基于蚁群优化算法的城市生态用地空间规划模型

doi:10.13249/j.cnki.sgs.2017.03.013

地理科学 ›› 2017, Vol. 37 ›› Issue (3): 426-436.doi: 10.13249/j.cnki.sgs.2017.03.013

基于蚁群优化算法的城市生态用地空间规划模型

王海鹰^1,²(), 秦奋^1,², 张新长³, 张传才⁴, 李培君¹

1. 河南大学环境与规划学院, 河南开封 475001
2.黄河中下游数字地理技术教育部重点实验室, 河南开封 475001
3. 中山大学地理科学与规划学院, 广东广州 510275
4.安徽理工大学测绘学院, 安徽淮南 232001

收稿日期:2016-05-18 修回日期:2016-08-12 出版日期:2017-03-20 发布日期:2017-03-20
作者简介:
作者简介：王海鹰（1980-）,男,河南洛阳人,博士,讲师,硕导,主要研究方向为城市地理信息系统、空间智能优化与决策。E-mail:whyhdgis@163.com
基金资助:
国家自然科学基金青年项目（41401457）、国家科技支撑计划项目（2013BAC05B01）、国家自然科学基金重点项目（41431178）、河南省高等学校重点科研项目计划（15A170003）资助

The Spatial Planning Model of Urban Ecological Land Based on Ant Colony Optimization Algorithm

Haiying Wang^1,²(), Fen Qin^1,², Xinchang Zhang³, Chuancai Zhang⁴, Peijun Li¹

1. College of Environment and Planning, Henan University, Kaifeng 475004, Henan, China
2. Key Laboratory of Geospatial Technology for Middle and Lower Yellow River Regions/Henan University, Ministry of Education, Kaifeng 475004, Henan, China
3. School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, Guangdong, China
4.College of Geodesy and Geomatics,Anhui University of Science and Technology, Huainan 232001, Anhui,China

Received:2016-05-18 Revised:2016-08-12 Online:2017-03-20 Published:2017-03-20
Supported by:
National Nature Science Foundation of China (41401457), National Key Project of Scientific and Technical Supporting Programs (2013BAC05B01), State Key Program of National Natural Science Foundation of China (41431178),Colleges and Universities Key Scientific Research Projects of Henan Province (15A170003)

摘要/Abstract

摘要：

城市生态用地规划是城市生态系统保护的重要基础和前提。针对传统空间规划方法的不足,提出基于蚁群优化算法的城市生态用地空间规划模型。研究对蚁群优化算法的空间禁忌策略、选择策略进行改进,考虑了城市生态用地的生态效益和空间集约性,在规划目标函数中引入生态适宜性、空间紧凑度和最邻近距离指数,并设计最邻近距离指数的栅格计算方法。以广州市为例,分别模拟城市生态用地占广州市面积15%,30%和50%情景下的生态用地规划方案,取得了较好的效果。研究表明：基于蚁群优化算法的城市生态用地空间规划模型能够合理的对城市生态用地的空间布局进行配置,明显提高了城市生态用地生态效益和空间集约性。

关键词: 蚁群优化算法, 城市生态用地, 空间规划模型

Abstract:

Urban ecological land plan in cities is an important foundation and premises for the protection of urban ecosystem. Rational planning and protection of the land for ecological use is an effective way to address ecological environment problem. In addition, they are also of strategic importance to safeguard the health and balance of ecosystem, and to establish ecological security pattern and spatial extension in cities. Ecological land plan does not only require the guarantee of index area and target amount, it also involves the insurance of a series of spatial objectives and limitation such as maximization of ecological interests, the integrity, intensiveness and compactness of ecological land, and urban spatial development. This article will propose Urban Ecological Land Plan Model (UELPM) based on Ant Colony Optimization. The article makes improvements in the taboo strategy, site selection mechanism. Additionally, it introduces the ecological suitability, spatial compactness and the index of nearest neighbor distance in the process of establishing plan objectives function. Furthermore it designs Trellis Algorithm of the nearest neighbor distance index. For instance, Guangzhou simulates its ecological land plan in different situation when ecological land takes up 15%, 30% and 50% of the city’s total area, which has achieved satisfying result. According to the research, UELPM which based on Ant Colony Optimization can not only set up objectives function and spatial limitations in line with different plan destinations and requirements, but also reasonably allocate the spatial distribution of ecological land. Compared to the scheme of plan ecological control line, the average suitability, spatial compactness and the nearest neighbor distance index are greatly improved in accordance with the spatial simulation result. In addition, all other indexes are superior to the traditional method like plan ecological control line. Therefore, it is meaningful to provide scientific support and reference to urban ecological land use and it also can find itself broad application prospect.

Key words: Ant colony Optimization Algorithm, urban ecological land, spatial planning model

中图分类号:

F293.2

王海鹰, 秦奋, 张新长, 张传才, 李培君. 基于蚁群优化算法的城市生态用地空间规划模型[J]. 地理科学, 2017, 37(3): 426-436.

Haiying Wang, Fen Qin, Xinchang Zhang, Chuancai Zhang, Peijun Li. The Spatial Planning Model of Urban Ecological Land Based on Ant Colony Optimization Algorithm[J]. SCIENTIA GEOGRAPHICA SINICA, 2017, 37(3): 426-436.

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参数	第1组参数	第2组参数
最邻近距离指数	1	0
空间紧凑度指数	0	1
信息素强度	50	50
初始信息量	20	20
挥发系数	0.3	0.3
信息因子	4	4
期望因子	4	4
迭代次数	1500	1500

参数	第1组参数	第2组参数	第3组参数
生态适宜性	1	1	1
最邻近距离指数	0	1	0
紧凑度指数	0	0	1
信息素强度	20	20	15
初始信息量	50	5	50
挥发系数	0.2	0.2	0.2
信息因子	4	5	3
启发因子	3	2	3
迭代次数	1500	1500	3500

参数设置	参数（50%）	参数（30%）	参数（15%）
生态适宜性权重	1	1	1
空间聚集度权重	1	1	1
信息素强度	50	50	50
初始信息量	20	20	20
挥发系数	0.2	0.3	0.3
信息因子	4	4	4
期望因子	5	4	4
迭代次数	6 000	1 000	1 000

模拟情景	平均生态适宜性	NNI指数	CI指数
15%情景	0.710	0.631	0.185
30%情景	0.680	0.501	0.124
50%情景	0.647	0.391	0.092

对比类型	平均适宜度	NNI指数	CI指数
空间模拟结果	0.647	0.391	0.092
规划生态控制线	0.624	0.359	0.069

基于蚁群优化算法的城市生态用地空间规划模型

The Spatial Planning Model of Urban Ecological Land Based on Ant Colony Optimization Algorithm

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