摘要
以辽中南城市群为例,通过经济联系强度模型、城市流模型和城市通达性模型,构建系列空间联系能力数理模型,定量分析辽中南城市群空间联系能力的空间分异特征。在此基础上构建了SOM神经网络分级模型,以评价辽中南城市群十个节点城市的空间联系能力。研究表明:①沈阳的经济联系总量最大,沈阳与其他城市的经济联系强度和沈阳距其铁路距离呈S形曲线关系。②依据城市流强度值的大小将辽中南城市群十个节点城市划分为高、中、低三个档次,大连的值最大,营口则显现出作为该城市群中部区域极点的潜力。③沈大高速公路集中了通达性处于前三位的三个城市,辽阳在城市通达性方面显现出显著的优势,四项通达性指标全位居第一。④从SOM神经网络的分级结果看,沈阳都作为独立的一级,表明沈阳的空间联系能力最强,体现了其中心性的地位。
Against the backdrop of pacing up economic globalization and regional economic integration, the international elements flow more freely and frequently, such as flow of labor, material, funds, technology and information. The tends promote the development of regional society and economy along with the evolution of urban spatial structure, and make the spatial cornbination among urban agglomerations act more alive with a character of net connection. As the suburbanikation develops, spatial diffusion gradually turns into a new study field. The spatial association of urban agglomerations is an abstract concept, which we defined it not only a connection among cities of urban agglomerations but also a connection among urban agglomerations as a whole and outside regions. By applying the economic relation intensity model, urban flow model and urban accessibility model, this article constructes a series of spatial combination capacity model and analyzes the spatial differentiation characteristics of spatial combination capacity taking the mid-southern Liaoning Based on the analysis, the SOM neural network grading model is built to ty of the ten node cities. The results shows that ： 1 ） Shenyang has the Urban agglomerations as an example. evaluate the spatial combination capacilargest total economic linkage. The relationship between economic relation intensity of Shenyang and other cities, and the distance of railway among them presents the ＂S＂ curve. 2） According to the value of urban flow intensity, the ten node cities are divided into three sorts--high, middle and low. Dalian＇s value is the highest and Yingkou shows its potential as the center in the middle part of city group. 3） The accessibility of the top three cities is high along the Shenyang-Dalian Highway. 4） The classification result of SOM neural network indicates that Shenyang has the strongest combination capacity and it shows the centrality as a solely class. spatial combination capacity and it shows the centrality as a solely class.
出处
《地理科学》
CSCD
北大核心
2011年第12期1461-1467,共7页
Scientia Geographica Sinica
基金
"东师学者"青年学术骨干培养计划项目(120401042)资助
关键词
辽中南城市群
空间联系能力
通达性
SOM神经网络
Central and Southern Liaoning Urban Agglomerations
spatial combination capacity
accessibility
SOM neural network
