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Crime potential modelling: A GIS-based method using weights-of-evidence (Ontario).

机译:犯罪潜力建模:使用证据权重的基于GIS的方法(安大略省)。

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摘要

This thesis was undertaken to evaluate the utility, effectiveness and accuracy of the GIS-based weights of evidence prediction model for the spatial prediction of residential break and enter crime in the City of Ottawa. The data-driven predictive weights of evidence (WofE) model was applied against six specific land uses of the urban environment as identified in the environmental criminology literature, including known occurrences of break and enters, in order to generate maps that could identify where future occurrences of residential break and enter might be located. Using the Arc-WofE extension written for the ArcView 3.2 GIS software package, a series of "crime potential maps" were generated that successfully indentified small areas of high potential (in the order of 60 to 95% probability) and were successful in placing future break and enter occurrences in these areas of high potential.
机译:本文旨在评估基于GIS的证据权重预测模型在渥太华市居住突破和进入犯罪的空间预测中的实用性,有效性和准确性。数据驱动的预测证据权重(WofE)模型针对环境犯罪学文献中确定的六种特定的城市环境土地用途(包括已知的闯入事件)进行了应用,以便生成可以确定未来发生地点的地图可能位于住宅休息区并进入。使用为ArcView 3.2 GIS软件包编写的Arc-WofE扩展,生成了一系列“犯罪潜力图”,这些地图成功地识别了高潜力的小区域(概率为60%到95%),并成功地将未来打破并进入这些高潜力地区的事件。

著录项

  • 作者单位

    Carleton University (Canada).;

  • 授予单位 Carleton University (Canada).;
  • 学科 Geography.; Sociology Criminology and Penology.
  • 学位 M.A.
  • 年度 2005
  • 页码 102 p.
  • 总页数 102
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 自然地理学;法学各部门;
  • 关键词

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