基于遗传算法和图论法的生态安全格局构建与优化——以武汉市为例

doi:10.13249/j.cnki.sgs.2022.10.001

地理科学 ›› 2022, Vol. 42 ›› Issue (10): 1685-1694.doi: 10.13249/j.cnki.sgs.2022.10.001

• • 下一篇

基于遗传算法和图论法的生态安全格局构建与优化——以武汉市为例

王子琳¹(), 李志刚¹, 方世明²()

1.武汉大学城市设计学院/湖北省人居环境工程技术研究中心，湖北武汉 430072
2.中国地质大学（武汉）公共管理学院/国土资源部法律评价工程重点实验室，湖北武汉 430074

收稿日期:2021-03-19 修回日期:2021-05-24 出版日期:2022-10-10 发布日期:2022-12-06
通讯作者: 方世明 E-mail:zilin_wang@whu.edu.cn;fsmcug@qq.com
作者简介:王子琳（1995−），女，广西桂林人，博士研究生，主要从事自然资源保护、规划与评价。E-mail: zilin_wang@whu.edu.cn
基金资助:
国家自然科学基金项目(41201574);国家自然科学基金项目(41771167)

Construction and Optimization of Ecological Security Pattern Based on Genetic Algorithm and Graph Theory: A Case Study of Wuhan City

Wang Zilin¹(), Li Zhigang¹, Fang Shiming²()

1. School of Urban Design/Hubei Habitat Environment Research Center of Engineering and Technology, Wuhan University, Wuhan 430072, Hubei, China
2. School of Public Administration/Key Laboratory of Legal Evaluation Project of Ministry of Land and Resources, China University of Geosciences (Wuhan), Wuhan 430074, Hubei, China

Received:2021-03-19 Revised:2021-05-24 Online:2022-10-10 Published:2022-12-06
Contact: Fang Shiming E-mail:zilin_wang@whu.edu.cn;fsmcug@qq.com
Supported by:
National Natural Science Foundation of China(41201574);National Natural Science Foundation of China(41771167)

摘要/Abstract

摘要：

以武汉市为例，通过分析生态系统服务价值、生态敏感性、景观连通性及生态需求识别武汉市陆地和水域生态源地，利用遗传算法获取最优生态源地。在此基础上，利用最小累积阻力模型（MCR）分别提取陆地和水域生态廊道，将生态源地与生态廊道叠加构建2017年武汉市生态安全格局。研究表明：2017年武汉市生态源地总面积约为1 917.342 km²，其中陆地和水域生态源地面积分别为780.217 km²和1 137.125 km²；利用遗传算法识别的最优陆地和水域生态源地分别为65和32个，所提取的生态廊道总长度为2 305.37 km，其中陆地和水域生态廊道长度分别为1 497.86 km和807.51 km；武汉市生态安全格局呈现“三横、三纵、三团簇”特征。此外，分别新增了8个陆地和水域生态垫脚石及5个生态源地，运用图论法对比优化前后相关指标，发现优化后可构建更完善的生态安全格局，优化方案可行。该生态安全格局构建与优化方法可为高速发展的大都市的生态安全格局研究提供更科学的参考。

关键词: 生态安全格局, 生态源地, 生态廊道, 遗传算法, 图论法, 武汉

Abstract:

Ecological security pattern is the bridge between ecosystem services and human society development, and it is a healthy spatial pattern of ecosystem existing in landscape. Most of the studies on corridor extraction have insufficient quantitative basis and strong subjectivity. For example, all ecological sources are directly used for the extraction of ecological corridors, or after subjectively eliminating or merging small ecological source areas, the remaining ecological source areas are used to extract ecological corridors, which is easy to cause the problems of corridor redundancy or low credibility. In addition, the research on the optimization of the ecological security pattern is not in-depth enough, which is mainly manifested in the determination of the optimized areas of the ecological security pattern without quantitative analysis of the optimization effect. This paper takes Wuhan City as an example, by analyzing ecosystem service value, ecological sensitivity, landscape connectivity and ecological needs, Wuhan land and water ecological sources were identified. And using genetic algorithm to obtain the optimal ecological source, on this basis, the minimum cumulative resistance model (MCR) was used to extract the land and water ecological corridors, respectively. The ecological source and ecological corridor are superimposed to construct the ecological security pattern of Wuhan in 2017. The results show that in 2017, the total area of ecological source in Wuhan was about 1917.342 km², of which the land and water ecological source areas were 780.217 km² and 1137.125 km², respectively. The number of the optimal land and water ecological sources identified by the genetic algorithm is 65 and 32 respectively. The extracted ecological corridors have a total length of 2 305.37 km, and the length of land and water ecological corridors is 1 497.86 km and 807.51 km, respectively. The ecological security pattern in Wuhan presents the characteristics of “three horizontal, three vertical and three clusters”, and in general, the ecological security pattern can construct a circular intersecting layout of ecological sources. In addition, eight new land ecological stepping stones, 8 new water ecological stepping stones and 5 new ecological sources were added in this paper. The graph theory method was used to compare the relevant indexes before and after optimization, and it was found that a more perfect ecological security pattern could be constructed after optimization, the optimization effect is good and the optimization scheme is feasible. The construction and optimization method of ecological security pattern can provide a more scientific reference for the study of ecological security pattern in rapidly developing metropolises.

Key words: ecological security pattern, ecological sources, ecological corridor, genetic algorithm, graph theory, Wuhan

中图分类号:

X171

王子琳, 李志刚, 方世明. 基于遗传算法和图论法的生态安全格局构建与优化——以武汉市为例[J]. 地理科学, 2022, 42(10): 1685-1694.

Wang Zilin, Li Zhigang, Fang Shiming. Construction and Optimization of Ecological Security Pattern Based on Genetic Algorithm and Graph Theory: A Case Study of Wuhan City[J]. SCIENTIA GEOGRAPHICA SINICA, 2022, 42(10): 1685-1694.

图/表 10

图1

表1

武汉市生态安全格局研究主要数据来源及预处理

数据类型	数据子类	数据来源/年份/精度	数据预处理
注：① http://data. ess.tsinghua. edu.cn/；② https://www.gscloud.cn/search；③ https://www.ngdc.noaa.gov/eog/viirs/download_dnb_composites.html；④ https://www.gscloud.cn/search；⑤ https://max.book118.com/html/2019/0421/8131105010002020.shtm；⑥ http://tjj.wuhan.gov.cn/tjfw/tjnj/；⑦https://tjj.hubei.gov.cn/tjsj/sjkscx/tjnj/qstjnj/；⑧https://www.resdc.cn/；⑨http://data.cma.cn/dataService/cdcindex/datacode/F.0009.0001/show_value/normal.html；⑩ https://www.gscloud.cn/search；⑪ www.openstreet map.org；—为无此项。
土地利用/土地覆被变化（LUCC）数据	—	清华大学地球系统科学中心提供的全球土地覆被数据集①/2017年/30 m×30 m	合并、裁剪、解译
DEM数据	—	地理空间数据云GDE MDE M数字高程数据②/2017年/30 m×30 m	合并、裁剪、提取
夜间灯光数据	—	美国国家海洋大气管理局（NOAA）③/NPP-VIIRS数据/ 2017年/500 m×500 m	裁剪、提取
NDVI数据	—	地理空间数据云 MODIS陆地标准产品④、MOD13Q1/2017年/ 250 m×250 m	合并、裁剪、提取
社会经济数据	粮食价格数据	《中国农产品价格调查年鉴》⑤/2018年/—	进行相关计算
	粮食单产数据	《武汉统计年鉴2018》⑥、《湖北统计年鉴2018》⑦/2018年/—	进行相关计算
	人口数据	中国科学院资源环境数据中心⑧/2015年/—	裁剪
	GDP数据	中国科学院资源环境数据中心⑧/2015年/—	裁剪
气象数据	降雨数据	中国气象数据网⑨/2017年/500 m×500 m	（取7~10月份均值）空间插值、掩膜提取
基础地理数据	水系数据	地理空间数据云⑩、中国内陆水体信息产品	裁剪、提取、缓冲区处理
基础地理数据	道路数据	OpenStreet Map开放共享数据库⑪/2017年/—	裁剪、提取、缓冲区处理

表1

表2

复合维度下的生态源地识别指标系统构建

	维度和指标层	公式	测算方法和技术	指标选取和测算的依据
注：①用地类型包括林地、草地、耕地、湿地、水体、建设用地（价值系数为0）、未利用地共7类；②根据Arnoldus提出的R值方程进行计算^[23]；③水污染敏感性中采用夜间灯光数据指示人类活动强度，考虑到植被和降雪及寒暑假人口流动对灯光数据的影响，最终选择10月份数据进行处理。
生态系统服务价值(ESV)		$ ES{V_i} = \displaystyle\sum {{S_i} \times V{C_i}} $ $ ESV = \displaystyle\sum\limits_i {ES{V_i}} $ 式中，S_i表示土地利用类型^①i的面积大小/hm²，VC_i 是土地利用类型i的生态系统服务价值系数/（元/hm²）	ArcGIS 10.2、生态服务价值当量因子法	[17~19]
生态敏感性	地质灾害敏感性(GHS)	$ GHS = \displaystyle\sum\limits_{i = 1}^n {{X_i} \times {W_i}} $ 式中，X_i为土地利用类型（0.264），植被覆盖率（0.132），坡度（0.089），距主要道路（0.058）、大面积水域（0.162）和小面积水域（0.077）的欧式距离，降雨侵蚀力^②（0.218）7项指标，W_i为采用层次分析法（AHP）确定的权重（括号内值）	ArcGIS 10.2、多指标决策、层次分析法	[20~26]
生态敏感性	水污染敏感性^③(WPS)	$ WPS = {X_1} \times 0.5{\text{ + }}{X_2} \times 0.5 $ 式中，X₁为人类活动强度，X₂为距水域距离影响度，0.5为二者的权重	ArcGIS 10.2、多指标决策、层次分析法	[20~26]
景观连通性	连通性指数(PC)	$ PC = \dfrac{{\displaystyle\sum\limits_{i = 1}^n {\displaystyle\sum\limits_{j = 1}^n {{a_i} \times {a_j} \times {p_{ij}}} } }}{{{A^2}}} $ 式中，a_i、a_j分别为生境斑块i和j的面积，p_ij为生境斑块i与j之间最大连通路径值，A为所有斑块总面积，n为生境斑块数量	ArcGIS 10.2、 Confor Sensinode 2.6、 Confor Inputs for ArcGIS 10.X插件
	连通性指数(PC)			[27,28]
	连通重要性值(dPC)	$ dP{C_i} = 100 \times \dfrac{{PC - P{C_{i - remove}}}}{{PC}} $ 式中，PC_i-remove为去掉生境斑块i后的景观可能连通性指数		[29,30]
生态需求（e）		$e = {x_1} \times \lg{x_2} \times \lg{x_3}$ 式中，x₁是土地开发利用强度，x₂为人口密度，x₃为GDP	ArcGIS 10.2	[11,28]
生态用地被需求程度(E)		$ {E_i} = \dfrac{{{e_i} - {e_{\min }}}}{{{e_{\max }} - {e_{\min }}}} $ 式中，e_i为斑块i的生态需求，e_min为生态需求最小值，e_max为生态需求最大值	ArcGIS 10.2	[11,28]

表2

图2

表3

图3

图4

图5

图6

表4

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陆地生态源地面积/m²	L_s	水域生态源地面积/m²	W_s	源地距所在分区中心的距离/m	L_l或W_l
注：L_s和L_l分别为陆地生态源地的面积和位置赋分；W_s和W_l分别为水域生态源地的面积和位置赋分。
≥1×10⁶	9	≥2.0×10⁵	9	0~1000	9
8×10⁵~1×10⁶	7	1.7×10⁵~2.0×10⁵	7	1000~2 000	7
6×10⁵~8×10⁵	5	1.5×10⁵~1.7×10⁵	5	2 000~3000	5
3×10⁵~6×10⁵	3	1.3×10⁵~1.5×10⁵	3	3000~5000	3
≤3×10⁵	1	≤1.3×10⁵	1	>5000	1

	优化前长度/km	优化后长度/km	优化前平均连通数	优化后平均连通数
陆地生态廊道	1497.86	1480.50	1.38	1.52
水域生态廊道	807.51	822.16	1.19	1.28

	优化前可能连通率	优化后可能连通率	优化前成本消耗度	优化后成本消耗度
陆地生态廊道	0.48	0.70	0.48	0.42
水域生态廊道	0.42	0.64	0.40	0.40

基于遗传算法和图论法的生态安全格局构建与优化——以武汉市为例

Construction and Optimization of Ecological Security Pattern Based on Genetic Algorithm and Graph Theory: A Case Study of Wuhan City

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