit, the basic unit of green space service used by residents, the dense time-series remote sensing data is applied to extract the stable and regenerated green space on the community service unit, and the ecological, social and economic multi-dimensional indicators related to regeneration are selected by combining expert scoring and hierarchical analysis, including the common green space rate and behavioral perception indicators, to establish a city-scale A model for evaluating the benefits of regenerated green spaces at the city scale and in typical regeneration cases was developed. The model is applied to the main urban area of Guangzhou to examine the spatial layout of regenerated green space from 2000 to 2015, to deeply interpret the connotation of urban regeneration planning indicators, and to clarify the differences of regeneration benefits under different transformation modes on this basis. It further combines linear planning algorithms to carry out the optimal allocation of public green space for each dimension of benefits, providing data support for the overall layout of urban green space and the optimal assessment of urban regeneration space.