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Journal of Geographical Sciences    2015, Vol. 25 Issue (12) : 1521-1536     DOI: 10.1007/s11442-015-1249-9
Research Articles |
A spatial-temporal analysis of urban recreational business districts: A case study in Beijing, China
ZHU He1,2,3,LIU Jiaming1,2,*(),CHEN Chen4,LIN Jing1,2,3,TAO Hui1,2,3,5
1. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
2. Key Laboratory of Regional Sustainable Development Modeling, CAS, Beijing 100101, China
3. University of Chinese Academy of Sciences, Beijing 100049, China
4. College of Water Resources & Civil Engineering, China Agricultural University, Beijing 100083, China
5. Institute of Economics and Management, Hubei Minzu University, Enshi 445000, Hubei, China
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Abstract  

This study has revealed spatial-temporal changes in Recreational Business Districts (RBDs) in Beijing and examined the relationship between the location of urban RBDs and traffic conditions, resident and tourist density, scenic spots, and land prices. A more reasonable classification of urban RBDs (LSC, CPS, and ULA) is also proposed. Quantitative methods such as Gini Coefficient, Spatial Interpolation, Kernel Density Estimation, and Geographical Detector were employed to collect and analyze the data from three types of urban RBDs in Beijing in 1990, 2000, and 2014, respectively, and the spatial-temporal patterns as well as the distribution characteristics of urban RBDs were analyzed using ArcGIS software. It was concluded that (1) both the number and scale of urban RBDs in Beijing have been expanding and the trend for all types of urban RBDs in Beijing to be spatially agglomerated is continuing; (2) the spatial-temporal evolution pattern of urban RBDs in Beijing is “single-core agglomeration-dual-core agglomeration-multi-core diffusion”; and (3) urban RBDs were always located in areas with low traffic density, tourist attractions, high resident and tourist population density, and relatively high land valuations; these factors also affect the scale size of RBDs.
Keywords urban RBD      spatial-temporal pattern      distribution characteristics      Beijing     
Fund:National Natural Science Foundation of China, No.41071110
Issue Date: 05 January 2016
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ZHU He
LIU Jiaming
CHEN Chen
LIN Jing
TAO Hui
Cite this article:   
ZHU He,LIU Jiaming,CHEN Chen, et al. A spatial-temporal analysis of urban recreational business districts: A case study in Beijing, China[J]. Journal of Geographical Sciences, 2015, 25(12): 1521-1536.
URL:  
http://www.geogsci.com/EN/10.1007/s11442-015-1249-9     OR     http://www.geogsci.com/EN/Y2015/V25/I12/1521
Figure 1  The study area in Beijing
Year LSC CPS ULA Total
Number Scale (km2) Number Scale (km2) Number Scale (km2) Number Scale (km2)
1990 2 0.0149 13 0.3289 0 0 15 0.3439
2000 13 0.3449 16 2.5125 4 1.0920 33 3.9494
2014 37 2.3953 40 6.3984 11 4.6648 88 13.4584
Table 1  Statistics of urban RBDs in Beijing in 1999, 2000 and 2014
Year
1990 2000 2014
Gini Coefficient of LSCs 0.5015 0.5280 0.5949
Gini Coefficient of CPSs 0.5228 0.5402 0.5998
Gini Coefficient of ULAs - 0.5079 0.5287
Table 2  Gini Coefficient variation of urban RBDs in Beijing
Figure 2  Density distribution of urban RBDs in Beijing in 1990, 2000 and 2014
Figure 3  Classification and distribution of urban RBDs in Beijing based on traffic conditions
Figure 4  Relationship between urban RBDs and population density in Beijing
Figure 5  Relationship between urban RBDs and tourist density in Beijing
Figure 6  Relationship between urban RBDs and land valuations in Beijing
2000 2014
LSC CPS ULA LSC CPS ULA
Traffic conditions 0.11 b 0.24 0.38 b 0.07 b 0.05 b 0.14
Inhabitant density 0.34 a 0.21 0.41 b 0.27 a 0.08 b 0.24
Tourist density 0.45 a 0.28 0.44 b 0.29 a 0.36 a 0.32
Distance from attractions 0.20 b 0.21 0.72 a 0.14 b 0.03 b 0.43
Land prices 0.07 b 0.21 0.41 b 0.09 b 0.08 b 0.27
Table 3  Spatial factors influencing the scale size of RBDs
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