基于街道轮廓和离散微积分的犯罪边界识别方法

Justin Song, Valerie Spicer, Andrew J. Park, Herbert H. Tsang, P. Brantingham
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引用次数: 1

摘要

城市环境的结构决定了犯罪模式。街道侧容分析是分析与街道网络有关的犯罪的一种新方法。街道轮廓分析可以用来确定犯罪激增或沿道路犯罪的严重集中。在这项研究中,将街道轮廓技术与离散微积分方法相结合,以确定加拿大不列颠哥伦比亚省温哥华市小型犯罪空间的边界。这项实验技术利用来自温哥华警察局的开源财产犯罪数据来分析温哥华的犯罪模式。详细描述了这种计算犯罪分析技术,并探讨了该技术的实用性。这种新技术对于情报和安全信息学领域来说是一种有价值的工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Computational Method for Identifying the Boundaries of Crime with Street Profile and Discrete Calculus
The structure of the urban setting determines the crime patterns. This research explores the street profile analysis which is a new method for analyzing crime in relation to street networks. Street profile analysis can be used to identify crime surges or heavy concentrations of crime along roadways. In this study, the street profile technique is combined with a discrete calculus approach to locate the boundaries of small criminal spaces in the City of Vancouver, British Columbia, Canada. This experimental technique utilizes open source property crime data from the Vancouver Police Department to analyze crime patterns within Vancouver. This computational crime analysis technique is described in detail and the utility of this technique explored. The new technique is a valuable tool for the intelligence and security informatics communities.
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