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An analysis of crime hot spots using GPS tracking data of children and agent-based simulation modeling

机译:利用儿童GPS追踪数据和基于Agent的仿真模型分析犯罪热点

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Although the problem of a lack of an adequate denominator of crime rates has been widely recognized, relatively few solutions have been found. This paper proposes a sophisticated method of analyzing crime hot spots using global positioning system (GPS) tracking data and agent-based simulation modeling. The goal of the proposed analysis technique is to estimate a population at risk across time and space at the micro-level, such as streets and locations (e.g. parks and playgrounds).In order to create valid estimates of a population at risk and to illustrate how the estimated population at risk can be used in crime analysis, this paper presents a series of three sub-studies. First, GPS tracking data were obtained for two weeks for 80 children in the second and fifth grades from one school located in a suburb of Tokyo, Japan. GIS software was used to analyze the GPS data in order to identify streets and places that the children frequented. Second, agent-based simulation modeling was developed to extend the proposed analysis method to school districts that had not participated in the GPS sub-study. In the process of developing a simulation algorithm, the validity of simulation modeling was checked by comparing the simulation results with the GPS tracking data. Third, victimization surveys with maps were conducted in six schools (including the school that participated in the GPS sub-study) that identified locations of crime incidents. Victimization survey results were overlaid with the analysis results of GPS data and agent-based simulation modeling in order to examine crime hot spots.The proposed technique of agent-based modeling produces an accurate denominator of crime rates at the micro-level which can then be used to analyze crime hot spots properly. In particular, this paper discusses how crime analysts can identify different types of hot spots, such as crime generators and crime attractors, by examining the number of crime incidents and the magnitude of crime rate. This paper argues intervention strategies need to be tailored for each type of crime hot spots, as these crime hot spots develop through different mechanisms. Finally, this paper discusses limitations of the proposed technique and the direction of future research.View full textDownload full textKeywordscrime hot spots, GPS, child victimization, simulation model, crime rate, spatio-temporal movementRelated var addthis_config = { ui_cobrand: "Taylor & Francis Online", services_compact: "citeulike,netvibes,twitter,technorati,delicious,linkedin,facebook,stumbleupon,digg,google,more", pubid: "ra-4dff56cd6bb1830b" }; Add to shortlist Link Permalink http://dx.doi.org/10.1080/19475683.2012.691902
机译:尽管人们普遍认识到缺乏适当的犯罪率分母的问题,但找到的解决方案相对较少。本文提出了一种使用全球定位系统(GPS)跟踪数据和基于代理的仿真模型来分析犯罪热点的复杂方法。所提出的分析技术的目标是在微观层面上(例如街道和位置(例如公园和游乐场))跨时间和空间来估计处于风险中的人口。为了创建对处于风险中的人口的有效估计并进行说明如何将估计的处于危险中的人口用于犯罪分析,本文提出了一系列三个子研究。首先,从位于日本东京郊区的一所学校的80位二年级和五年级的孩子获得了两周的GPS跟踪数据。 GIS软件用于分析GPS数据,以识别儿童经常光顾的街道和地方。其次,开发了基于主体的仿真模型,以将所提出的分析方法扩展到未参与GPS子研究的学区。在开发仿真算法的过程中,通过将仿真结果与GPS跟踪数据进行比较,检查了仿真建模的有效性。第三,在六所学校(包括参与GPS子研究的学校)中进行了带有地图的受害者调查,以查明犯罪事件的地点。受害者调查结果与GPS数据的分析结果和基于主体的仿真模型相叠加,以检查犯罪热点。所提出的基于主体的建模技术可在微观层次上产生准确的犯罪率分母。用于正确分析犯罪热点。特别是,本文讨论了犯罪分析师如何通过检查犯罪事件的数量和犯罪率的大小来识别不同类型的热点,例如犯罪产生者和犯罪吸引者。本文认为,应针对每种类型的犯罪热点量身定制干预策略,因为这些犯罪热点是通过不同的机制发展的。最后,本文讨论了所提出的技术的局限性和未来的研究方向。在线”,services_compact:“ citeulike,netvibes,twitter,technorati,可口,linkedin,facebook,stumbleupon,digg,google,更多”,发布号:“ ra-4dff56cd6bb1830b”};添加到候选列表链接永久链接http://dx.doi.org/10.1080/19475683.2012.691902

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