THE DENSITY OF VARIOUS ROAD TYPES AND LARCENY RATE: AN EMPIRICAL ANALYSIS OF ZG CITY
LIU Lin1,2, DU Fang-ye1, XIAO Lu-zi1, SONG Guang-wen1, LIU Kai1, JIANG Chao1
1. Center of Integrated Geographic Information Analysis, School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China;
2. Department of Geography, University of Cincinnati, Cincinnati OH 45221-0131, USA
Abstract:Spatial crime patterns have found to be related to street network, yet previous studies have not distinguished the heterogeneous influences of different types of road. Different social and physical environments are attached with different types of road, and they may impose different impacts on the occurrence of crime events. Of all the crime types, larceny is one of the most frequent crimes in the ZG city, and is closely associated with citizens' routine activities and their behavioral environments. Based on the routine activity theory, social disorder theory, crime pattern theory, and rational choice theory, this paper examines the impacts of different types of road on the spatial distribution of larceny with social-physical features taken as control variables. For the analysis, 91990 records of larceny are extracted from the call for services data in the ZG city police department, while the sixth census and points of interest from commercial navigation data sets are collected to represent the social-physical environment of the ZG city. Multiple linear regressions are used to quantitatively test the theoretical expectations. The regression results have confirmed the theoretical expectation that the densities of different types of road have diverse influences on the spatial larceny pattern. The densities of the secondary road, branch road, other vehicle-passable road, and pedestrian road are significantly associated with the larceny rate.
柳林, 杜方叶, 肖露子, 宋广文, 刘凯, 姜超. 不同类型道路密度对公共空间盗窃犯罪率的影响——基于ZG市的实证研究[J]. 人文地理, 2017, 32(6): 32-38,46.
LIU Lin, DU Fang-ye, XIAO Lu-zi, SONG Guang-wen, LIU Kai, JIANG Chao. THE DENSITY OF VARIOUS ROAD TYPES AND LARCENY RATE: AN EMPIRICAL ANALYSIS OF ZG CITY. HUMAN GEOGRAPHY, 2017, 32(6): 32-38,46.
毛媛媛,戴慎志.犯罪空间分布与环境特征——以上海市为例[J]. 城市规划学刊,2006(3):85-93.[Mao Yuanyuan, Dai Shenzhi. Research on spatial and environment characters of crime:Case study of shanghai[J]. Urban Planning Forum, 2006(3):85-93.]
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[29]
Cervero R, Sarmiento O L, Jacoby E, et al. Influences of built environments on walking and cycling:Lessons from Bogotá[J]. International Journal of Sustainable Transportation, 2009,3(4):203-226.
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Cervero R, Sarmiento O L, Jacoby E, et al. Influences of built environments on walking and cycling:Lessons from Bogotá[J]. International Journal of Sustainable Transportation, 2009,3(4):203-226.
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[30]
Wortley R, Mcfarlane M. The role of territoriality in crime prevention:A field experiment[J]. Security Journal, 2011,24(2):149-156.
[31]
王发曾.城市空间环境对城市犯罪的影响[J].人文地理,2001,16(2):1-6.[Wang Fazeng. The urban spatial environment's influences on urban crime[J]. Human Geography, 2001,16(2):1-6.]
[30]
Wortley R, Mcfarlane M. The role of territoriality in crime prevention:A field experiment[J]. Security Journal, 2011,24(2):149-156.
[31]
王发曾.城市空间环境对城市犯罪的影响[J].人文地理,2001,16(2):1-6.[Wang Fazeng. The urban spatial environment's influences on urban crime[J]. Human Geography, 2001,16(2):1-6.]
[37]
Reid A A, Frank R, Iwanski N, et al. Uncovering the spatial patterning of crimes:A criminal movement model(CriMM)[J]. Journal of Research in Crime and Delinquency, 2014,51(2):230-255.
[32]
Zhang W Y, Wei Z W, Wang B H, et al. Measuring mixing patterns in complex networks by Spearman rank correlation coefficient[J]. Physica A:Statistical Mechanics and its Applications, 2016,451(1):440-450.
[26]
Anderson J M, Macdonald J M, Bluthenthal R, et al. Reducing crime by shaping the built environment with zoning:An empirical study of Los Angeles[J]. University of Pennsylvania Law Review, 2013,161(3):699-756.
[33]
张景阳,潘光友.多元线性回归与BP神经网络预测模型对比与运用研究[J].昆明理工大学学报(自然科学版),2013,38(6):61-67.[Zhang Jingyang, Pan Guangyou. Comparison and application of multiple regression and BP neural network prediction model[J]. Journal of Kunming University of Science and Technology(Natural Science Edition), 2013,38(6):61-67.]
[32]
Zhang W Y, Wei Z W, Wang B H, et al. Measuring mixing patterns in complex networks by Spearman rank correlation coefficient[J]. Physica A:Statistical Mechanics and its Applications, 2016,451(1):440-450.
[34]
高建,周丽萍.基于Box-Cox变换的住宅特征价格理论研究[J].河北科技大学学报,2007,28(3):247-250.[Gao Jian, Zhou Liping. Study on housing hedonic price theory based on Box-Cox transformation[J]. Journal of Hebei University of Science and Technology, 2007,28(3):247-250.]
[33]
张景阳,潘光友.多元线性回归与BP神经网络预测模型对比与运用研究[J].昆明理工大学学报(自然科学版),2013,38(6):61-67.[Zhang Jingyang, Pan Guangyou. Comparison and application of multiple regression and BP neural network prediction model[J]. Journal of Kunming University of Science and Technology(Natural Science Edition), 2013,38(6):61-67.]
[34]
高建,周丽萍.基于Box-Cox变换的住宅特征价格理论研究[J].河北科技大学学报,2007,28(3):247-250.[Gao Jian, Zhou Liping. Study on housing hedonic price theory based on Box-Cox transformation[J]. Journal of Hebei University of Science and Technology, 2007,28(3):247-250.]
[35]
左文鼎,夏祥谦,王力宾.Box-Cox变换在Matlab上的实现——以中国汽车特征价格模型为例[J].云南财经大学学报,2007,23(6):116-120.[Zuo Wending, Xia Xiangqian. Box-Cox transformation and its implementation by Matlab-application in Chinas automobile hedonic price model[J]. Journal of Yunnan University of Finance and Economics, 2007,23(6):116-120.]
[35]
左文鼎,夏祥谦,王力宾.Box-Cox变换在Matlab上的实现——以中国汽车特征价格模型为例[J].云南财经大学学报,2007,23(6):116-120.[Zuo Wending, Xia Xiangqian. Box-Cox transformation and its implementation by Matlab-application in Chinas automobile hedonic price model[J]. Journal of Yunnan University of Finance and Economics, 2007,23(6):116-120.]
[36]
王惠文,孟洁.多元线性回归的预测建模方法[J].北京航空航天大学学报,2007,33(4):500-504.[Wang Huiwen, Meng Jie. Predictive modeling on multivariate linear regression[J]. Journal of Beijing University of Aeronautics and Astronautics, 2007,33(4):500-504.]
[36]
王惠文,孟洁.多元线性回归的预测建模方法[J].北京航空航天大学学报,2007,33(4):500-504.[Wang Huiwen, Meng Jie. Predictive modeling on multivariate linear regression[J]. Journal of Beijing University of Aeronautics and Astronautics, 2007,33(4):500-504.]
[27]
Felson M, Cohen L E. Human ecology and crime:A routine activity approach[J]. Human Ecology, 1980,8(4):389-406.
[37]
Reid A A, Frank R, Iwanski N, et al. Uncovering the spatial patterning of crimes:A criminal movement model(CriMM)[J]. Journal of Research in Crime and Delinquency, 2014,51(2):230-255.
[37]
Reid A A, Frank R, Iwanski N, et al. Uncovering the spatial patterning of crimes:A criminal movement model(CriMM)[J]. Journal of Research in Crime and Delinquency, 2014,51(2):230-255.