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浙江大学学报(理学版)  2022, Vol. 49 Issue (2): 219-228    DOI: 10.3785/j.issn.1008-9497.2022.02.011
地球科学     
城市新区犯罪数量与犯罪危害程度空间分异规律研究
李琛1(),吴映梅1(),高彬嫔1,郑可君1,2,武燕1
1.云南师范大学 地理学部,云南 昆明 650500
2.云南省社会科学院,云南 昆明 650000
Research on the spatial differentiation of crime quantity and harm degree in new urban districts
Chen LI1(),Yingmei WU1(),Binpin GAO1,Kejun ZHENG1,2,Yan WU1
1.Faculty of Geography,Yunnan Normal University,Kunming 650500,China
2.Yunnan Academy of Social Sciences,Kunming 650000,China
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摘要:

立足新发展阶段,统筹平安和发展,建设更高水平的平安法治文明城市。以昆明市呈贡区为例,综合运用核密度估计法、犯罪集中度、空间自相关分析、标准差椭圆法等GIS方法,分析2015、2017、2019年的犯罪数量与犯罪危害程度空间分异规律。结果表明:(1)犯罪数量的空间格局以城市核心区集聚为主,高密度和较高密度集聚区主要分布于交通便捷、经济活动频繁、人员密集的老城区、商业中心及大学城周围居住区。犯罪危害程度在空间上形成龙城片区“单核心”的格局并未被打破,且高密度集聚区的空间分布与犯罪数量的空间分布相似,较高密度集聚区相对分散,较低密度集聚区渐呈“散点状”分布。(2)犯罪数量和犯罪危害程度均表现出显著的集中分布和空间集聚格局。二者空间集中差异逐渐加大,犯罪危害日趋集中的态势更强烈;空间集聚差异变化明显。(3)犯罪数量与犯罪危害程度热点区存在明显的空间分布差异,随新区建设的发展,各犯罪热点区逐渐破碎化。犯罪数量与犯罪危害程度热点重合区位于呈贡区中部,沿城市主干道和地铁线路分布;犯罪数量热点区分布于学校、医院及商业中心附近;犯罪危害程度热点区分布于城郊乡镇、城中村、工业园区、物流园区、施工工地等区域。(4)犯罪数量和犯罪危害程度的扩散方向与城市空间扩展方向密切相关,且随城市发展逐渐趋于一致,其中,犯罪危害程度扩散更明显,更易随城市空间结构变化而改变。

关键词: 犯罪地理学犯罪危害空间分异城市新区    
Abstract:

During the new stage of development, it is important to coordinate safety and development to build a higher level of safe and civilized cities under the rule of law. Taking Chenggong district of Kunming as an example, this paper comprehensively uses GIS analysis methods such as nuclear density, crime concentration, spatial autocorrelation and standard deviation ellipse to analyze the spatial differentiation of crime quantity and harm degree in the study area in 2015, 2017 and 2019. The results show that: (1) The spatial pattern of crimes in Chenggong district is dominated by urban core areas. High-density agglomeration areas and less high-density agglomeration areas are mainly distributed in old urban areas and commercial centers with convenient transportation, frequent economic activities, and dense populations as well as the residential areas around the university town. The spatial pattern of the "single core" of the Longcheng area regarding the degree of criminal harm still exists, and the distribution of high-density agglomeration areas of criminal harm is similar to that of the number of crimes. Nevertheless, the less high-density agglomeration areas of criminal harm are relatively scattered, and the distribution of low-density agglomeration areas appears gradually as "scattered dots". (2) Both the number of crimes and the degree of crime harm in Chenggong district in the specified years showed significant concentrated distribution and spatial agglomeration patterns. The difference in spatial concentration between the two was gradually increasing, and the situation distribution of criminal harm become more concentrated. (3) There are obvious spatial distribution differences between the number of crimes and the degree of crime harm in the hot spots. With the development of the new district, the crime hot spots gradually become fragmented. The hot spots of crime number and degree of harm were located in the middle of Chenggong district, along the main roads and subway lines of the city; in particular, the hot spots regarding the number of crimes are more likely located near schools, hospitals and commercial centers; and the hot spots of crime harm degree are more likely located in suburbs, towns, villages in cities, industrial parks, logistics parks, construction sites and other areas. (4) The spatial distribution of both the number of crimes and the degree of crime harm are closely related to the direction of urban space expansion. Among them, the distribution of the degree of crime harm is more obvious, and its spatial spread is more likely to follow the change in the urban spatial structure.

Key words: criminal geography    criminal harm    spatial differentiation    new urban districts
收稿日期: 2021-03-10 出版日期: 2022-03-22
CLC:  F129.9  
基金资助: 国家自然科学基金资助项目(41761037);云南省哲学社会科学创新团队科研项目(2021tdxmy04);云南省哲学社会科学规划社会智库项目(SHZK2021415)
通讯作者: 吴映梅     E-mail: lichen5112@qq.com;wuyingmei@hotmail.com
作者简介: 李琛(1998—),ORCID:https://orcid.org/0000-0002-4627-6841,男,硕士研究生,主要从事区域经济开发与管理研究,E-mail:lichen5112@qq.com.
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引用本文:

李琛,吴映梅,高彬嫔,郑可君,武燕. 城市新区犯罪数量与犯罪危害程度空间分异规律研究[J]. 浙江大学学报(理学版), 2022, 49(2): 219-228.

Chen LI,Yingmei WU,Binpin GAO,Kejun ZHENG,Yan WU. Research on the spatial differentiation of crime quantity and harm degree in new urban districts. Journal of Zhejiang University (Science Edition), 2022, 49(2): 219-228.

链接本文:

https://www.zjujournals.com/sci/CN/10.3785/j.issn.1008-9497.2022.02.011        https://www.zjujournals.com/sci/CN/Y2022/V49/I2/219

图1  研究区区位示意
图2  2015—2019年呈贡区犯罪数量核密度空间分布(a)2015年 (b)2017年 (c)2019年
图3  2015—2019年呈贡区犯罪危害程度核密度空间分布(a)2015年 (b)2017年 (c)2019年
年份数量或平均危害程度累积25%的网格比重/%累积50%的网格比重/%Moran's I
犯罪数量20153240.351.370.250
20173590.281.310.175
20192170.351.370.176

犯罪危害

程度

201521.3590.331.310.201
201717.3120.331.110.130
201915.0510.301.110.196
表1  呈贡区犯罪数量及犯罪危害程度网格的集中程度和Moran's I值
图4  2015—2019年呈贡区犯罪数量和犯罪危害程度热点区空间分布(a)2015年 (b)2017年 (c)2019年
图5  2015—2019年呈贡区犯罪数量和犯罪危害程度的SDE(a)2015年 (b)2017年 (c)2019年
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