基于成渝经济区的城市间辐射效力测度评价及影响因素分析

区域性中心城市对周边地区的辐射效应,对区域经济发展和城市发展战略的制定有重要意义。本文以成渝经济区内的成都、绵阳、资阳等15个市辖区为研究对象,采用层次分析法,建立了城市间辐射效力指数的指标体系,求得各城市的城市辐射力、城市辐射效率和城市距成都距离,并通过对比得出城市间辐射效应与城市辐射效率成正比,与城市间距离成反比,与城市间辐射力差距相关性不明确的结论。

基于距离与规模的中国城市体系规模结构

城市规模结构是城市体系研究的重要内容。经济基础理论相关的研究忽视了城市体系中某一城市规模往往受到其他城市规模、距离的影响。本文以第五次人口普查的"市人口"作为城市人口规模标度指标,以铁路运行距离为两城市间距离的标度指标,证明了距离要素对解释中国城市体系结节结构的有效性。讨论了全国城市体系、北方城市、南方城市体系中城市i的规模Pi与最近距离城市n的规模Pn、城市体系首位城市s的规模Ps、区域中心城市c的规模Pc,及与相应城市间距离Din、Dis、Dic的定量关系,以及Din及其位序的定量关系。研究发现:(1)全国城市体系中,Pi可以用Pn、Din、Dic来说明,其中,Pn、Din为正向影响,Dic为负向影响,Pn影响最大,Din次之,Dic再次之。(2)北方城市体系中,Pn、Din、Pc均对Pi有正向影响,Din影响力最大,Pn次之,Pc再次之。(3)南方城市体系中Pi的解释因素及各因素的重要性与全国城市体系相同。南方城市体系与北方城市体系中Pi的解释因素的差异性源自南方城市体系中Dic、Pc/Pi较小。(4)Din与其位序R间存在与城市位序-规模律相同的内在定量关系。

环鄱阳湖城市体系规模结构变动——基于距离、规模、创新扩散的解释

在城市规模结构理论的基础上,对环鄱阳湖城市间距离、城市规模、创新扩散与城市体系规模结构变动之间的关系进行了研究。结果显示,一个城市的规模可由规模大于它且距离它最近的城市的规模以及两城市间的距离解释,两者都对此城市的规模产生正向影响,其中城市间距离的影响更大。然而,环鄱阳湖城市体系中,城市间距离的位序差异对城市间距离差异没有明显的解释作用,即环鄱阳湖城市体系中城市间距离和距离位序之间不存在明显的与城镇位序规律相一致的内在定量关系。此外,为进一步发现环湖城市体系内城市的创新扩散是否影响稳定的城市位序—规模体系,引入创新扩散因素分析了环鄱阳湖城市体系创新扩散的特征以及创新扩散与城市规模、城市位序之间的关系。结果表明,环鄱阳湖城市体系各城市的创新流强度等级与各城市规模等级基本对应,其创新扩散主要呈现出由大城市扩散到次级规模城市再扩散到小城市的等级扩散模式。

Accessibility and Integration Study of Part of the Abu Dhabi 2030 Master Plan by Using Space Syntax

This paper studies the accessibility of open spaces and facilities and the integration of streets to the whole urban system of the Emirati neighbourhood of the Business District of the Abu Dhabi 2030 Master Plan. For this purpose, axial lines were produced by applying space syntax theory, Depthmap software. The research aims to verify the location of open spaces and facilities, such as schools, in relation to the location of public transportation stops （bus, metro and tram）, in order to check their accessibility within walking distances. The objective is to pay attention to the relationship between land use and transportation in the planning phase for future interventions or proposals, in other words, to improve the accessibility of public spaces or buildings by pedestrians in order to comply with the vision of the Abu Dhabi 2030 Master Plan and its promotion of walkability and cycling. Although many measures will be taken at the scale of urban design to provide shaded open spaces and sidewalks, saving pedestrians from walking long distances shall be done in the planning phase, the challenge remains to create a micro climate to increase the ease of walking in the heat and decrease dependence on cars for mobility.

Are Chinese resource-exhausted cities in remote locations?

Numerous domestic scholars have argued that a remote location is the major factor preventing the transformation and sustainable development of resource-exhausted cities. Research to date, however, has not presented relevant evidence to support this hypothesis or explained how to identify the concept of ‘remoteness'. Resource-exhausted cities designated by the State Council of China were examined in this study alongside the provincial capital cities that contain such entities and three regional central cities that are closely connected to this phenomenon: Beijing, Shanghai, and Guangzhou. Spatial and temporal distances are used to calculate and evaluate the location remoteness degrees(LRDs) of resource-exhausted cities, in terms of both resource types and regions. The results indicate that resource-exhausted cities are indeed remote from the overall samples. Based on spatial distances, the LRDs are α_1 = 1.36(i.e., distance to provincial capital city) and β_1 = 1.14(i.e., distance to regional central city), but when based on temporal distances, α_2 = 2.02(i.e., distance to provincial capital city) and β_2 = 1.44(i.e., distance to regional central city). Clear differences are found in the LRDs between different regions and resource types, with those in western China and forest industrial cities the most obviously remote. Finally, the numbers of very remote resource-exhausted cities based on spatial and temporal distances(i.e.,α > 1.5 ∩β> 1.5) are 14 and 19, respectively, encompassing 17.9% and 24.4% of the total sampled. Similarly, 25 and 30 not remote resource-exhausted cities based on spatial and temporal distances(i.e.,α≤1.0 ∩β≤ 1.0) encompass 32.1% and 38.5% of the total, respectively. This study provided supporting information for the future development and policy making for resource-exhausted cities given different LRDs.