Construction of an ecological resistance surface model and its application in urban expansion simulations

被引:70
作者
Ye Yuyao [1 ]
Su Yongxian [1 ]
Zhang Hong-ou [1 ]
Liu Kai [2 ]
Wu Qitao [1 ]
机构
[1] Guangzhou Inst Geog, Guangzhou 510070, Guangdong, Peoples R China
[2] Sun Yat Sen Univ, Sch Geog & Planning, Guangzhou 510275, Guangdong, Peoples R China
基金
中国国家自然科学基金;
关键词
urban expansion; simulation; ecological resistance surface; model; CELLULAR-AUTOMATA; LAND-USE; SPATIAL PROCESSES; PATTERN; GROWTH; COVER; URBANIZATION; INTEGRATION; SCENARIOS; DYNAMICS;
D O I
10.1007/s11442-015-1163-1
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
Urban expansion models are useful tools to understand urbanization process and have been given much attention. However, urban expansion is a complicated socio-economic phenomenon that is affected by complex and volatile factors involving in great uncertainties. Therefore, the accurate simulation of the urban expansion process remains challenging. In this paper, we make an attempt to solve such uncertainty through a reversal process and view urban expansion as a process wherein the urban landscape overcomes resistance from other landscapes. We developed an innovative approach derived from the minimum cumulative resistance (MCR) model that involved the introduction of a relative resistance factor for different source levels and the consideration of rigid constraints on urban expansion caused by ecological barriers. Using this approach, the urban expansion ecological resistance (UEER) model was created to describe ecological resistance surfaces suitable for simulating urban expansion and used to simulate urban expansion in Guangzhou. The study results demonstrate that the ecological resistance surface generated by the UEER model comprehensively reflects ecological resistance to urban expansion and indicates the spatial trends in urban expansion. The simulation results from the UEER-based model were more realistic and more accurately reflected ecological protection requirements than the conventional MCR-based model. These findings can enhance urban expansion simulation methods.
引用
收藏
页码:211 / 224
页数:14
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