KEYWORDS: Geographic information systems, Roads, Analytical research, Data conversion, Data modeling, Control systems, Design and modelling, Standards development, Spatial analysis, Ecology
As urbanisation continues, problems such as spatial congestion, population concentration and lack of environmental greenery are gradually coming to the fore. The existing urban green spaces have formed a scattered layout in the city due to the needs of the service recipients, their distribution, and other environmental factors making it difficult to balance functionality and economy, thus, creating an inability to achieve the maximum extent of green space service range requirements as well as forming an organic network system. This paper adopts a geographic information system (GIS) analysis model and attempts to use technical means to analyse pocket parks in cities, focusing on the spatial distribution of residents, their composition, demand differences, the competitiveness of neighbouring parks, service facilities and the degree of road radiation. The study also explores a digital analysis-based approach to the layout of urban pocket parks, which combines the needs of residents with the spatial layout of pocket parks in a practical way. This ensures the needs of residents and the balance of spatial distribution can be fully considered. In addition, the urban habitat and ecological environment can be improved and the overall appearance of the city can be enhanced.
Taking Hongshan District, Wuhan City as the research area, using remote sensing data, POI data and Baidu heat map data, we used kernel density and two-factor mapping method to analyse the coupling degree of public service facilities and population in space and time. The remote sensing map and the population heat density from the distribution, there are differences, using multiple sources of data for validation can compensate, the shortcomings caused by a single data source. It is also possible to analyse the coupling between public service facilities and population distribution from two latitudes in time and space. Taking the Hongshan District as an example, we can conclude that: 1. Spatially, public service facilities in Hongshan District show a pattern of one main centre and two to three secondary centres, with a relatively uneven spatial distribution; 2 .Spatially, the population is coupled with public service facilities in a primary and secondary manner, with better coupling concentrated in the areas south of Hongshan Square and Liyuan Street area; 3. From the analysis of the population heat map, the demand for transportation facilities is greater on weekdays than on weekends, and the demand for shopping facilities is greater on weekends than on weekdays.
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