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高斯两步移动搜索法的模型研究——以上海市绿地可达性为例

1. 东北师范大学地理科学学院,长春 130024
• 出版日期:2016-08-25 发布日期:2016-08-25
• 通讯作者: 杨令宾 E-mail:yanglb872@nenu.edu.cn
• 作者简介:

作者简介：李孟桐(1989-),女,吉林辽源人,硕士研究生,主要从事GIS应用、灾害风险评价、地理建模与应用等方面研究,E-mail:limt251@nenu.edu.cn

• 基金资助:
国家自然科学基金项目(41271350)

Improved Gaussian based 2-step floating catchment area method:A case study of green space accessibility in Shanghai

Mengtong LI, Lingbin YANG*(), Ye WEI

1. School of Geographical Science, Northeast Normal University, Changchun 130024, China
• Online:2016-08-25 Published:2016-08-25
• Contact: Lingbin YANG E-mail:yanglb872@nenu.edu.cn
• Supported by:
National Natural Science Foundation of China, No.41271350

Abstract:

In recent years, urban public service facilities have increased rapidly. Spatial accessibility measurement can be applied to assess the soundness of public service facilities distribution. Among various kinds of methods, the Gaussian based 2-step floating catchment area (2SFCA) method is relatively straightforward, and the greatest strength of the method is that it overcomes the restriction of using only pre-defined regional boundaries. Therefore it is most widely used. However, further research is needed to improve its accuracy. Many recent improvements to the 2-step floating catchment area method generally account for distance-decay within a catchment or enable the usage of variable catchment sizes. In order to improve the method, this study conducted a case study of green space accessibility analysis for the city of Shanghai using the census data of 2000 and 2010 and raster GIS analysis. The result was compared to the original 2-step floating catchment area method output. The results show that the raster Gaussian based 2-step floating catchment area method is a more precise method than the Gaussian based 2-step floating catchment area method for measuring the spatial accessibility to green space. A map of spatial accessibility was developed to show the geographic distribution of spatial accessibility to green space in Shanghai. Spatial accessibility is higher in the peri-urban part as compared to the central part of the city. The raster Gaussian based 2-step floating catchment area method can reduce the error of Kriging spatial interpolation. In the Gaussian based 2-step floating catchment area method the result is expressed as values at the center points of streets and these values are discrete. But in the raster Gaussian based 2-step floating catchment area method the green space accessibility of a point in the space is computed for the grid cell. Thus the raster Gaussian based 2-step floating catchment area method is more precise than the Gaussian based 2-step floating catchment area method. Also, the raster Gaussian based 2-step floating catchment area method calculates the exact number of demand within a catchment. The green space accessibility example is used to demonstrate the advantage of the improved method, but it can also be applied in other urban public service facility studies.