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基于点状数据与GIS的广州大都市区产业空间格局
引用本文:田光进,沙默泉.基于点状数据与GIS的广州大都市区产业空间格局[J].地理科学进展,2010,29(4).
作者姓名:田光进  沙默泉
作者单位:北京师范大学环境学院,北京,100875
基金项目:科技部科研项目,国家自然科学基金 
摘    要:利用2004年数字城市数据,研究了广州大都市区产业内部、产业之间的空间关系,比较了广州大都市区中心城区和新城区各种产业的空间格局。将广州大都市区行业分为制造业、批发和运输、零售、生产服务业、房地产业、管理服务、教育、医疗保健及社会扶助和娱乐设施等10类。利用1 km2格网画出了各行业点状密度,并通过分区产业百分比及区位商分析了各产业企业的空间分布,中心城区的主导产业是管理服务、房地产、零售及金融保险等服务行业,而在新城区其主导功能是制造业、批发与运输及生产服务业等。利用平均最邻近距离分析广州大都市区中心城区和新城区各产业内企业之间的空间关系,广州大都市区各产业企业都呈凝聚分布,在中心城区金融行业分布最集中,其次是房地产、生产服务业、娱乐、管理服务等。利用邻近性指数分析了各产业之间的空间关系,发现生产服务业和管理服务业、教育和医疗保健与社会扶助、娱乐和零售等邻近性较大。

关 键 词:广州大都市区  产业空间格局  区位商  平均最邻近距离  邻近性指数

The Spatial Pattern of Guangzhou Metropolitan Area Industry Based on Point Data and GIS
TIAN Guangjin,SHA Moquan.The Spatial Pattern of Guangzhou Metropolitan Area Industry Based on Point Data and GIS[J].Progress in Geography,2010,29(4).
Authors:TIAN Guangjin  SHA Moquan
Abstract:This paper studies the spatial pattern of intra-sectoral and inter-sectoral industries in Guangzhou metropolitan area using the digital city data of 2004. The industries of Guangzhou metropolitan area are classified as manufacture, wholesale and transportation, retail, producer service, real estate, administration service, education, health care and social assitance, entertainment and accommodation. The cartographic map of 1km~2, percentage and location quotient are applied to study spatial distribution of establishments. In the central urban areas, administration service,real estate, retail, finance and insurance are the major industries while manufacture, wholesale and transportation and producer service are the major industries in the new cities. Average nearest neighbor distance (R) is used to study the intrasectoral spatial pattern. The establishments of Guangzhou are cluster distributed and finance and insurance are concentrated in central urban areas. Proximity index (PI) is used to study intersectoral pattern. The proximity of entertainment and accommodation and retail, education and health care and social assistance, producer service and administration service are more obvious.
Keywords:Guangzhou metropolitan area  industrial spatial pattern  location quotient  average nearest neighbor distance  proximity index
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