Aiming at the problem of lack of data model to analyze the level of transportation integration, the paper taking Changsha-Zhuzhou-Xiangtan City Group of China as the research object, based on the Gravity measurement model, transportation comprehensive distance model, weighted road density model, analysis of Changsha-Zhuzhou-Xiangtan City Group accessibility and transportation integration level. A new method to measure the level of traffic integration is proposed and verified by the road network data and socio-economic data of Changsha-Zhuzhou-Xiangtan City Group. The results show that: Changsha-Zhuzhou-Xiangtan City Group traffic accessibility was “point to surface” shape distribution, taking the core region of Changsha as the optimal, Xiangtan, Zhuzhou, Changsha County next, in remote Yanling County, Chaling county has the lowest accessibility; the correlation between traffic network connection degree and economic connection degree reached 0.871, indicating that the transportation integration level of urban agglomerations has a high degree of fit with the level of economic integration. The research results on the one hand for the Chang-Zhuzhou-Xiangtan urban agglomeration traffic present situation to make an annotation; on the other hand, that provide a reference for further optimization of Changsha-Zhuzhou-Xiangtan urban agglomeration traffic planning.
The level of traffic development is an important quota of the development of urban agglomeration. Traffic plays an important role in promoting the economic development of urban agglomeration. Traffic accessibility and transportation integration level are important embodiment of traffic development.
Hansen [
Taking the road network of Changsha-Zhuzhou-Xiangtan City Group core regional as the research object, using gravity metric model and road weighted density model to construct accessibility model, this paper analyzes the spatial characteristics of accessibility in the core area of Changsha-Zhuzhou-Xiangtan City Group [
The prototype of gravity model is the universal gravity model proposed by physicist Newton [
R i j = P i V i P j V j D i j 2 (1)
where Rij is the traffic network connection degree between cities i and j, Pi and Pj are the regional population indexes of the two cities, and are usually expressed by the total population, Vi and Vj are the economic indexes of the two cities, and are usually used to express the GDP of the region, and D i j 2 represents the distance of the cities i to j.
The comprehensive distance between cities can consider the transportation mode, time cost and transportation cost of the two cities at the same time. It is a more comprehensive index than the comprehensive index, and can well reflect the advantages and disadvantages of the traffic accessibility between the two cities [
D i j 2 = ∑ m = 1 n c i j − m t i j − m p i j − m (2)
where D i j 2 represents the comprehensive distance of cities i to j, and cij-m selects the weight of the traffic mode m between cities i to j; tij-m is the time cost when the transportation mode m is selected between cities i to j; pij-m is the traffic cost when traffic mode m is selected between cities i to j.
Road density refers to the ratio of the weighted length of different grades of roads to the area of the region, and is a commonly used index to evaluate the traffic situation [
P i = ∑ a = 1 b L i − a ρ a A i , i ∈ ( 1 , 2 , 3 , ⋯ , n ) (3)
where Pi is the road network density (km/km2) of region i, and Li-a is the road length of type a of region i, ρa is the weight of type a road and Ai is the land area of region i.
Usually, the greater the density of the regional network, the more developed the traffic and the higher the degree of accessibility. But if the density is too high, it will lead to low utilization rate of roads, unreasonable urban land use and excessive investment in urban traffic construction. Conversely, the density of road network is too small, the more backward the traffic, the lower the accessibility, which will easily lead to traffic congestion and affect the travel efficiency of residents [
Transportation integration refers to the unified management of transportation and planning among several cities with geographical proximity, under the impetus of social and economic development, to break through the administrative boundaries of cities, to establish cross-regional transportation infrastructure, and promote the development of regional economy [
Y = ∑ T i j (4)
T i j = L i / S i L j / S j D i j 2 (5)
where Y is the level of traffic integration; Tij is the traffic network link between city i and j; Li, Lj is the road index of two cities, usually represented by the general road length in urban administrative division; Si, Sj is the area size index of two cities, usually expressed in administrative planning area; D i j 2 represents the comprehensive distance of the city i and j.
The research area of this paper is the core area of Changsha-Zhuzhou-Xiangtan City Group. According to the planning of Changsha-Zhuzhou-Xiangtan City Group, the “3 + 5” urban circle is put forward. Its core areas are Changsha, Zhuzhou, Xiangtan, and its subordinate cities and counties: Changsha County, Wangcheng County, Liuyang City, Ningxiang City, Xiangtan County, Shaoshan City, Xiangxiang County, Liling City, Zhuzhou County, You County, Chaling County, Yanling County (
The data of this paper mainly include Changsha-Zhuzhou-Xiangtan City Group economic development data and road network data. The road network data is mainly derived from the download data of OpenStreetMap.
Based on the electronic map of Changsha-Zhuzhou-Xiangtan City Group, the road network geo-spatial database of Changsha-Zhuzhou-Xiangtan City Group was established by means of ArcGIS software [
In the traffic network of Changsha-Zhuzhou-Tan city group, railway transportation and road traffic are mainly included. Which railway including high-speed railway and ordinary railway .Road traffic includes expressway, national highway, provincial and urban road. According to the grade of different roads, the difference between the influence ability of manpower and logistics circulation among cities is analyzed, combined with score by experts, the weight of road is given to the road by comprehensive evaluation method, and the weight value of different grade roads is obtained [
In the traffic network of Changsha-Zhuzhou-Tan city group, the interpolation map of comprehensive distance accessibility presents a “point-face” shape (
| Realm name | Area (km2) | High-speed railway (km) | Railway (km) | Expressway (km) | National road (km) | Provincial road (km) | Urban expressway (km) |
|---|---|---|---|---|---|---|---|
| Changsha City | 576.89 | 56.38 | 62.07 | 129.59 | 103.89 | 235.03 | 542.11 |
| Changsha County | 1973.45 | 66.19 | 18.30 | 149.52 | 124.47 | 105.31 | 218.75 |
| Wangcheng County | 1354.96 | 0.00 | 45.36 | 99.46 | 74.21 | 47.26 | 253.04 |
| Liuyang City | 4998.17 | 0.00 | 68.20 | 13.74 | 188.23 | 164.87 | 43.96 |
| Ningxiang County | 2916.54 | 0.00 | 24.71 | 38.84 | 41.82 | 209.46 | 41.97 |
| Xiangtan City | 268.95 | 0.00 | 52.64 | 84.29 | 45.44 | 60.32 | 90.43 |
| Xiangtan County | 2528.61 | 36.58 | 51.70 | 97.65 | 75.06 | 71.66 | 56.43 |
| Xiangxiang City | 2002.17 | 32.44 | 65.92 | 100.53 | 0.00 | 168.35 | 6.39 |
| Shaoshan City | 210.56 | 18.97 | 13.81 | 0.00 | 0.00 | 26.06 | 19.92 |
| Zhuzhou City | 553.12 | 41.15 | 95.28 | 87.13 | 44.33 | 138.23 | 148.40 |
| Zhuzhou County | 1364.68 | 49.68 | 68.73 | 109.12 | 20.73 | 109.74 | 68.95 |
| Youxian County | 2661.86 | 0.00 | 66.62 | 0.00 | 67.34 | 137.53 | 10.13 |
| Liling city | 2157.52 | 35.30 | 99.04 | 74.43 | 109.13 | 43.56 | 44.53 |
| Yanling County | 2023.42 | 0.00 | 0.00 | 0.00 | 97.03 | 33.77 | 0.00 |
| Chaling County | 2491.24 | 0.00 | 42.02 | 0.00 | 75.61 | 74.77 | 0.00 |
| Road type | High-speed railway | Railway | Expressway | National road | Provincial road | Urban expressway |
|---|---|---|---|---|---|---|
| Weight | 0.3 | 0.2 | 0.2 | 0.15 | 0.1 | 0.05 |
a central area, Changsha is also the core area of regional transportation. In terms of space distance, Changsha City is close to becoming the regional center of mass and it is relatively close to the surrounding cities [
In the traffic network of Changzhou-Zhuzhou-Xiangtan urban agglomeration, the area with the highest road weighted density is Changsha, Xiangtan and Zhuzhou, which appear to form vertical zonal distribution as a whole (
In the area with the highest weighted density, there are main roads such as Jingzhu Expressway, Shanghai-Kunming Expressway, G107, G319, G320 and so on. At the same time, there are many expressways between cities. Because of the high speed railway transportation superiority, the weighted proportion is bigger, in the Changsha City, Xiangtan County, Zhuzhou City, Shaoshan City, Liling City which has the high speed railway passes, road weight density is also relatively high. In Youxian County, Chaling County and Yanling County, the weighted density of the road network is relatively low because of the relative deviation of the location and the lack of major traffic roads (
In the development of urban agglomeration to a certain level, transportation network and the total economic volume of urban agglomeration, population are closely related [
With the help of gravity measurement model, traffic comprehensive distance
| Realm name | Changsha City | Changsha County | Wangcheng County | Liuyang City | Ningxiang County | Xiangtan City | Xiangtan County | Xiangxiang City |
|---|---|---|---|---|---|---|---|---|
| Weighted density | 0.2105 | 0.0474 | 0.0424 | 0.0127 | 0.0144 | 0.1664 | 0.0246 | 0.0301 |
| Realm name | Shaoshan City | Zhuzhou City | Zhuzhou County | Liling city | Youxian County | Yanling County | Chaling County | |
| Weighted density | 0.0572 | 0.1387 | 0.0498 | 0.0316 | 0.0142 | 0.0089 | 0.0109 |
| Realm name | Economic connection degree | Traffic connection degree |
|---|---|---|
| Changsha County | 280 | 337 |
| Liuyang City | 57 | 72 |
| Ningxiang County | 105 | 234 |
| Xiangtan City | 126 | 290 |
| Zhuzhou City | 175 | 325 |
| Liling City | 34 | 80 |
| Wangcheng County | 125 | 265 |
| Xiangxiang City | 40 | 118 |
| Correlation coefficent | 0.871 |
model, road weighted density model and traffic integration model, the traffic accessibility and traffic integration level of Changsha-Zhuzhou-Xiangtan City Group are comprehensively studied. It puts forward a new method to measure the level of traffic integration. The road network data and socio-economic data of Chang-Zhuzhou-Xiangtan City Group are used to verify the method, and the traffic accessibility and economic connection degree among cities in the region are comprehensively evaluated. The results show that:
1) The most accessible area in Changsha-Zhuzhou-Xiangtan City Group is the core area of Changsha City, Xiangtan City and Zhuzhou City is the second, the regional economic development is good, the traffic network density is high. But the distant area is due to natural conditions and economic development, etc. The accessibility is very low, such as Yanling County, Chaling County.
2) In the calculation of the comprehensive distance of traffic and the weighted density of roads, the city is taken as the basic unit, and the influence factors such as the main intersections between cities are not taken into account. At the same time, the ability to influence the inter-city connection is much lower than that of high-speed railway, which is not taken into account in this paper.
3) According to the relationship between traffic integration and urban agglomeration integration, a metrological algorithm for the degree of intercity traffic network connection is put forward. Through the analysis of the correlation between the degree of transportation network connection and the degree of economic connection, the result reflects the influence of traffic on urban agglomeration economy.
4) More influence factors will be taken into account to measure the degree of traffic connection in future studies to improve the accuracy of the analysis results.
This paper was jointly funded by the National Key R&D Projects (No. 2017YFB0503802, 2018YFB0505401).
The authors declare no conflicts of interest regarding the publication of this paper.
Li, C.K., Zhou, Q.L., Ma, K.S., Fang, J. and Yang, W.T. (2019) Research on Traffic Accessibility and Transportation Integration Level of Chang-Zhu-Tan City Group in China. Jour- nal of Geographic Information System, 11, 715-726. https://doi.org/10.4236/jgis.2019.116043