Spatial conjunctive analysis of (crime) case configurations: Using Monte Carlo methods for significance testing

While research has repeatedly demonstrated how spatial distributions of crime can be shaped by the presence of facilities such as bars and public transport hubs, the joint influence of different facility types has rarely been explored. Spatial conjunctive analysis of case configurations (also known as qualitative comparative analysis) offers a means to identify the combinations of facility types that are most commonly found around crime events, and has been used in a small number of studies focusing on street robbery. This study extends this limited evidence base by implementing a significance test based on the Monte Carlo method using street robbery data for Austin, Texas. The results show that some of the top-ranking facility type combinations had observed frequencies that were not significantly greater than chance expectations. The accurate identification of the highest-risk environments has important implications for crime prevention.     

街头抢劫者前犯罪经历对其后作案地选择的影响

作案地选择是犯罪地理学的研究主题。已有的重复作案地选择的研究表明,犯罪者“前案件”作案地选择对他们“后案件”作案地选择具有影响,但以往研究关注的是先前的犯罪时间和地点对其后续作案地选择的影响,仍未检验犯罪者在“前案件”中犯罪经历的具体作用。因此,论文以中国东南沿海ZG市为例,利用街头抢劫者的抓捕数据和混合Logit模型,聚焦探析街头抢劫者先前的个体犯罪经历对他们随后的作案地选择的影响。研究发现：街头抢劫者在“前案件”中的犯罪间隔、犯罪出行和当场被捕等个体犯罪经历对其“后案件”作案地选择具有强烈的影响,即“前后案件”的犯罪间隔越临近、“前案件”犯罪出行距离越短,以及“前案件”未当场被捕,则大大增加了街头抢劫者返回到先前抢劫区域再次犯罪的可能性。并通过警察访谈和结合理论分析,发现“前案件”未当场被捕是由犯罪者当场被捕的恐惧感、警察特殊的干预方式,以及社会凝聚力和犯罪防控的相互作用而形成。研究结论可为警务部门的“事前防控”与“主动处置”提供一定的参考。     

基于风险地形建模的毒品犯罪风险评估和警务预测

犯罪具有明显的时空特征,研究犯罪问题离不开时间和空间维度分析,以及产生犯罪的社会、地理、生态、环境等因素。风险地形建模是美国学者研发的空间风险评估和警务预测技术,已在全球六大洲45个国家和美国35个州得到了独立测试和验证,被广泛应用于警务预测、国土安全、交通事故、公共医疗、儿童虐待、环境污染、城市发展等多个领域。在毒品、纵火、爆炸、强奸、抢劫、盗窃等犯罪研究领域更是取得了显著成果。本文运用犯罪热点分析和风险地形建模,以长三角地区N市毒品犯罪为研究对象,对该市2015年毒品犯罪的危险因子、空间盲区、风险地形进行分析,探索毒品犯罪的生成机理和演化规律,并对2016年毒品犯罪进行预测。研究结果表明,N市毒品犯罪呈现明显的犯罪热点和冷点;出租屋、酒店、车站、ATM机、停车场、娱乐场所、城市快速路、网吧是N市毒品犯罪的风险性因素。风险地形建模能较好地预测毒品犯罪。公安机关禁毒部门应据此进行严密管控,逐步限制、消除犯罪产生地、犯罪吸引地、犯罪促进地的生存土壤和条件。     

基于犯罪模式理论的犯罪出行空间特征与影响因素——以长春市南关区扒窃为例

犯罪出行是犯罪地理学的重要研究议题,在犯罪防控、侦破等警务实践中具有突出的技术贡献。受制于研究数据的限制,中国犯罪出行实证研究较为缺乏。论文研究了2010—2016年长春市南关区扒窃犯罪出行的空间模式与影响因素,并指出：① 2010—2016年长春市南关区扒窃犯罪出行平均距离为5.74 km,存在明显的空间衰减效应,空间模式为就近掠夺,在距离犯罪者居住地2 km处出现犯罪缓冲区。② 南关区扒窃犯罪高发区与犯罪群体主要聚居地在空间上呈现重叠,该区域犯罪以就近掠夺的空间模式为主。③ 回归模型验证了犯罪者人口属性中性别、户籍地、是否就业和具有前科劣迹、涉案金额、犯罪地点所属类型对于出行距离的显著影响,其中户籍地变量为理解转型期中国大城市犯罪行为具有一定意义。     

Understanding the spatial distribution of crime in hot crime areas

Hot crime areas are always targeted for police patrol to deter crimes. While much research has studied the distribution patterns of hot crime areas, research on the spatial distribution of crime within hot crime areas remains limited. Using burglary records in a large Chinese city, the ‘hottest’ place with the highest crime density was located using two spatial temporal kernel density estimation methods. The results indicated that the majority of crime within hot crime areas was concentrated within a small area distant from the hot area's center. These results provide a micro view of crime distribution within hot crime areas. Our analysis indicates that the results will not be affected by the methods adopted in identification of hot areas. This research is expected to improve the efficiency of police patrols.     

功能区视角下城市夜光与夜间“两抢一盗”犯罪的空间相关性——以H市市辖区为例

以H市市辖区为例,基于POI数据识别城市功能区,并结合NPP-VIIRS夜光遥感数据与夜间“两抢一盗”犯罪数据,构建双变量空间自相关分析模型,从整体及不同功能区角度探讨城市夜光与夜间“两抢一盗”犯罪的空间关系。结果表明：1）整体上,H市夜间“两抢一盗”犯罪形成“一主一副”的犯罪热点,且夜光与夜间“两抢一盗”犯罪存在空间异质性关系。2）大部分功能区在全局Moran's Ι上表现为正相关。在局部LISA聚类上,只有居住用地、商业服务业用地和道路与交通设施用地呈现显著的空间异质性。商业用地的高-高聚类多数分布在一环及二环以内,低-低聚类多数分布在城市外围及边缘地带,高-低聚类与低-高聚类则零散分布在二者之间的区域;居住用地的聚类情况呈现南北区域差异;道路与交通设施用地则由于报警地点与实际案发地点可能有所出入,因而结果可信度降低。     

Evaluating the Relationships of Bus Transit with Street and Off-Street Robberies

The relationship between public transit and crime has been extensively investigated for decades. Compared to rail systems, limited research has been conducted on bus transit and its surrounding robbery influence. In particular, most of the studies have focused on either all types of robbery as a whole or street robbery only. Street and off-street robberies have distinct spatial characteristics, however: The former occurs on the street, whereas the latter occurs not on the street but at indoor places or in (semi)public areas. Therefore, they might have different proximity to bus transit. Furthermore, as bus transit is not operated twenty-four hours a day, it is questionable to connect bus transit with robbery when bus transit is not in service. This study uses exploratory spatial data analysis and statistical modeling to compare and contrast street and off-street robberies to discover how their relations with bus transit vary in space and time. Results reveal that both street and off-street robberies decrease as the distance from bus stops increases. Compared to off-street robbery, street robbery is inclined to occur on the street without bus routes and during nonservice hours, respectively. These findings suggest that the preference of street robbery is related to the excess of suitable targets over capable guardians away from bus routes and when bus transit is not in operation, whereas off-street robbery is connected with the residential and commercial attractions along bus routes and people's frequent activities at these places during transit service hours.     

犯罪共生空间的类型识别及其特征分析

以ZG市公共空间盗窃、入室盗窃、寻衅滋事、接触诈骗、抢劫抢夺犯罪为研究对象,采用K均值聚类法识别不同类型的犯罪共生空间;并通过决策树模型分析了不同犯罪共生空间的特征。结果表明,ZG市犯罪共生空间可划分为4种类型：① 无犯罪类型共生区;② 公共空间盗窃和接触诈骗犯罪共生区;③ 所有类型犯罪共生区;④ 入室盗窃、寻衅滋事和抢劫抢夺犯罪共生区。城市中各异的社会环境和建成环境产生了不同类型的犯罪机会,而且各类社会环境和建成环境之间存在着条件交互性作用。研究结果为制定犯罪的联合防控策略和实现有限警力的合理布控并且提高执法效率提供了理论基础。     

顾及时间效应的周围人口与视频监控对街头抢劫者作案地选择的影响研究

作案地选择是犯罪地理学的研究主题,但以往研究侧重考虑建成环境和社会环境的影响,缺乏研究周围人口与视频监控的作用。为弥补这一不足,论文以中国ZG市为例,利用离散空间选择模型,检验周围人口和视频监控对街头抢劫者作案地选择的影响,并尝试验证其时间效应。结果表明：① 周围人口与视频监控对街头抢劫者作案地选择均存在显著负影响,但两者的作用强度有所差异,即它们均能抑制街头抢劫的发生,但周围人口的监护作用大于视频监控的威慑作用;② 在周内日变化上,周围人口和视频监控的监护作用具有时间平稳性;但在日内时变化上,周围人口的影响呈现出时间波动性,而视频监控的影响却保持时间稳定特性。研究结果对警务防控和犯罪研究具有重要的参考意义,如：① 开展社会治安视频监控系统防控效果的实验评估,并对其布设位置进行动态优化与调整;② 在城市规划或城市更新时安排适量的混合功能用地,以在规划或管理上加强对周围人口的适度调节;③ 未来时间效应研究应重点关注日变化规律。     

The use of predictive analysis in spatiotemporal crime forecasting: Building and testing a model in an urban context

Police databases hold a large amount of crime data that could be used to inform us about current and future crime trends and patterns. Predictive analysis aims to optimize the use of these data to anticipate criminal events. It utilizes specific statistical methods to predict the likelihood of new crime events at small spatiotemporal units of analysis. The aim of this study is to investigate the potential of applying predictive analysis in an urban context. To this end, the available crime data for three types of crime (home burglary, street robbery, and battery) are spatially aggregated to grids of 200 by 200 m and retrospectively analyzed. An ensemble model is applied, synthesizing the results of a logistic regression and neural network model, resulting in bi-weekly predictions for 2014, based on crime data from the previous three years. Temporally disaggregated (day versus night predictions) monthly predictions are also made. The quality of the predictions is evaluated based on the following criteria: direct hit rate (proportion of incidents correctly predicted), precision (proportion of correct predictions versus the total number of predictions), and prediction index (ratio of direct hit rate versus proportion of total area predicted as high risk). Results indicate that it is possible to attain functional predictions by applying predictive analysis to grid-level crime data. The monthly predictions with a distinction between day and night produce better results overall than the bi-weekly predictions, indicating that the temporal resolution can have an important impact on the prediction performance.     

ZG市诈骗犯罪的时空分布与影响因素

诈骗犯罪是现代城市中亟待解决的一大社会难题。现有研究多从社会学角度,基于微观层次探讨影响诈骗受害的个人属性特征,缺乏从地理学视角对诈骗受害者生存环境中的中宏观层次因素的考虑。本文基于犯罪地理学视角,综合运用平均最近邻、核密度以及负二项回归等研究方法,对ZG市5类诈骗警情的时空分布特征和基于建成环境与社会环境两大维度的影响因素进行了深入探讨。结果表明：① 各类诈骗的时间分布规律各异,但整体上呈现出工作日高于休息日、下午或晚上高于上午、凌晨时段为最低的特征;② 和其他类型的城市犯罪类似,诈骗犯罪整体呈现出与老城区距离衰减的“多中心”显著性集聚特征;各类型诈骗热点的空间分布大同小异,多分布在城市的老城区、CBD、火（汽）车站、城中村或高校布局的周边地带;③ 各类诈骗犯罪的空间分布影响因素各异,但整体表现出与银行网点、旅游景点、道路密度、土地利用混合度、高校等建成环境因素高度相关;与购买商品房家庭占比、受教育水平、人口老龄化和城镇化水平等社会环境显著相关的特性。本文拓展了犯罪地理学领域对诈骗犯罪的研究成果,证实了各类诈骗犯罪符合日常活动理论的理论假设,对诈骗受害情景预防具有重要意义。     

Leveraging parallel spatio-temporal computing for crime analysis in large datasets: analyzing trends in near-repeat phenomenon of crime in cities

ABSTRACT

Crime often clusters in space and time. Near-repeat patterns improve understanding of crime communicability and their space–time interactions. Near-repeat analysis requires extensive computing resources for the assessment of statistical significance of space–time interactions. A computationally intensive Monte Carlo simulation-based approach is used to evaluate the statistical significance of the space-time patterns underlying near-repeat events. Currently available software for identifying near-repeat patterns is not scalable for large crime datasets. In this paper, we show how parallel spatial programming can help to leverage spatio-temporal simulation-based analysis in large datasets. A parallel near-repeat calculator was developed and a set of experiments were conducted to compare the newly developed software with an existing implementation, assess the performance gain due to parallel computation, test the scalability of the software to handle large crime datasets and assess the utility of the new software for real-world crime data analysis. Our experimental results suggest that, efficiently designed parallel algorithms that leverage high-performance computing along with performance optimization techniques could be used to develop software that are scalable with large datasets and could provide solutions for computationally intensive statistical simulation-based approaches in crime analysis.     

基于时空临近重复效应的犯罪热点特征及成因分析——以北京市抢劫案件为例

时空临近重复效应是犯罪活动的一种重要时空特征。为深入研究犯罪热点的特征及其形成原因,论文以北京市内城六区2012—2014年抢劫案件为例,通过核密度估计、时空临近重复计算及定义时空临近重复案件链等方法分析了犯罪热点的案件构成,并从犯罪人因素和环境因素等方面对犯罪热点内的案件特征结构进行了分析。结果表明：北京市内城六区的抢劫案件存在有“a”“b”“c”三个主要的空间热点,并且热点内的大部分案件均具有显著的时空临近重复效应;其中热点“a”位于双井、劲松一带,热点“c”位于南四环大红门桥一带,且2个热点内案件的犯罪人特征在一致性程度上高于环境类特征,表明热点的形成源于犯罪人在热点区域内重复作案的可能性较大;而热点“b”位于东南三环的分钟寺地区,热点内案件的环境类特征在一致性程度上高于犯罪人特征,表明该热点的形成为不同犯罪人在热点区域内集中作案的可能性较高。研究对警务部门开展针对性的犯罪打击和防控有一定的支撑作用。     

土地利用对街头抢劫影响的空间分异模式：以H市为例

选取H市中心城区2009年和2010年发生的街头抢劫案件为研究对象,构建地理加权泊松回归GWPR模型,探讨不同性质土地利用对案件影响的空间差异性。研究表明,各类用地与街头抢劫的关系存在显著的空间异质性。其中,位于中心区外围的传统居住区和部分新建社区等居住用地对街头抢劫存在显著的负向影响;商业服务业设施用地对街头抢劫的影响总体上显著性不强,但与其中的商业设施点类型密切相关,独栋高层的商业综合体会使犯罪数量下降,而临街商铺形式的商业设施点则是犯罪高发区域;工业用地仅对老城区的街头抢劫产生正向影响;公园绿地总体上与街头抢劫案件呈负相关性,但城市开敞绿地多的地方案件数量也较多;交通设施用地与街头抢劫的关系则受到交通设施、道路等级、路网形态的影响。最后通过聚类分析发现,土地利用对案件影响的主导因素的空间分异模式与不同的城市功能分区有一定的对应关系,可以对每个功能分区根据其街头抢劫发生的主导因素制定相应的土地利用规划导则。     

ZG市街头抢劫者作案地选择及其影响因素研究

以往关于作案地选择的研究,缺乏考虑不同属性群体间的空间差异。以中国ZG市为例,利用离散空间选择模型,基于不同年龄属性的视角,进行街头抢劫者作案地选择及影响因素的对比分析,并据此提出犯罪防控建议。研究发现：① 不同年龄的街头抢劫者作案地选择存在显著的空间差异。即少年抢劫者趋向在劳动密集型产业集聚区和中小学密集区作案,而年轻的成年抢劫者仅趋向于劳动密集型产业集聚区,但成年抢劫者的作案地却偏向于客运站所在社区及其周边地区。② 年龄相关的活动节点、周围人口的监护作用和青少年人口比例是形成这种空间差异的主要因素。研究结果对犯罪防控与社会治理具有重要的参考意义,如：① 在青少年抢劫者频繁作案的劳动密集型产业集聚区,调控网吧、酒吧等年龄相关活动节点的数量。② 在成年抢劫者作案密集的客运站及其周边社区,规划一定数量周围人口的持续存在,以发挥出更好的监护作用。③ 在青少年人口比例较高的社区,通过问题青少年的摸底调查,加强精准引导与帮扶。论文首次验证了不同年龄的街头抢劫者作案地选择差异及成因,并在理论上弥补了犯罪者作案地选择缺乏细分人群的不足。     

基于空间句法的武汉城区“两抢一盗”犯罪分布环境

结合空间组构与环境犯罪学,初步建构基于空间句法的犯罪分布环境阐释理论。以武汉市中心城区为案例区域,以立案判决的2013年盗窃罪、抢劫罪和抢夺罪案件分布地点为数据源,以典型犯罪空间为实证研究对象,解读城市“两抢一盗”犯罪现象的分布环境。宏观尺度下,空间组构自发涌现的城市节点容易成为犯罪吸引场,与犯罪热点区分布形成密切关系;节点可达性衔接宏微观空间,影响犯罪人到达、逃逸犯罪地点成本的大小以及犯罪失败风险的高低;微观尺度上,局部空间与整体空间割裂形成的“空间缝隙”为犯罪人的空间探索创造了可能,空间的高集成度与空间使用者的单一化强化了犯罪集聚;空间拓扑深度则通过塑造社区人流的社会结构与领域感影响犯罪的空间防卫。空间句法为分析犯罪人的滋生环境、犯罪动机的刺激环境、犯罪人“到达”、“实施”、“逃逸”的活动环境以及防卫犯罪活动的约束环境提供了有力支撑。     

中国省域犯罪率影响因素的空间非平稳性分析

收入差距和流动人口是影响犯罪率的两个重要因素, 以往研究基于OLS模型, 在假设地域空间为均质的前提下分析其对犯罪率的影响, 但现实世界的空间单元往往难以满足“均质”的假设, 多数表现为“空间异质”。以OLS计量空间异质会造成计量结果出现偏差, 同时无法了解不同空间单元的不同影响。而地理加权回归模型通过将空间结构嵌入线性回归模型中, 很好的解决了空间异质的计量问题。利用地理加权回归模型研究2008 年中国大陆省域单元犯罪率的影响因素, 结果表明:① 犯罪率的影响因素表现出空间非平稳性, 流动人口与犯罪率显著相关, 但各个省份相关程度并不相同, 影响关系随空间位置变化而变化;② 地理加权回归模型的计量精度和拟合度比OLS模型有大幅提高     

Crime concentrations and similarities in spatial crime patterns in a Brazilian context

Research within the geography of crime and spatial criminology literature most often show that crime is highly concentrated in particular places. Moreover, a subset of this literature has shown that the spatial patterns of these concentrations are different across crime types. This raises questions regarding the appropriateness of aggregating crime types (property and violent crime, for example) when the underlying spatial pattern is of interest. In this paper, using crime data from Campinas, Brazil, we investigate the crime concentrations and the similarities among different crime types across space. Similar to some recent research in another context, we find that crime is highly concentrated in Campinas but the ability to aggregate similar crime types at the street segment level is not generalizability when compared to a North American context.     

Voronoi Diagrams and Spatial Analysis of Crime

A range of spatial analyses are used in the field of crime mapping, such as kernel density estimation, Ripley's K-function, and spatial autocorrelation, but there is limited use of Voronoi diagrams (VDs). The goal of this article is to contribute to the spatial analysis of crime through the use of VDs. We use four years of commercial robbery data from Campinas, Brazil, and employ several VD techniques: (1) We analyze crime concentrations through the properties of VDs—area and number of vertices—and coverage curve; (2) we introduce a new crime geovisualization with VD in three dimensions; and (3) we apply a network VD technique to crime analysis. The results demonstrate associations between these VD techniques and the ability of the researcher to recognize crime patterns associated with crime concentration, crime along pathways, and the highly regularized distribution of crime in limited areas spatially.     

Street profile analysis: A new method for mapping crime on major roadways

Street profile analysis is a new method for analyzing temporal and spatial crime patterns along major roadways in metropolitan areas. This crime mapping technique allows for the identification of crime patterns along these street segments. These are linear spaces where aggregate crime patterns merge with crime attractors/generators and human movement to demonstrate how directionality is embedded in city infrastructures. Visually presenting the interplay between these criminological concepts and land use can improve police crime management strategies. This research presents how this crime mapping technique can be applied to a major roadway in Burnaby, Canada. This technique is contrasted with other crime mapping methods to demonstrate the utility of this approach when analyzing the rate and velocity of crime patterns overtime and in space.