城市承载力空间差异分析方法 --以常州市为例

城市承载力是指一定范围内,特定目标、特定时期城市的资源禀赋、生态环境、基础设施和公共服务对人口及经济社会活动的承载能力。基于城市复合生态系统理论,从资源环境对人类活动的支撑力、人类活动对环境的压力和调控力三方面提出城市承载力概念模型及综合承载指数计算方法,从城市管理的空间特性出发,提出基于微观空间层面的承载力空间差异性分析方法,构建承载力评价指标体系,并以常州市区为例对所提出方法进行实证研究。结果表明:(1)采用城市综合承载指数评价城市承载力,能够较为直观地显示和分析承载力空间差异,符合实际情况;(2)所划分的高、中、低承载区的空间分布与城市总体规划确定的城市空间形态基本吻合,且在城市未来发展方向上对城市空间结构规划具有指导性;(3)通过空间定量评价确定的承载力提升热点地区能够将提升要素空间化,定向、定位指导城市建设。但在提升要素筛选中受指标实际可获取性影响,存在一定的偏差,有待进一步完善。

Approach to spatial differences analysis of urban carrying capacity:a case study of Changzhou City

As the urban population increases, so do diverse urban problems and concerns including issues of servicing large numbers of people within existing resources, environment and infrastructures. Environmental problems as well as resource shortage, have become more evident and now considered central issues for urban planners and decision-makers. To address these issues, particularly environmental problems, practical method incorporating the concept of urban carrying capacity (UCC) into managing urban development is needed. Based on the ecological concept of carrying capacity, we define UCC as population and social economic activities that the natural resource, environment, urban infrastructure and commonality service can sustain within a fixed urban area, in a particular period and according to pertinent criteria of living quality. After reviewing previous researches on carrying capacity, we recognize the limitation of carrying capacity study on human ecosystem. Because of limited knowledge of the earth system and human self-adaptation ability it is difficult to estimate the quantitative capacity. A new approach to urban carrying capacity study beyond conventional research paradigm of natural ecosystem is needed. This paper aims at developing an integrated framework for assessing spatial differences of UCC which can guide planning of resource utility, environment protection and infrastructure construction in the city. Firstly we presented a model of UCC evaluation. On the basis of urban complex ecosystem theory, we contend that a single component's carrying capacity should not be identified without considering the integrity of the whole system. The UCC is inherently a kind of complex ability consisting of support, pressure and regulation which are respectively associated with resource and environment foundation, population growth and human self-regulation. UCC is studied as an indicator F calculated by the three functions. The UCC improvement hot spots can be identified by the F. Secondly we provided the index system for UCC evaluation which is composed of support parameter (S), press parameter (P) and adjustment parameter (A). There are 4 secondary indicators in S, including water quality, air, eco-environment and geological condition. Moreover population, economy and land-use have been quantified by several tertiary indicators in P. And the A has been showed in industry, traffic and infrastructure. Thirdly we assessed the spatial variation of UCC in Changzhou city according to F. Using GIS Grid Analysis we divided study area into 1886 1km×1km grids to get the level of F through the evaluation model. Three UCC zones have been identified by the value of F. There are 36.9% high-zone, 33.1% mid-zone and 30% low-zone of which the F is lower than 0.65. Lastly the hot spots of UCC improvement have been further identified in the low-zone. Based on the primary factor we concluded 5 types of hot spots, such as Water Environment Improvement Hot Spots, Industrial Structure Adjustment Hot Spots, and Limited Development Spots. Then some strategies have been sug-gested. Through a demonstration study it has been found that (1) the spatial differences of UCC can be visually displayed and analyzed using the evaluation model; (2) the distribution of the 3 types of zones is mostly coincides with the urban pattern decided by the overall urban planning of Changzhou and instructive for the urban spatial configuration planning; (3) the measures to improve the low-zone can be spatialized to guide site selection of urban construction through identifying the hot spots. However, the improvement measures can't be exhaustive and need to be further improved as a result of the evaluation index system are limited by data sources.