顾及城市空间结构信息的元胞自动机模型构建及其应用

doi:10.13249/j.cnki.sgs.2019.08.009

摘要/Abstract

摘要：

利用衡量新增斑块空间邻接关系的多阶景观扩张指数定量识别城市组团的空间特征,结合城市组团所表现出的城市空间结构信息,构建基于MLEI的元胞自动机城市扩展（MLEI-CA）模型。针对武汉市1990、2000、2013年3期遥感影像数据,运用MLEI-CA对武汉市城市扩展进行模拟,通过与Logistic-CA模型对比验证该模型的适用性。研究结果表明,MLEI-CA模型更加准确地揭示城市扩展的空间演变过程,MLEI-CA模型精度优于Logistic-CA模型,Kappa系数、城市用地的精度分别提高6%和4%。

关键词: 城市扩展模拟, 城市空间结构, 城市组团, 多阶景观扩张指数, 元胞自动机模型

Abstract:

The urban spatial structure and its evolution have a deep impact on the development of urban spatial pattern. The traditional urban expansion simulation ignores the important influence of urban spatial structure information. This study uses Multi-order Landscape Expansion Index (MLEI), which measures spatial adjacency of new patch to identify characteristics of urban cluster, and puts such information into MLEI-CA Model. This paper uses MLEI-CA Model to simulate the urban expansion of Wuhan, based on the remote sensing image data of 1990, 2000 and 2013. Meanwhile, this paper verifies the applicability of such method by comparing with Logistic-CA model. The result shows that the MLEI-CA model can reveal the spatial evolution of urban expansion more accurately and has a better simulation accuracy than Logistic-CA model, especially in the Kappa coefficient and urban land use accuracy. The accuracy of MLEI-CA model increases by 6% and 4% respectively. The MLEI-CA model puts the information of urban spatial structure into consideration from the perspective of city expansion cluster. Furthermore, it provides new ideas for simulation of urban expansion. The simulation results can provide reference for urban planning and urban expansion effect analysis. In addition, the research model mentioned in this paper can provide new theoretical references and technical support for urban expansion simulation. However, deficiencies still exist in this study. For example, if an intelligent algorithm was considered into the model, a more realistic result might be gotten; This article use MLEI-CA model to simulate urban space form only on the basis of current situation. In practice, different situation can get different scenarios of urban space form. The MLEI-CA model needs more deep research in different cities.

Key words: urban expansion simulation, urban space structure, urban cluster, Multi-order Landscape Expansion Index, Cellular Automata model

中图分类号:

K909

焦利民,杨璐迪,刘稼丰,张博恩,许刚. 顾及城市空间结构信息的元胞自动机模型构建及其应用[J]. 地理科学, 2019, 39(8): 1276-1283.

Jiao Limin,Yang Ludi,Liu Jiafeng,Zhang Boen,Xu Gang. Construction and Application of Cellular Automata Model Based on Urban Spatial Structure Information[J]. SCIENTIA GEOGRAPHICA SINICA, 2019, 39(8): 1276-1283.

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变量	参数值	标准误差	瓦尔德检验
元胞到市级中心距离	-1.681	0.151	124.536
元胞到片区中心距离	0.061	0.120	0.255
元胞到组团的距离	1.478	0.091	260.965
元胞到高速/快速路距离	1.771	0.093	362.704
元胞到一般道路距离	2.146	0.142	228.377
坡度	6.883	0.248	772.900
高程	-0.499	0.285	3.061
常数	-10.921	0.314	1206.554

区域	原城市用地面积	新增城市用地面积:图3a	新增城市用地面积:图3b
1	9.73	17.85	7.19
2	11.53	21.61	18.73
3	10.08	1.63	14.89
4	6.61	1.12	12.79
5	9.65	21.15	10.5
6	9.62	18.51	7.66
7	9.03	1.11	14.34

	Logistic-CA 模型			MLEI-CA模型
	模拟非城市用地	模拟城市用地	精度	模拟非城市用地	模拟城市用地		精度
实际非城市用地	160354	30760	0.84	164239	26875	0.86
实际城市用地	30745	66008	0.68	26881	69872	0.72
总精度	—	—	0.79	—	—	0.81
Kappa系数	—	—	0.52	—	—	0.58