Road Centrality and Landscape Spatial Patterns in Wuhan Metropolitan Area, China

LIU Yaolin; WANG Huimin; JIAO Limin; LIU Yanfang; HE Jianhua; AI Tinghua

doi:10.1007/s11769-015-0749-y

Road Centrality and Landscape Spatial Patterns in Wuhan Metropolitan Area, China

doi: 10.1007/s11769-015-0749-y

1.
School of Resource and Environment Science, Wuhan University, Wuhan 430079, China;
2.
Key Laboratory of Geographical Information System, Ministry of Education, Wuhan University, Wuhan 430079, China

基金项目: Under the auspices of National Key Technology Research and Development Program of China (No. 2012BAH28B02)

详细信息

通讯作者:
WANG Huimin. E-mail: hmw@whu.edu.cn

Road Centrality and Landscape Spatial Patterns in Wuhan Metropolitan Area, China

1.
School of Resource and Environment Science, Wuhan University, Wuhan 430079, China;
2.
Key Laboratory of Geographical Information System, Ministry of Education, Wuhan University, Wuhan 430079, China

Funds: Under the auspices of National Key Technology Research and Development Program of China (No. 2012BAH28B02)

More Information

Corresponding author: WANG Huimin. E-mail: hmw@whu.edu.cn

摘要: Road network is a corridor system that interacts with surrounding landscapes, and understanding their interaction helps to develop an optimal plan for sustainable transportation and land use. This study investigates the relationships between road centrality and landscape patterns in the Wuhan Metropolitan Area, China. The densities of centrality measures, including closeness, betweenness, and straightness, are calculated by kernel density estimation (KDE). The landscape patterns are characterized by four landscape metrics, including percentage of landscape (PLAND), Shannon's diversity index (SHDI), mean patch size (MPS), and mean shape index (MSI). Spearman rank correlation analysis is then used to quantify their relationships at both landscape and class levels. The results show that the centrality measures can reflect the hierarchy of road network as they associate with road grade. Further analysis exhibit that as centrality densities increase, the whole landscape becomes more fragmented and regular. At the class level, the forest gradually decreases and becomes fragmented, while the construction land increases and turns to more compact. Therefore, these findings indicate that the ability and potential applications of centrality densities estimated by KDE in quantifying the relationships between roads and landscapes, can provide detailed information and valuable guidance for transportation and land-use planning as well as a new insight into ecological effects of roads.
- road centrality /
- landscape patterns /
- kernel density estimation (KDE) /
- landscape metrics /
- Wuhan Metropolitan Area /
- China
Abstract: Road network is a corridor system that interacts with surrounding landscapes, and understanding their interaction helps to develop an optimal plan for sustainable transportation and land use. This study investigates the relationships between road centrality and landscape patterns in the Wuhan Metropolitan Area, China. The densities of centrality measures, including closeness, betweenness, and straightness, are calculated by kernel density estimation (KDE). The landscape patterns are characterized by four landscape metrics, including percentage of landscape (PLAND), Shannon's diversity index (SHDI), mean patch size (MPS), and mean shape index (MSI). Spearman rank correlation analysis is then used to quantify their relationships at both landscape and class levels. The results show that the centrality measures can reflect the hierarchy of road network as they associate with road grade. Further analysis exhibit that as centrality densities increase, the whole landscape becomes more fragmented and regular. At the class level, the forest gradually decreases and becomes fragmented, while the construction land increases and turns to more compact. Therefore, these findings indicate that the ability and potential applications of centrality densities estimated by KDE in quantifying the relationships between roads and landscapes, can provide detailed information and valuable guidance for transportation and land-use planning as well as a new insight into ecological effects of roads.
- road centrality /
- landscape patterns /
- kernel density estimation (KDE) /
- landscape metrics /
- Wuhan Metropolitan Area /
- China

[1]	Anderson T K, 2009. Kernel density estimation and K-means clustering to profile road accident hotspots. Accident Analysis Prevention, 41(3): 359-364. doi: 10.1016/j.aap.2008.12.014
[2]	Barthélemy M, 2011. Spatial networks. Physics Reports, 499(1): 1-101. doi: 10.1016/j.physrep.2010.11.002
[3]	Cai X, Wu Z, Cheng J, 2013. Using kernel density estimation to assess the spatial pattern of road density and its impact on landscape fragmentation. International Journal of Geographical Information Science, 27(2): 222-230. doi: 10.1080/ 13658816.2012.663918
[4]	Carr L W, Fahrig L, Pope S E, 2002. Impacts of landscape transformation by roads. In: Gutzwiller K J (ed). Applying Landscape Ecology in Biological Conservation. New York: Springer, pp. 225-243.
[5]	Castella J C, Manh P H, Kam S P et al., 2005. Analysis of village accessibility and its impact on land use dynamics in a mountainous province of northern Vietnam. Applied Geography, 25(4): 308-326. doi: 10.1016/j.apgeog.2005.07.003
[6]	Chen X, Roberts K A, 2008. Roadless areas and biodiversity: A case study in Alabama, USA. Biodiversity and Conservation, 17(8): 2013-2022. doi: 10.1007/s10531-008-9351-2
[7]	Coffin A W, 2007. From roadkill to road ecology: a review of the ecological effects of roads. Journal of Transport Geography, 15(5): 396-406. doi: 10.1016/j.jtrangeo.2006.11.006
[8]	De Clercq E M, De Wulf R, Van Herzele A, 2007. Relating spatial pattern of forest cover to accessibility. Landscape and Urban Planning, 80(1): 14-22. doi: 10.1016/j.landurbplan.2006.04. 007
[9]	Erath A, Löchl M, Axhausen K W, 2009. Graph-theoretical analysis of the Swiss road and railway networks over time. Networks and Spatial Economics, 9(3): 379-400. doi: 10.1007/ s11067-008-9074-7
[10]	Forman R T T, Alexander L E, 1998. Roads and their major ecological effects. Annual Review of Ecology and Systematics, 29: 207-231. doi: 10.1146/annurev.ecolsys.29.1.207
[11]	Freeman L C, 1979. Centrality in social networks conceptual clarification. Social Networks, 1(3): 215-239. doi: 10.1016/ 0378-8733(78)90021-7
[12]	Fu B, Hu C, Chen L et al., 2006. Evaluating change in agricultural landscape pattern between 1980 and 2000 in the Loess hilly region of Ansai County, China. Agriculture, Ecosystems Environment, 114(2): 387-396. doi: 10.1016/j.agee.2005.11. 012
[13]	Gao J, Li S, 2011. Detecting spatially non-stationary and scale-dependent relationships between urban landscape fragmentation and related factors using geographically weighted regression. Applied Geography, 31(1): 292-302. doi: 10.1016/ j.apgeog.2010.06.003
[14]	Gao S, Wang Y, Gao Y et al., 2013. Understanding urban traffic-low characteristics: A rethinking of betweenness centrality. Environment and Planning B: Planning and Design, 40: 135-153. doi: 10.1068/b38141
[15]	Geurs K T, van Wee B, 2004. Accessibility evaluation of land-use and transport strategies: Review and research directions. Journal of Transport Geography, 12(2): 127-140. doi: 10.1016/j. jtrangeo.2003.10.005
[16]	Hawbaker T J, Radeloff V C, Hammer R B et al., 2005. Road density and landscape pattern in relation to housing density, and ownership, land cover, and soils. Landscape Ecology, 20(5): 609-625. doi: 10.1007/s10980-004-5647-0
[17]	Latora V, Marchiori M, 2007. a measure of centrality based on network efficiency. New Journal of Physics, 9(6): 188. doi: 10.1088/1367-2630/9/6/188
[18]	Laurance W F, Balmford A, 2013. Land use: A global map for road building. Nature, 495(7441): 308-309. doi: 10.1038/ 495308a
[19]	Liang Jun, Liu Ye, Ying Lngxiao et al., 2014. Road impacts on spatial patterns of land use and landscape fragmentation in three parallel rivers region, Yunnan Province, China. Chinese Geographical Science, 24(1): 15-27. doi: 10.1007/s11769-014-0652-y
[20]	Liu Y, Jiao L, Liu Y, 2011. Analyzing the effects of scale and land use pattern metrics on land use database generalization indices. International Journal of Applied Earth Observation and Geoinformation, 13(3): 346-356. doi: 10.1016/j.jag.2011.01.002
[21]	McGarigal K, Cushman S A, Neel M C et al., 2002. FRAGSTATS: spatial pattern analysis program for categorical maps. Available at: http://www.umass.edu/landeco/research/ fragstats/fragstats.html.
[22]	Mitsuda Y, Ito S, 2011. A review of spatial-explicit factors determining spatial distribution of land use/land-use change. Landscape and Ecological Engineering, 7(1): 117-125. doi: 10. 1007/s11355-010-0113-4
[23]	Nagendra H, Munroe, D K, Southworth J, 2004. From pattern to process: Landscape fragmentation and the analysis of land use/land cover change. Agriculture, Ecosystems Environment, 101(2): 111-115. doi: 10.1016/j.agee.2003.09.003
[24]	Patarasuk R, Binford M W, 2012. Longitudinal analysis of the road network development and land-cover change in Lop Buri Province, Thailand, 1989-2006. Applied Geography, 32(2): 228-239. doi: 10.1016/j.apgeog.2011.05.0 09
[25]	Perz S G, Caldas M, Walker R et al., 2008. Road networks and forest fragmentation in the Amazon: Explanations for local differences with implications for conservation and development. Journal of Latin American Geography, 7(2): 85-104. doi: 10.1353/lag.0.0004
[26]	Porta S, Crucitti P, Latora V, 2006. The network analysis of urban streets: a primal approach. Environment and Planning B: Planning and Design, 33(5): 705-725. doi: 10.1068/b32045
[27]	Porta S, Latora V, Wang F et al., 2009. Street centrality and densities of retail and services in Bologna, Italy. Environment and Planning B: Planning and Design, 36(3): 450-465. doi: 10.1068/b34098
[28]	Porta S, Latora V, Wang F et al., 2012. Street centrality and the location of economic activities in Barcelona. Urban Studies, 49(7): 1471-1488. doi: 10.117 7/004209801142 2570
[29]	Rui Y, Ban Y, 2014. Exploring the relationship between street centrality and land use in Stockholm. International Journal of Geographical Information Science, 28(7): 1425-1438. doi: 10.1080/13658816.2014.893347
[30]	Sabidussi G, 1966. The centrality index of a graph. Psychometrika, 31(4): 581-603. doi: 10.1007/BF02289527
[31]	Saunders S C, Mislivets M R, Chen J et al., 2002. Effects of roads on landscape structure within nested ecological units of the Northern Great Lakes Region, USA. Biological Conservation, 103(2): 209-225. doi: 10.1016/S0006-3207(01)00130-6
[32]	Salonen M, Toivonen T, Cohalan J M et al., 2012. Critical distances: comparing measures of spatial accessibility in the riverine landscapes of Peruvian Amazonia. Applied Geography, 32(2): 501-513. doi: 10.1016/j.apgeog.2011.0 6.017
[33]	Saura S, Torras O, Gil-Tena A et al., 2008. Shape irregularity as an indicator of forest biodiversity and guidelines for metric selection. In: Lafortezza R et al. (eds). Patterns and Processes in Forest Landscapes. New York: Springer, pp. 167-189.
[34]	Sevtsuk A, Mekonnen M, 2012. Urban network analysis. A new toolbox for ArcGIS. Revue Internationale de Géomatique, 22(2): 287-305. doi: 10.3166/rig.22.287-305
[35]	Sheikh M Z A, Rajabi M A, 2013. Analyzing the effect of the street network configuration on the efficiency of an urban transportation system. Cities, 31(1): 285-297. doi: 10.1016/ j.cities.2012.08.008
[36]	Su S, Xiao R, Li D, 2014. Impacts of transportation routes on landscape diversity: a comparison of different route types and their combined effects. Environmental Management, 53(3): 636-647. doi: 10.1007/s00267-013-0214-6.
[37]	Tyrväinen L, Uusitalo M, Silvennoinen H et al., 2014. Towards sustainable growth in nature-based tourism destinations: clients' views of land use options in Finnish Lapland. Landscape and Urban Planning, 122(1): 1-15. doi: 10.1016/j.landurbplan.2013.10.003
[38]	Wang F, Antipova A, Porta S, 2011. Street centrality and land use intensity in Baton Rouge, Louisiana. Journal of Transport Geography, 19(2): 285-293. doi: 10.1016/j.jtrangeo.2010.01. 004
[39]	Wang F, Chen C, Xiu C et al., 2014. Location analysis of retail stores in Changchun, China: a street centrality perspective. Cities, 41(1): 54-63. doi: 10.1016/j.cities.2014.05.005
[40]	Ying Lingxiao, Shen Zehao, Chen Jiding et al., 2014. Spatiotemporal patterns of road network and road development priority in Three Parallel Rivers Region in Yunnan, China: an evaluation based on modified kernel distances estimate. Chinese Geographical Science, 24(1): 39-49. doi: 10.1007/s11769-014-0654-9

[1]	ZHANG Suwen, LI Chenggu, MA Zuopeng, LI Xin. Influences of Different Transport Routes and Road Nodes on Industrial Land Conversion: A Case Study of Changchun City of Jilin Province, China . Chinese Geographical Science, 2020, 30(3): 544-556. doi: 10.1007/s11769-020-1126-z
[2]	LI Jinfeng, XU Haicheng, LIU Wanwan, WANG Dongfang, ZHOU Shuang. Spatial Pattern Evolution and Influencing Factors of Cold Storage in China . Chinese Geographical Science, 2020, 30(3): 505-515. doi: 10.1007/s11769-020-1124-1
[3]	WANG Fahui, LIU Cuiling, XU Yaping. Analyzing Population Density Disparity in China with GIS-automated Regionalization: The Hu Line Revisited . Chinese Geographical Science, 2019, 20(4): 541-552. doi: 10.1007/s11769-019-1054-y
[4]	XIAO Yang, OUYANG Zhiyun. Spatial-temporal Patterns and Driving Forces of Water Retention Service in China . Chinese Geographical Science, 2019, 20(1): 100-111. doi: 10.1007/s11769-018-0984-0
[5]	MA Zhenbang, CHEN Xingpeng, CHEN Huan. Multi-scale Spatial Patterns and Influencing Factors of Rural Poverty: A Case Study in the Liupan Mountain Region, Gansu Province, China . Chinese Geographical Science, 2018, 28(2): 296-312. doi: 10.1007/s11769-018-0943-9
[6]	LIU Daqian, LO Kevin, SONG Wei, XIE Chunyan. Spatial Patterns of Car Sales and Their Socio-economic Attributes in China . Chinese Geographical Science, 2017, 27(5): 684-696. doi: 10.1007/s11769-017-0902-x
[7]	JU Hongrun, ZHANG Zengxiang, WEN Qingke, WANG Jiao, ZHONG Lijin, ZUO Lijun. Spatial Patterns of Irrigation Water Withdrawals in China and Implications for Water Saving . Chinese Geographical Science, 2017, 27(3): 362-373. doi: 10.1007/s11769-017-0871-0
[8]	XU Xinliang, CAI Hongyan, QIAO Zhi, WANG Liang, JIN Cui, GE Yaning, WANG Luyao, XU Fengjiao. Impacts of Park Landscape Structure on Thermal Environment Using QuickBird and Landsat Images . Chinese Geographical Science, 2017, 27(5): 818-826. doi: 10.1007/s11769-017-0910-x
[9]	ZHANG Shaoliang, JIANG Lili, LIU Xiaobing, ZHANG Xingyi, FU Shicong, DAI Lin. Soil Nutrient Variance by Slope Position in a Mollisol Farmland Area of Northeast China . Chinese Geographical Science, 2016, 26(4): 508-517. doi: 10.1007/s11769-015-0737-2
[10]	WANG Chengjin, César DUCRUET, WANG Wei. Port Integration in China: Temporal Pathways, Spatial Patterns and Dynamics . Chinese Geographical Science, 2015, 25(5): 612-628. doi: 10.1007/s11769-015-0752-3
[11]	YING Lingxiao, SHEN Zehao, CHEN Jiding, FANG Rui, CHEN Xueping, JIANG Rui. Spatiotemporal Patterns of Road Network and Road Development Priority in Three Parallel Rivers Region in Yunnan, China：An Evaluation Based on Modified Kernel Distance Estimate . Chinese Geographical Science, 2014, 0(1): 39-49. doi: 10.1007/s11769-014-0654-9
[12]	DU Jia, SONG Kaishan, WANG Zongming, ZHANG Bai, LIU Dianwei. Evapotranspiration Estimation Based on MODIS Products and Surface Energy Balance Algorithms for Land (SEBAL) Model in Sanjiang Plain, Northeast China . Chinese Geographical Science, 2013, 23(1): 73-91.
[13]	CHANG Qing1, LI Shuangcheng2, WANG Yanglin2, WU Jiansheng3, XIE Miaomiao4. Spatial Process of Green Infrastructure Changes Associated with Rapid Urbanization in Shenzhen, China . Chinese Geographical Science, 2013, 23(1): 113-128.
[14]	LIU Zigang1, WANG Ming2, 3, MA Xuehui2. Estimation of Storage and Density of Organic Carbon in Peatlands of China . Chinese Geographical Science, 2012, 22(6): 637-646.
[15]	SU Changhong, FU Bojie, LU Yihe, et al.. Land Use Change and Anthropogenic Driving Forces: A Case Study in Yanhe River Basin . Chinese Geographical Science, 2011, 21(5): 587-.
[16]	ZONG Yueguang, YANG Wei, MA Qiang, XUE Song. Cassini Growth of Population Between Two Metropolitan Cities——A Case Study of Beijing-Tianjin Region, China . Chinese Geographical Science, 2009, 19(3): 203-210. doi: 10.1007/s11769-009-0203-0
[17]	WANG Kaiyong, GAO Xiaolu, CHEN Tian. Influencing Factors for Formation of Urban and Rural Spatial Structure in Metropolis Fringe Area——Taking Shuangliu County of Chengdu in China as a Case . Chinese Geographical Science, 2008, 18(3): 224-234. doi: 10.1007/s11769-008-0224-0
[18]	FANG Yangang, LIU Jisheng. Cultural Landscape Evolution of Traditional Agricultural Villages in North China——Case of Qianzhai Village in Shandong Province . Chinese Geographical Science, 2008, 18(4): 308-315. doi: 10.1007/s11769-008-0308-x
[19]	KONG Fan-hua, Nobukazu NAKAGOSHI, YIN Hai-wei, Akira KIKUCHI. SPATIAL GRADIENT ANALYSIS OF URBAN GREEN SPACES COMBINED WITH LANDSCAPE METRICS IN JINAN CITY OF CHINA . Chinese Geographical Science, 2005, 15(3): 254-261.
[20]	钱步东. PRECIPITATION PATTERNS IN FLOOD SEASON OVER CHINA ASSOCIATED WITH THE EL NI?O/SOUTHERN OSCILlATION . Chinese Geographical Science, 1997, 7(3): 220-228.

点击查看大图

计量

文章访问数: 567
HTML全文浏览量: 18
PDF下载量: 1529
被引次数: 0

姓名
邮箱
手机号码
标题
留言内容
验证码

留言板

Road Centrality and Landscape Spatial Patterns in Wuhan Metropolitan Area, China

doi: 10.1007/s11769-015-0749-y

通讯作者:
WANG Huimin. E-mail: hmw@whu.edu.cn

Road Centrality and Landscape Spatial Patterns in Wuhan Metropolitan Area, China

Corresponding author: WANG Huimin. E-mail: hmw@whu.edu.cn

计量

Road Centrality and Landscape Spatial Patterns in Wuhan Metropolitan Area, China

doi: 10.1007/s11769-015-0749-y

1. School of Resource and Environment Science, Wuhan University, Wuhan 430079, China;

2. Key Laboratory of Geographical Information System, Ministry of Education, Wuhan University, Wuhan 430079, China

通讯作者: WANG Huimin. E-mail: hmw@whu.edu.cn

English Abstract

Road Centrality and Landscape Spatial Patterns in Wuhan Metropolitan Area, China

1. School of Resource and Environment Science, Wuhan University, Wuhan 430079, China;

2. Key Laboratory of Geographical Information System, Ministry of Education, Wuhan University, Wuhan 430079, China

Corresponding author: WANG Huimin. E-mail: hmw@whu.edu.cn

全文HTML

目录

留言板

Road Centrality and Landscape Spatial Patterns in Wuhan Metropolitan Area, China

doi: 10.1007/s11769-015-0749-y

通讯作者: WANG Huimin. E-mail: hmw@whu.edu.cn

Road Centrality and Landscape Spatial Patterns in Wuhan Metropolitan Area, China

Corresponding author: WANG Huimin. E-mail: hmw@whu.edu.cn

计量

出版历程

Road Centrality and Landscape Spatial Patterns in Wuhan Metropolitan Area, China

doi: 10.1007/s11769-015-0749-y

1. School of Resource and Environment Science, Wuhan University, Wuhan 430079, China; 2. Key Laboratory of Geographical Information System, Ministry of Education, Wuhan University, Wuhan 430079, China

通讯作者: WANG Huimin. E-mail: hmw@whu.edu.cn

English Abstract

Road Centrality and Landscape Spatial Patterns in Wuhan Metropolitan Area, China

1. School of Resource and Environment Science, Wuhan University, Wuhan 430079, China; 2. Key Laboratory of Geographical Information System, Ministry of Education, Wuhan University, Wuhan 430079, China

Corresponding author: WANG Huimin. E-mail: hmw@whu.edu.cn

全文HTML

目录

通讯作者:
WANG Huimin. E-mail: hmw@whu.edu.cn

1. School of Resource and Environment Science, Wuhan University, Wuhan 430079, China;

2. Key Laboratory of Geographical Information System, Ministry of Education, Wuhan University, Wuhan 430079, China

1. School of Resource and Environment Science, Wuhan University, Wuhan 430079, China;

2. Key Laboratory of Geographical Information System, Ministry of Education, Wuhan University, Wuhan 430079, China