摘要
基于1993-2008年间4个时相的遥感影像,应用SLEUTH模型模拟与预测自组织和规划引导两类情景下泉州中心城区的城市用地增长过程,并借助空间关联法分析其城市增长的空间格局演化特征,为"两规"空间协调提供科学依据。结果表明:①SLEUTH模型适用于研究区的城市增长模拟与预测,其对城市用地扩展的数量拟合要优于空间匹配,可作为多方案情景模拟的一个技术手段。②规划引导预案的MPS、ED、AWMSI、MPI四类景观指数均优于自组织预案,城市用地斑块的整体性、连接性较优,未来城市发展较为紧凑,利于实现土地的集约利用与城市的集聚发展。③随预测时间推移,研究区城市用地扩展的速率以及空间集聚性将有所减弱,城市增长的热点区也会发生演变与迁移。2008-2020年,热点区分布总体呈现"圈层式"结构,局部以"跨江发展"为主要特征;2020-2030年,热点区总体布局较为发散,局部则呈"环湾发展"与"孤立分布"特征。本研究将情景模拟、景观指数、空间分析等方法有效结合,有助于深刻理解研究区的城市空间增长过程,可为城市管理工作提供决策支持。
The paper examines the urban growth patterns in Quanzhou City based on remote sensing images over the period 1993-2008. Using SLEUTH cellular automata model, we simulate two typical scenarios of urban development： the self-organizing expansion and planning oriented growth in Quanzhou. We also employ landscape metrics and spatial statistical analysis methods to analyze the spatial characteristics of urban spatial expansion in the study areas over the study period. The results show that： （1） The SLEUTH model is a useful tool to predict urban growth patterns under different scenarios. （2） Four landscape metrics, i.e., MPS, ED, AWMSI and MPI, for the planning-oriented growth scenario are significantly greater than those derived from self-organizing expansion scenario. The planning oriented scenario is also characterized by better connectivity and integrity of urban growth patches. This further demonstrates that the urban planning, if efficiently implemented, can help to achieve the goal of compact and sustainable development. （3） However, over the years, we find that urban expansion rate and spatial aggregation in the study area are weakening and the hotspots of urban growth also changes as follows. First, from 2008 to 2020, the distribution of urban growth hotspots is characterized by a ＂single-ring＂ pattern with an emphasis on the ＂cross-river development＂. Second, from 2020 to 2030, the layout of hotspots is more dispersedly distributed characterized by ＂bay-area-oriented development＂ and ＂isolated development＂. We argue that a combination of simulation, landscape metrics and spatial analysis can provide more reliable evidence to support policy decision making concerning city planning and management in China.
出处
《地理研究》
CSSCI
CSCD
北大核心
2013年第11期2041-2054,共14页
Geographical Research
基金
福建省泉州市"十二五"规划项目
