GIS空间分析在服务设施评价中的应用——以上海轨道交通五号线站周围区域为例.docx

GIS空间分析在服务设施评价中的应用——以上海轨道交通五号线站周围区域为例.docx

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GIS空间分析在服务设施评价中的应用——以上海轨道交通五号线站周围区域为例

AbstractWitll Abstract Witll the development of“One City,Nine towns”,rail transit system, extending to suburban areas, become the important connection between urban area and suburbs.However,many issues,referring to the spatial distribution of service facilities,need further discussion for primary urbanization level and unbalanced development.Therefore,谢m the support of GIS,it is a new way to domestic researches of the distribution of service facilities. In the aspect of theory research,four-level classification of service facility is put forward in the paper.Besides,population and metro station are regarded as two major factors influencing the distribution of service facilities.And service radius,service target,equality,using frequency,spatial collocation are the indicators of rational evaluation. In the aspect of methodology,GIS spatial analysis,including buffer analysis, overlaying analysis,geocoding,are applied to the study of the distributed features of service facilities,and species classification is also involved. This paper selects 500m buffer area around each station of Shanghai light-rail line 5 as the study region,and the buffer around Beiqiao station is enlarged to 1 000m. All the raw data are collected through field survey and integrated by GIS database. The paper discussed the distributed features,factors and functional mechanism. The result shows that the distribution of service facilities along line 5 has the characteristics of spatial heterogeneity,and the amount of which become fewer away from station.Furthermore,the paper presents that population distribution,income discrepancy and culture diversity are the major factors that influence the collocation of service facilities along the rail line 5. Refering to rational appraisal,Ganquan Communnity,as the frame of reference, offer the criterion of rational distribution to compare with the region along rail line 5. Finally,the paper presents several suggestions of how to optimize the spatial distributio

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