日常人口迁徙视角下我国地级以上城市的网络联系特征——兼论引力模型系数的变化特点

Characteristics of Urban Connections at Prefecture Level or Above in China from the Perspective of Daily Population Migration——Also on the Correction of Gravitational Model Coefficients

在流空间理论下,城镇之间的日常人口迁徙状况是界定城市联系和城市体系的重要资源.因此,建立在传统的中心地体系上的城市体系和网络分析越来越多地运用引力模型作为流数据的假设值,而构建相对科学的引力模型则是合理划分城镇体系的关键,也是本文的核心问题.本文首先运用腾讯所提供的日常人口迁徙大数据,建构全国338个地级以上单位的城镇OD网络,借助复杂网络分析的相关概念,对城镇日常联系的点、线、面进行分层解析,展现了我国城镇网络联系具有地域差异性、距离衰减性和等级差异性等三个整体特征;其次,运用现有数据对经典引力模型中的经济因子、人口规模因子和等级因子进行分地域、分等级和分级别的回归分析,进而指出在不同地域、等级和级别的城市中这些因素的系数差异,并对这些系数进行修正.

In recent years, the theory of flow space, which measures the relationship between cities, has become an important supplement to the traditional urban system theory based on hierarchical scale standards. In the period when the flow data is relatively difficult to obtain, constructing a relatively scientific gravity model(model form, coefficient) is the key factor to rationally describe and plan the urban linkage system. Among the various types of actual flow data, the daily migration status between cities is one of the most important data resources. This data resource can help us understand the characteristics of urban network connections and put forward some thoughts on the construction of gravity model.This paper first uses the simple program written by Python to climb the daily population flow data of China’s prefecture-level units from Tencent’s location big data, and builds the urban OD network of 338 prefecture-level units. With the help of Ucinet, a tool for complex network analysis, the daily communication network of cities and towns is hierarchically analyzed at three levels: point(cities), line(flows) and surface(groups). The results show that there are great differences in the characteristics of network connections according to the level of regional development. The degree of network connectivity in coastal developed areas are relatively high, while the development level of central cities like Chengdu and Chongqing in the southwestern region are generally higher than that in general cities. The lower degree of networking in the northwestern region has made some large and medium-sized cities have strong control over the rest of the cities. The population flow data was transformed from the urban level to the provincial level. Using the Concor algorithm, it was found that the group formed by the urban network has a close relationship with the urban location, but the location restrictions on the southern cities are weaker than those in the northern cities. In general, the network connection characteristics show that the urban network connection in China is the result of the comprehensive effects of regional differences, distance attenuation and grade differences.Secondly, using the existing data, the economic factors, population size factors and distance factors in the classical gravity model are divided into regions, grades and distances. The results show that the influence of local economic development level on population mobility is U-shaped, and the urban economic growth in developed and underdeveloped regions will lead to a larger population flow;the attenuation factor in Central China is the weakest, and the possibleexplanation is that located in the national railway hub. The higher the city level, the stronger the influence of economy, population and distance, indicating the polarization effect of big cities. The closer the flow distance is to the urban traffic flow, the greater the hindrance of the distance. At a flow distance of more than 1 000 km, the obstruction effect of the distance is not obvious. It shows that the attenuation of the distance may only be effective in a limited space-time distance, because people are doing daily activities. Long-distance town connections may be specialized in business activities, which are less affected by time and space.The conclusions of this paper indicate that for urban space, it is necessary to pay attention to its heterogeneity characteristics at different scales and different levels and different regions. Considering the influence degree of different factors, there will be great differences. In the planning practice, it is necessary to pay attention to the construction of the theoretical model and the actual data, or use the actual data to modify the theory to obtain relatively scientific and reasonable conclusions.