The Spatial- Temporal Prediction of Various Crime Types | In Houston, TX Based on Hot-Spot Techniques

Shuzhan Fan (u. a.)

ISBN 10: 3659631574 / ISBN 13: 9783659631573

Published by LAP LAMBERT Academic Publishing, 2018

About this Item

The Spatial- Temporal Prediction of Various Crime Types | In Houston, TX Based on Hot-Spot Techniques | Shuzhan Fan (u. a.) | Taschenbuch | 80 S. | Englisch | 2018 | LAP LAMBERT Academic Publishing | EAN 9783659631573 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.

Seller Inventory # 114174919

Bibliographic Details

• Title: The Spatial- Temporal Prediction of Various Crime Types | In Houston, TX Based on Hot-Spot Techniques
• Publisher: LAP LAMBERT Academic Publishing
• Publication Date: 2018
• Language: English
• ISBN 10: 3659631574
• ISBN 13: 9783659631573
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 5D millimeters 220 millimeters width by 150 millimeters height by 5 millimeters depth
• Weight: 137 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

A series of hotspot mapping theories and methods have been proposed to predict where and when a crime will happen. Each method has its strengths and weaknesses. In addition, the predictive accuracy of each hotspot method varies depending on the study area, crime type, parameter settings of each method, etc. The predictive accuracy of hotspot methods can be quantified by three measures, which include the hit rate, the predictive accuracy index (PAI), and the recapture rate index (RRI). This work applied eight hotspot mapping techniques from the crime analysis field to predict crime hotspot patterns. In addition, these hotspot methods were compared and evaluated in order to possibly find a single best method that outperforms all other methods based on the three predictive accuracy measures. Identifying the single best method is carried out for all Part1 Crimes combined and individually, for five of the nine Part 1 Crime. In addition to the spatial analysis, a spatial–temporal analysis of the same crime dataset was conducted to investigate the distribution of crime clusters from both the space and time dimensions.