Research on spatial scale effect of landscape pattern of land use in Wuhan City

doi:10.3969/j.issn.1004-9479.2020.01.2018370

Abstract

Abstract:

The study of landscape pattern of urban land use has theoretical value and practical significance in urban planning and management of land resource, the choice of research scale is an indispensable part. We take Wuhan as the study area and analyze the landscape pattern of land use with indices from three different types (index of aggregation and dispersion, index of plaque type and index of shape).Then we discuss the scale effect and response characteristics of the land use pattern. The results show that as the spatial scale increases, the degree of landscape fragmentation increases, the distribution of landscape became more dispersed, the landscape heterogeneity decreased, and the connectivity between patches become weaker and weaker. On this foundation, we develop the model of optimal scale selection to select the optimal scale in land use pattern research, and check the rationality based on fractal theory. Consequently we come to the conclusion that the optimal scale of the landscape pattern of land use in Wuhan is 60 m.

Key words: Wuhan city, land use pattern, landscape index, scale effect, fractal theory

摘要：

城市土地利用景观格局研究对城市规划设计和土地资源管理具有重要的理论价值和现实意义，而研究尺度的选择是其必不可少的部分。本文基于景观生态学方法，以武汉市为研究区域，选取聚集分散指数、斑块类型指数、形状指数三种类型指数对土地利用景观格局进行分析，同时引入层次分析法，研究武汉市土地利用景观格局的空间尺度效应及其响应特征，结果表明武汉市土地利用景观格局具有明显的空间尺度效应，随着空间尺度的增大，景观破碎程度增大，景观分布越来越分散，景观异质性减小，斑块之间连接度越来越弱。在此基础上，建立最佳尺度选择模型，并基于分型理论对最佳尺度的合理性进行验证，最终得出武汉市土地利用景观格局研究的最佳空间尺度为60 m。

关键词: 武汉市, 土地利用格局, 景观指数, 尺度效应, 分形理论

Lu WANG, Yanbin YUAN, Heng DONG, Jiejun HUANG, Peng HUANG, Chengfang ZHANG. Research on spatial scale effect of landscape pattern of land use in Wuhan City[J]. World Regional Studies, 2020, 29(1): 96-103.

王璐, 袁艳斌, 董恒, 黄解军, 黄鹏, 张城芳. 土地利用景观格局空间尺度效应研究[J]. 世界地理研究, 2020, 29(1): 96-103.

Figures/Tables 8

Fig.1 Land use map of Wuhan

Tab.1 Ecological meaning and change law of landscape index

景观指数	生态学意义	变化规律
蔓延度 (CONTAG)	反映景观系统中各景观的聚集分散程度	蔓延度越大，表明景观中的斑块具有良好的连接；反之，表明斑分布较为分散。
斑块聚合度 (AI)	根据斑块像元间的公共边界的长度判断斑块的聚集分散程度	像元间存在的公共边界的长度越小，聚合度越小；公共边界越大，则斑块聚合度越大。
结构连接度指数 (COHESION)	反映斑块之间距离和排列格局对景观结构的影响，表示景观在空间上的表观连续性	结构连接度指数越大，说明斑块之间的连续性越强，关联越紧密；结构连接度指数越小，说明斑块之间的越分散。
香农多样性指数 (SHDI)	基于信息论反映景观异质性，反映景观中不同斑块类型的分布均衡情况	土地利用越丰富，破碎化程度越大，含有的信息量就越大，香农多样性指数也就越高。
香农均匀度指数 (SHEI)	反应景观结构组成的复杂性	香农均匀度指数较小时，说明景观受到一种或少数几种优势斑块类型支配；香农均匀度指数较大时，各斑块类型在景观中分布较为均匀。
形状指数 (LSI)	通过计算斑块与相同面积的圆或正方形的形状偏离程度反映斑块的形状复杂程度	形状指数越大说明景观系统中斑块形状越不规则；形状指数越小，说明斑块形状越接近于正方形。

Tab.2 Landscape index values at different spatial scales

Scale/m	CONTAG	AI	COHESION	SHDI	SHEI	LSI
30	45.1069	88.3851	99.6478	1.208	0.7511	114.3700
60	39.0276	81.0928	99.4803	1.2089	0.7511	93.1706
90	35.2539	75.7786	99.2959	1.209	0.7512	79.6749
120	33.0691	72.3743	99.2517	1.2091	0.7513	68.2444
150	31.6206	69.9873	99.0684	1.2088	0.7511	59.4198
180	30.7179	68.3742	98.8674	1.2088	0.7511	52.2208
210	29.8436	66.9492	98.7525	1.2087	0.751	46.8745
240	29.2084	65.7204	98.5608	1.2085	0.7509	42.5498
270	28.5222	64.6496	98.3346	1.2089	0.7512	39.1109
300	28.2151	63.9924	98.3162	1.2085	0.7509	35.8594

Fig.2 Response of landscape index to spatial scale

Fig.3 Analytic hierarchy model

Tab.3 Standardized values of landscape index at different spatial scales

Scale/m	CONTAG	AI	COHESION	SHDI	SHEI	LSI
30	1.00	1.00	1.00	0.50	0.50	1.00
60	0.64	0.70	0.87	0.67	0.50	0.73
90	0.42	0.48	0.74	0.83	0.75	0.56
120	0.29	0.34	0.70	1.00	1.00	0.41
150	0.20	0.25	0.56	0.50	0.50	0.30
180	0.15	0.18	0.41	0.50	0.50	0.21
210	0.10	0.12	0.33	0.33	0.25	0.14
240	0.06	0.07	0.18	0.00	0.00	0.09
270	0.02	0.03	0.01	0.67	0.75	0.04
300	0.00	0.00	0.00	0.00	0.00	0.00

Tab.4 Amplitude of change in landscape index and fractal dimension at different spatial scales

Scale/m	60	90	120	150	180	210	240	270	300
$λ i$	0.27	0.19	0.14	0.15	0.07	0.08	0.09	0.13	0.11
分维数	0.054	0..32	0.012	0.010	0.004	0.008	0.000	0.006	0.004

Tab.4 Amplitude of change in landscape index and fractal dimension at different spatial scales

Scale/m	60	90	120	150	180	210	240	270	300
$λ i$	0.27	0.19	0.14	0.15	0.07	0.08	0.09	0.13	0.11
分维数	0.054	0..32	0.012	0.010	0.004	0.008	0.000	0.006	0.004

Tab.5 Result of fractal model

Scale/m	方程	R方	分维数
30	y=0.638x+0.434	0.988	1.276
60	y=0.665x+0.18	0.988	1.330
90	y=0.681x-0.261	0.989	1.362
120	y=0.687x-0.422	0.989	1.374
150	y=0.692x-0.554	0.989	1.384
180	y=0.694x-0.647	0.989	1.388
210	y=0.698x-0.746	0.989	1.396
240	y=0.698x-0.805	0.990	1.396
270	y=0.701x-0.881	0.989	1.402
300	y=0.703x-0.950	0.989	1.406

References 17

1	田义超, 陈志坤, 梁铭忠, 等. 土地利用最佳模拟尺度选择及空间格局模拟. 计算机工程与应用, 2014,50(24):244-249.
	Tian Y, Chen Z, Liang M, et al. Selection of land use best simulation scale and patterns of spatial simulation. Computer Engineering and Applications, 2014, 50(24):244-249.
2	周俊菊,张恒玮, 张利利, 等. 综合治理前后民勤绿洲景观格局时空演变特征.干旱区研究, 2017,34(1):79-87.
	Zhou J, Zhang H, Zhang L, et al. Spatio-temporal evolution of landscape pattern in the Minqin Oasis before and after implementing the comprehensive management. Arid Zone Research, 2017,34(1):79-87.
3	Corry R C, Lafortezza R. Sensitivity of landscape measurements to changing grain size for fine-scale design and management. Landscape & Ecological Engineering, 2007,3(1):47-53.
4	陈利顶, 李秀珍, 傅伯杰, 等. 中国景观生态学发展历程与未来研究重点.生态学报, 2014,34(12):3129-3141.
	Chen L，Li X，Fu B, et al. Development history and future research priorities of landscape ecology in China． Acta Ecologica Sinica，2014,34( 12): 3129-3141.
5	Šímová P, Gdulová K. Landscape indices behavior: A review of scale effects. Applied Geography, 2012,34:385-394.
6	赵秀丽, 侯英姿, 张闯, 等. 基于GIS/RS的滨海湿地景观空间格局多尺度分析. 安徽农业科学, 2016,44(2):139-141.
	Zhao X, Hou Y, Zhang C, et al. Multi-scale analysis of coastal wetland landscape pattern based on GIS/RS.Journal of Anhui Agri.Sci.,2016,44(2):139-141.
7	肖艳芳,张杰,马毅,等. 基于“资源三号”卫星的黄河口湿地景观格局及其空间尺度效应分析.海洋科学, 2015,39 (2):35-42.
	Xiao Y, Zhang J, Ma Y, et al. Landscape pattern and scale effect of Yellow River Estuarine wetland based on ZY-3 Satellite.Marine Sciences,2015,39(2):35-42.
8	陈雷, 刘玉龙, 李宝强, 等. 基于3S技术的景观格局指数空间尺度效应变化研究. 能源环境保护, 2014,28(5):28-32.
	Chen L, Liu Y, Li B, et al. The landscape pattern index changes of spatial scales effects based on 3S technology. Energy Environmental Protection, 2014,28(5):28-32.
9	陈永林,谢炳庚,李晓青.长沙市土地利用格局变化的空间粒度效应.地理科学,2016,36(4):564-570.
	Chen Y, Xie B, Li X.Spatial Grain, size effect on land use pattern changes in Changsha City.Scientia Geographica Sinica,2016,36(4):564-570.
10	刘媛媛, 刘学录. 甘肃永登县土地利用景观格局的空间尺度效应. 应用生态学报, 2016,27(4):1221-1228.
	LIu Y, Liu X. Spatial scale effect of land use landscape pattern in Yongdeng County, Gansu Province, China. Chinese Journal of Applied Ecology, 2016,27(4):1221-1228.
11	Zhao Y, Murayama Y. Effect of spatial scale on urban land-use pattern analysis in different classification systems: An empirical study in the CBD of Tokyo. Theory and Applications of GIS, 2006,14(1):29-42.
12	陈文波,肖笃宁,李秀珍.景观指数分类、应用及构建研究.应用生态学报,2002,13(1):121-125.
	Chen W, Xiao D, Li X.Classification,application and creation of landscape indices.Chinese Journal of Applied Ecology,2002,13(1):121-125.
13	邓雪, 李家铭, 曾浩健, 等. 层次分析法权重计算方法分析及其应用研究. 数学的实践与认识, 2012,42(7):93-100.
	Deng X, Li J, Zeng H, et al. Research on computation methods of AHP wight vector and its applications. Mathematics in Practice and Theory, 2012,42(7):93-100.
14	王爽, 王卫星. 基于高校内涵发展的财务评价指标体系构建. 财会通讯, 2015(13):69-71.
	Wang S, Wang W. Construction of financial evaluation index system based on the connotation development of colleges and universities. Finance and Accounting Communications, 2015(13):69-71.
15	曹雅坤. 基于分形维数和信息熵的土地利用景观格局变化研究——以西安市为例. 地下水, 2012,34(4):152-154.
	Cao Y. The change of Landscape pattern of land use Based on fractal dimension and entropy--a case study of Xian city. Ground water, 2012,34(4):152-154.
16	郭朝伟,邓小菲.绵阳市梓潼县土地利用景观格局变化分析.绵阳师范学院报,2011,30(5):92-99.
	Guo C,Deng X. On changes of landscape patterns of land use at Zitong County.Journal of Mianyang Normal University,2011,30(5):92-99.
17	贾科利,张俊华,常庆瑞.基于信息熵与分形理论的土地利用景观格局变化研究——以陕北农牧交错带为例.干旱地区农业研究,2009,27(5):235-250.
	Jia K, ZHang J, Chang Q. Land use landscape pattern changes based on information entropy and fractal theory--A case study of the farming-pastoral region of northern Shaanxi. Agricultural Research in the Arid Areas, 2009,27(5):235-250.