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[n° ou bulletin]
est un bulletin de Cartography and Geographic Information Science / Cartography and geographic information society (1999 -) ![]()
[n° ou bulletin]
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Exemplaires(1)
Code-barres | Cote | Support | Localisation | Section | Disponibilité |
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032-2015021 | RAB | Revue | Centre de documentation | En réserve L003 | Disponible |
Dépouillements


UK open source crime data: accuracy and possibilities for research / Lisa Tompson in Cartography and Geographic Information Science, Vol 42 n° 2 (April 2015)
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[article]
Titre : UK open source crime data: accuracy and possibilities for research Type de document : Article/Communication Auteurs : Lisa Tompson, Auteur ; Shane Johnson, Auteur ; Matthew Ashby, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 97 - 111 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] données ouvertes
[Termes IGN] données statistiques
[Termes IGN] infraction
[Termes IGN] masque géographique
[Termes IGN] protection de la vie privée
[Termes IGN] Royaume-Uni
[Termes IGN] similitudeRésumé : (auteur) In the United Kingdom, since 2011 data regarding individual police recorded crimes have been made openly available to the public via the police.uk website. To protect the location privacy of victims these data are obfuscated using geomasking techniques to reduce their spatial accuracy. This paper examines the spatial accuracy of the police.uk data to determine at what level(s) of spatial resolution – if any – it is suitable for analysis in the context of theory testing and falsification, evaluation research, or crime analysis. Police.uk data are compared to police recorded data for one large metropolitan Police Force and spatial accuracy is quantified for four different levels of geography across five crime types. Hypotheses regarding systematic errors are tested using appropriate statistical approaches, including methods of maximum likelihood. Finally, a “best-fit” statistical model is presented to explain the error as well as to develop a model that can correct it. The implications of the findings for researchers using the police.uk data for spatial analysis are discussed. Numéro de notice : A2015-236 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/15230406.2014.972456 En ligne : https://doi.org/10.1080/15230406.2014.972456 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76493
in Cartography and Geographic Information Science > Vol 42 n° 2 (April 2015) . - pp 97 - 111[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 032-2015021 RAB Revue Centre de documentation En réserve L003 Disponible The impact of using social media data in crime rate calculations: shifting hot spots and changing spatial patterns / Nick Malleson in Cartography and Geographic Information Science, Vol 42 n° 2 (April 2015)
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Titre : The impact of using social media data in crime rate calculations: shifting hot spots and changing spatial patterns Type de document : Article/Communication Auteurs : Nick Malleson, Auteur ; Martin A. Andresen, Auteur Année de publication : 2015 Article en page(s) : pp 112 - 121 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] infraction
[Termes IGN] production participative
[Termes IGN] réseau social
[Termes IGN] Yorkshire (Angleterre)Résumé : (auteur) Crime rate is a statistic used to summarize the risk of criminal events. However, research has shown that choosing the appropriate denominator is non-trivial. Different crime types exhibit different spatial opportunities and so does the population at risk. The residential population is the most commonly used population at risk, but is unlikely to be suitable for crimes that involve mobile populations. In this article, we use “crowd-sourced” data in Leeds, England, to measure the population at risk, considering violent crime. These new data sources have the potential to represent mobile populations at higher spatial and temporal resolutions than other available data. Through the use of two local spatial statistics (Getis-Ord GI* and the Geographical Analysis Machine) and visualization, we show that when the volume of social media messages, as opposed to the residential population, is used as a proxy for the population at risk, criminal event hot spots shift spatially. Specifically, the results indicate a significant shift in the city center, eliminating its hot spot. Consequently, if crime reduction/prevention efforts are based on resident population based crime rates, such efforts may not only be ineffective in reducing criminal event risk, but be a waste of public resources. Numéro de notice : A2015-237 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/15230406.2014.905756 En ligne : https://doi.org/10.1080/15230406.2014.905756 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76494
in Cartography and Geographic Information Science > Vol 42 n° 2 (April 2015) . - pp 112 - 121[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 032-2015021 RAB Revue Centre de documentation En réserve L003 Disponible Spatial eigenvector filtering for spatiotemporal crime mapping and spatial crime analysis / Marco Helbich in Cartography and Geographic Information Science, Vol 42 n° 2 (April 2015)
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[article]
Titre : Spatial eigenvector filtering for spatiotemporal crime mapping and spatial crime analysis Type de document : Article/Communication Auteurs : Marco Helbich, Auteur ; Jamal Jokar Arsanjani, Auteur Année de publication : 2015 Article en page(s) : pp 134 - 148 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse diachronique
[Termes IGN] carte thématique
[Termes IGN] données spatiotemporelles
[Termes IGN] filtrage statistique
[Termes IGN] Houston (Texas)
[Termes IGN] infraction
[Termes IGN] valeur propreRésumé : (auteur) Spatial and spatiotemporal analyses are exceedingly relevant to determine criminogenic factors. The estimation of Poisson and negative binomial models (NBM) is complicated by spatial autocorrelation. Therefore, first, eigenvector spatial filtering (ESF) is introduced as a method for spatiotemporal mapping to uncover time-invariant crime patterns. Second, it is demonstrated how ESF is effectively used in criminology to invalidate model misspecification, i.e., residual spatial autocorrelation, using a nonviolent crime dataset for the metropolitan area of Houston, Texas, over the period 2005–2010. The results suggest that local and regional geography significantly contributes to the explanation of crime patterns. Furthermore, common space-time eigenvectors selected on an annual basis indicate striking spatiotemporal patterns persisting over time. The findings about the driving forces behind Houston’s crime show that linear and nonlinear, spatially filtered, NBMs successfully absorb latent autocorrelation and, therefore, prevent parameter estimation bias. The consideration of a spatial filter also increases the explanatory power of the regressions. It is concluded that ESF can be highly recommended for the integration in spatial and spatiotemporal modeling toolboxes of law enforcement agencies. Numéro de notice : A2015-238 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/15230406.2014.893839 En ligne : https://doi.org/10.1080/15230406.2014.893839 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76495
in Cartography and Geographic Information Science > Vol 42 n° 2 (April 2015) . - pp 134 - 148[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 032-2015021 RAB Revue Centre de documentation En réserve L003 Disponible Visualization techniques for journey to crime flow data / Andrew Wheeler in Cartography and Geographic Information Science, Vol 42 n° 2 (April 2015)
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[article]
Titre : Visualization techniques for journey to crime flow data Type de document : Article/Communication Auteurs : Andrew Wheeler, Auteur Année de publication : 2015 Article en page(s) : pp 149 - 161 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] carte thématique
[Termes IGN] cartographie des flux
[Termes IGN] infraction
[Termes IGN] trajet (mobilité)
[Termes IGN] visualisationRésumé : (auteur) Research applications using journey to crime data present unique challenges for modeling and visualization not encountered with typical data that are only georeferenced at one point in space. The article provides graphical examples on how to visualize flow lines directly, how to effectively aggregate and visualize statistical summaries of distributions of flow lines, and supplemental statistical graphics to visualize flow data. The article also provides supplementary material demonstrating and implementing several of the techniques discussed in the article. Numéro de notice : A2015-239 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/15230406.2014.890545 En ligne : https://doi.org/10.1080/15230406.2014.890545 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76496
in Cartography and Geographic Information Science > Vol 42 n° 2 (April 2015) . - pp 149 - 161[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 032-2015021 RAB Revue Centre de documentation En réserve L003 Disponible