中文摘要：

城市体系及其空间组织分布模式是地理学、城市规划学的关注重点。城市之间具有合作与动态的网络互补关系。以资金流为例，分析资金流视角的流空间结构中城市网络分布特征。首先，分析城市网络连接度分布特征。然后从网络节点（即城市）出发，分析各城市重要程度或等级体系分布特征。研究发现：①从第一等级资金流强度到第五等级资金流强度，城市网络空间变化过程为：哈大城市走廊沿线-向东北方向扩展-向西扩展-覆盖东北地区较小规模城市-资金流网络整体向北迁移。城市间资金流联系强度较弱，且存在极化现象。②网络相对连接率较高的城市具有“丁字型”空间结构。城市等级体系为倒金字塔模式。③随着资金流强度等级下降，资金流网络所涵盖的城市规模越来越小。④前三等级资金流强度中各城市出现次数与各城市网络相对连接率为线性相关性。各城市网络现对连接率和城市出现次数与城市社会经济发展呈现较强相关性。

英文摘要：

City system and its spatial organization are concerned greatly by geographers and city planners. As the important nodes of global economic network, there exists cooperative and dynamic network complementary relationship among cities. This article will take fund flow as an example to analysis city network spatial distribution characteristics of northeast China from the perspective of fund flow. Firstly, the spatial distribution characteristics of connection strength between cities will be analyzed. Secondly, starting from the angle of network nodes, this re- search will discuss the distribution of city importance degree or the city grade system in northeast China. Main conclusions are as follows： 1 ） From the first grade connection strength to the fifth connection strength, the change process of city network spatial distribution is along the Ha-Da mega-corridor→extending toward northeast→spreading to west→cover the small scale cities of northeast China→integral fund flow network migrating to north. Connection strength of fund flow between cities has highly polarization effect. The general connection strength of fund flow between cities in northeast China is weak. 2） The spatial distribution characteristics of the node of city network are that the higher relative network connection rate of Cities demonstrate “Ding-shaped” space structure. City grade system shows reverse pyramid distribution mode except the the first grade cities which are at the top of the pyramid. 3 ） As the connection strength goes down, the scale of the cities convered by fund flow network become increasingly smaller. 4） The first three levels of relative network connection rate of cities show highly linear correlationship with the occurrence times of every city. And the relative network connection rate and the occurrence times of all cities has strong eorrelationship with their social and economic development level such as GDP and population size.