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Research On Urban Park Service Assessment And Spatial Layout Optimization

Posted on:2017-07-02Degree:MasterType:Thesis
Country:ChinaCandidate:J J WuFull Text:PDF
GTID:2322330509961229Subject:Agricultural Extension
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With the urban development, urban resident living standards improve the demand for services from urban park space community are also increasing. Therefore, it is very important about evaluate and plan the layout of urban park with scientific and rational.It related to the improvement of the urban environment and quality of life of residents,related to the urban landscape, ecological environment and urban culture.Therefore, this article aim to the problem about the layout of urban park, using the spatial analysis technology in GIS, with the perspective of fairness, service, efficiency and service capacity, designs four indicators. It is the park green space service coverage, park green space accessibility, park green space service population with per unit area, the park green space of oxygen supply and demand balance. And then use the four indexes in park green space layout of the qualitative analysis and quantitative evaluation in the district of Tianhe, this study found that the city park green space layout of Tianhe is good in generally,but the distribution of citywide comprehensive park green space is too concentrated, the small community park, that population pressure is large, and park green space ecosystem services also in low levels.Finally, this paper based on urban green space on the spatial distribution of quantitative evaluation, Established multi-objective optimization model of the city park green space layout. The model consists of two parts closely linked, one maximum security services population, and the shortest distance to the optimal accessibility of parkland layout model,two optimization model based on ecological planning of green parks service accessibility Optimal layout. According to the layout in Parks evaluation results in the study area of??ecosystem services of Tianhe district, planning new park green 33 candidates in Parksweak regional; the use of accessibility Optimal Location Model, to make sure that the status quo in the park selected, each a cell with at least one adjacent park(up to 30 minutes) of constraints, while meeting the calculated maximum service population, the shortest distance to all of the park layout more optimized solutions; combining Guangzhou planning new parks from which to choose the 11 new(full coverage guarantee a minimum number of new green park), 14, 18, Tianhe District parkland site optimization results, using ecological services planning optimization model to meet for each cell population oxygen binding requirements under All park area contains the smallest park status quo, the maximum amount of oxygen optimization. Results showed that:(1) In this paper, The model of maximum coverage and P- Value Model Public Parks site has practical value layout planning, site acquisition programs are a good compromise between the distance between the target and the target population and services, fairness and efficiency, better siting results.(2) The second model can take into account the needs of the population and the maximum amount of oxygen minimum target area under planning, rational planning of the new park their area, determine the type of the new park, the final decision makers based on their preferences siting these programs making choices.In general, Based on the study area in Parks quantitative evaluation of the selected candidate points to be built in the park to participate in multi-objective optimization location model can improve the rationality of siting program, making research results closer to the needs and reality. The multi-objective optimization model can be more intuitive and effective for city Park layout optimization, so, It provide scientific guidance for urban park layout, maintaining the sustainable development of urban complex ecological environment.
Keywords/Search Tags:Urban Parks, Layout evaluation, spatial location selection, Multi-objective optimization
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