土地利用配置的混沌蚁群优化算法研究

doi:10.3724/SP.J.1047.2017.01026

摘要/Abstract

摘要：

土地利用优化配置是促进土地可持续发展的重要举措,然而现有研究缺乏有效求解土地利用优化配置模型的新型混合式智能优化算法。本文结合蚁群算法和混沌模型,形成混沌蚁群优化（Chaos Ant Colony Optimization,CACO）算法,并以广州市增城区为研究区,对土地利用现状进行优化配置;然后在数量结构、目标函数值、空间布局等方面将优化结果与土地现状及标准蚁群算法优化结果进行对比分析。结果表明：① CACO算法能在满足多种约束条件下,有效解决多目标土地利用优化配置问题;② 与标准蚁群算法相比,CACO算法能增加土地利用的经济效益7.18亿元、生态效益0.33亿元、社会效益1.13%,同时降低地类转换成本1.15%;③ CACO算法能使土地利用现状空间分布多样性和均匀性的下降控制在1.30%以内,同时缩减地块数量8.86%,并使平均斑块大小增加9.77%,从而提升土地集约利用水平,更合理地配置各现状地类的空间分布,为研究区土地利用的科学规划与决策提供支持。

关键词: 土地利用, 优化配置, 混沌蚁群算法, 增城区

Abstract:

The optimal allocation of land use is an important and effective measures of promoting the sustainable development of the land. However, existing research was lack of efficient methods in the optimization allocation for the quantitative structure and spatial layout of land use by using original mixed algorithm. Therefore, this paper combined the ant colony optimization algorithm (ACO) with the chaos model, and proposed a hybrid and self-adapt chaos ant colony optimization algorithm (CACO). After that, in order to verify the feasibility and efficiency of the CACO, the Zengcheng district of Guangzhou was selected as the study case. The CACO was utilized to solve the model of land use optimization allocation based on the evaluation of actual land sustainable use. Finally, this study made some comparative analysis of the results of the CACO and the actual land use and the results of the ACO respectively in three main aspects: the quantitative structure of land use, the spatial layout of land use and the multiple objective functions. The results showed that: firstly, the CACO can effectively solve the complex problems of multi-objective land use optimization allocation under multiple constraint conditions; secondly, compared with the ACO, the coordination between economic benefit and ecological effectiveness in the CACO was weakened slightly. The CACO rose all others objective functions’ values. For example, economic benefits increased by 7.18 billion yuan, ecological effectiveness increased by 0.33 billion yuan, social benefits increased by 1.13%, while the land conversion costs shrank by 1.15%. Thirdly, compared with the ACO, the CACO decreased the diversity and evenness index of actual land use spatial distribution within 1.30%, made the number of total land patches reduced about 8.86%, and the average patches size increased 9.77%. The level of the land intensive use was improved. Therefore, the CACO could reasonably optimize actual various land use types to appropriate spatial layout, and supply useful technical support for scientific land use planning and decisions making.

Key words: land use, optimization allocation, chaos ant colony optimization algorithm, Zengcheng district

陆军辉, 梅志雄, 赵书芳, 肖艳云. 土地利用配置的混沌蚁群优化算法研究[J]. 地球信息科学学报, 2017, 19(8): 1026-1035.DOI:10.3724/SP.J.1047.2017.01026

LU Junhui,MEI Zhixiong,ZHAO Shufang,XIAO Yanyun. Land Use Optimization Allocation Based on Chaos Ant Colony Algorithm[J]. Journal of Geo-information Science, 2017, 19(8): 1026-1035.DOI:10.3724/SP.J.1047.2017.01026

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年份	年末耕地面积/hm²	增加值/亿元	经济效益系数/（万元/hm²）
2005	37 112	172 407	4.646
2006	27 188	193 504	7.117
2007	27 082	203 177	7.502
2008	27 014	223 454	8.272
2009	27 120	240 506	8.868
2010	27 114	270 515	9.977
2011	27 060	278 903	10.307
2012	27 042	309 373	11.440
2013	27 020	345 337	12.781
2014	26 570	372 281	14.011
2020	-	-	24.160

变量	耕地	园地	林地	草地	水域	城镇	农村	交通	其他
权重	1.00	1.54	1.50	1.54	0.55	7.02	0.67	0.67	0
经济效益系数/（万元/hm²）	17.33	26.69	26.00	26.69	9.53	121.67	11.61	105.37	0.10
生态效益系数/（万元/ hm²）	6.83	7.06	8.01	7.19	9.44	0	0	0	7.19

统计类型		耕地	园地	林地	草地	水域	城镇	农村	交通	其他
优化下限	像元数/个	112 219	83 809	245 735	0	32 989	59 225	0	24 600	0
优化上限	像元数/个	646 671	646 671	646 671	26 190	32 989	96 756	14 664	24 600	15 938
地类现状	像元数/个	112 219	83 829	229 329	26 211	32 989	59 225	62 331	24 600	15 938
	占比/%	17.35	12.96	35.46	4.05	5.10	9.16	9.64	3.80	2.48
	斑块密度	0.106	0.236	0.027	0.548	0.244	0.069	0.580	0.606	0.788
	形状指数	5.59	3.20	20.76	2.12	4.34	8.96	1.81	3.03	1.71
ACO	像元数/个	112 505	74 405	260 600	21 006	32 989	94 993	14 879	24 600	10 694
	占比/%	17.40	11.51	40.30	3.25	5.10	14.69	2.30	3.80	1.65
	斑块密度	0.105	0.237	0.026	0.534	0.244	0.068	0.597	0.606	0.788
	形状指数	5.81	3.21	21.16	2.11	4.34	9.09	1.78	3.03	1.71
CACO	像元数/个	113 808	73 175	263 057	20 057	32 989	97 510	10789	24 600	10 686
	占比/%	17.60	11.32	40.68	3.10	5.10	15.08	1.67	3.80	1.65
	斑块密度	0.096	0.210	0.023	0.500	0.244	0.062	0.565	0.606	0.788
	形状指数	5.54	3.18	20.75	2.06	4.34	8.90	1.72	3.03	1.70

统计类型	经济效益/亿元	生态效益/亿元	社会效益	经济生态协调性
现状	542.048	95.242	466 812.60	1 293 318
ACO	647.748	98.011	493 145.00	1 293 915
ACO增幅/%	19.500	2.908	5.641	0.046
CACO	654.925	98.337	498406.40	1 293 971
CACO增幅/%	20.824	3.249	6.768	0.050
CACO-ACO	7.1766	0.325	5261.400	56

统计类型	斑块数量	平均斑块大小	香农多样性指数	辛普森均匀度指数	香农均匀度指数	运算时间/h
现状	23 713	6.82	1.75	0.86	0.79	-
ACO	23 567	6.86	1.74	0.86	0.79	9.66
CACO	21 478	7.53	1.72	0.86	0.78	8.89
CACO比ACO增减幅度/%	-8.86	9.77	-1.15	0.00	-1.27	-7.97