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Modeling the risk of robbery in the city of Tshwane, South Africa / Nicolas Kemp in Cartography and Geographic Information Science, vol 48 n° 1 (January 2021)  

Public [article]  inCartography and Geographic Information Science > vol 48 n° 1 (January 2021) . - pp 29 - 42 Titre : Modeling the risk of robbery in the city of Tshwane, South Africa Type de document : Article/Communication Auteurs : Nicolas Kemp, Auteur ; Gregory D. Breetzke, Auteur ; Anthony K. Cooper, Auteur Année de publication : 2021 Article en page(s) : pp 29 - 42 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] Afrique du sud (état) [Termes IGN] criminalité [Termes IGN] modèle de simulation [Termes IGN] modélisation spatiale [Termes IGN] prévention des risques [Termes IGN] protection civile [Termes IGN] zone à risque Résumé : (auteur) In this study, we model the risk of robbery in the City of Tshwane in South Africa. We use the collective knowledge of two prominent spatial theories of crime (social disorganization theory, and crime pattern theory) to guide the selection of data and employ rudimentary geospatial techniques to create a crude model that identifies the risk of future robbery incidents in the city. The model is validated using actual robbery incidences recorded for the city. Overall the model performs reasonably well with approximately 70% of future robbery incidences accurately identified within a small subset of the overall model. Developing countries such as South Africa are in dire need of crime risk intensity models that are simple, and not data intensive to allocate scarce crime prevention resources in a more optimal fashion. It is anticipated that this model is a first step in this regard. Numéro de notice : A2021-017 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2020.1814872 Date de publication en ligne : 10/09/2020 En ligne : https://doi.org/10.1080/15230406.2020.1814872 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96455 [article]

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A spatio-temporal method for crime prediction using historical crime data and transitional zones identified from nightlight imagery / Bo Yang in International journal of geographical information science IJGIS, vol 34 n° 9 (September 2020)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 34 n° 9 (September 2020) . - pp 1740 - 1764 Titre : A spatio-temporal method for crime prediction using historical crime data and transitional zones identified from nightlight imagery Type de document : Article/Communication Auteurs : Bo Yang, Auteur ; Lin Liu, Auteur ; Minxuan Lan, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 1740 - 1764 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] coefficient de corrélation [Termes IGN] criminalité [Termes IGN] données spatiotemporelles [Termes IGN] géostatistique [Termes IGN] historique des données [Termes IGN] image NPP-VIIRS [Termes IGN] krigeage [Termes IGN] modèle dynamique [Termes IGN] nuit [Termes IGN] Ohio (Etats-Unis) [Termes IGN] prédiction [Termes IGN] prévention des risques [Termes IGN] prise de vue nocturne [Termes IGN] test statistique [Termes IGN] zone urbaine Résumé : (auteur) Accurate crime prediction can help allocate police resources for crime reduction and prevention. There are two popular approaches to predict criminal activities: one is based on historical crime, and the other is based on environmental variables correlated with criminal patterns. Previous research on geo-statistical modeling mainly considered one type of data in space-time domain, and few sought to blend multi-source data. In this research, we proposed a spatio-temporal Cokriging algorithm to integrate historical crime data and urban transitional zones for more accurate crime prediction. Time-series historical crime data were used as the primary variable, while urban transitional zones identified from the VIIRS nightlight imagery were used as the secondary co-variable. The algorithm has been applied to predict weekly-based street crime and hotspots in Cincinnati, Ohio. Statistical tests and Predictive Accuracy Index (PAI) and Predictive Efficiency Index (PEI) tests were used to validate predictions in comparison with those of the control group without using the co-variable. The validation results demonstrate that the proposed algorithm with historical crime data and urban transitional zones increased the correlation coefficient by 5.4% for weekdays and by 12.3% for weekends in statistical tests, and gained higher hit rates measured by PAI/PEI in the hotspots test. Numéro de notice : A2020-475 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1737701 Date de publication en ligne : 13/03/2020 En ligne : https://doi.org/10.1080/13658816.2020.1737701 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95622 [article]

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079-2020091	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Reestimating a minimum acceptable geocoding hit rate for conducting a spatial analysis / Alvaro Briz-Redon in International journal of geographical information science IJGIS, vol 34 n° 7 (July 2020)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 34 n° 7 (July 2020) . - pp 1283 - 1305 Titre : Reestimating a minimum acceptable geocoding hit rate for conducting a spatial analysis Type de document : Article/Communication Auteurs : Alvaro Briz-Redon, Auteur ; Francisco Martinez-Ruiz, Auteur ; Francisco Montes, Auteur Année de publication : 2020 Article en page(s) : pp 1283 - 1305 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse de groupement [Termes IGN] appariement automatique [Termes IGN] criminalité [Termes IGN] géocodage [Termes IGN] géopositionnement [Termes IGN] infraction [Termes IGN] simulation [Termes IGN] taux d'échantillonnage Résumé : (auteur) Geocoding consists in converting a textual description of a location into coordinates. Hence, geocoding a dataset of events has to be carried out before performing a spatial analysis of some data. Automated procedures are necessary to geocode large datasets of events, but they can produce errors. Therefore, it is natural to ask oneself what is the minimum percentage of events that should be geocoded. An 85% of success was established 15 years ago as the first estimate of a minimum acceptable rate, becoming a reference for many spatial analysts. In this paper, the goal is reestimating a minimum acceptable geocoding match rate through the same procedure that was employed for computing the first estimate while accounting for some spatial factors that could possibly influence this estimation: intensity, clustering and aggregation levels. Several statistical techniques and the presence of nonrandomly distributed errors are also explored in this context. The results indicate that variations in intensity, clustering and aggregation levels lead to different minimum acceptable geocoding match rates. Furthermore, specific techniques such as cluster detection seem to be especially sensitive to the existence of non-geocoded data. Therefore, the highly approved 85% geocoding rate may need to be raised. Numéro de notice : A2020-303 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2019.1703994 Date de publication en ligne : 18/12/2019 En ligne : https://doi.org/10.1080/13658816.2019.1703994 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95143 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
079-2020071	RAB	Revue	Centre de documentation	En réserve L003	Disponible

A novel method of spatiotemporal dynamic geo-visualization of criminal data, applied to command and control centers for public safety / Mayra Salcedo-Gonzalez in ISPRS International journal of geo-information, vol 9 n° 3 (March 2020)  

Public [article]  inISPRS International journal of geo-information > vol 9 n° 3 (March 2020) . - 17 p. Titre : A novel method of spatiotemporal dynamic geo-visualization of criminal data, applied to command and control centers for public safety Type de document : Article/Communication Auteurs : Mayra Salcedo-Gonzalez, Auteur ; Julio Suarez-Paez, Auteur ; Manuel Esteve, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 17 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] cartographie des risques [Termes IGN] Colombie [Termes IGN] criminalité [Termes IGN] données spatiotemporelles [Termes IGN] géoréférencement [Termes IGN] géovisualisation [Termes IGN] gestion des ressources humaines [Termes IGN] gestion urbaine [Termes IGN] logiciel libre [Termes IGN] protection civile [Termes IGN] risque social [Termes IGN] système d'information urbain [Termes IGN] système de contrôle [Termes IGN] ville intelligente Résumé : (auteur) This article shows a novel geo-visualization method of dynamic spatiotemporal data that allows mobility and concentration of criminal activity to be study. The method was developed using, only and significantly, real data of Santiago de Cali (Colombia), collected by the Colombian National Police (PONAL). This method constitutes a tool that allows criminal influx to be analyzed by concentration, zone, time slot and date. In addition to the field experience of police commanders, it allows patterns of criminal activity to be detected, thereby enabling a better distribution and management of police resources allocated to crime deterrence, prevention and control. Additionally, it may be applied to the concepts of safe city and smart city of the PONAL within the architecture of Command and Control System (C2S) of Command and Control Centers for Public Safety. Furthermore, it contributes to a better situational awareness and improves the future projection, agility, efficiency and decision-making processes of police officers, which are all essential for fulfillment of police missions against crime. Finally, this was developed using an open source software, it can be adapted to any other city, be used with real-time data and be implemented, if necessary, with the geographic software of any other C2S. Numéro de notice : A2020-259 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.3390/ijgi9030160 Date de publication en ligne : 10/03/2020 En ligne : https://doi.org/10.3390/ijgi9030160 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95016 [article]

Placial analysis of events: a case study on criminological places / Sunghwan Cho in Cartography and Geographic Information Science, Vol 46 n° 6 (November 2019)  

Public [article]  inCartography and Geographic Information Science > Vol 46 n° 6 (November 2019) . - pp 547-566 Titre : Placial analysis of events: a case study on criminological places Type de document : Article/Communication Auteurs : Sunghwan Cho, Auteur ; May Yuan, Auteur Année de publication : 2019 Article en page(s) : pp 547-566 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] cartographie statistique [Termes IGN] criminalité [Termes IGN] Dallas (Texas) [Termes IGN] détection d'événement [Termes IGN] données spatiotemporelles [Termes IGN] géolocalisation [Termes IGN] interaction humain-espace [Termes IGN] système d'information géographique [Termes IGN] zone à risque Résumé : (auteur) The contrast of space and place has long been an active topic of scholarly discussions in many disciplines. While spatial analysis enjoys a multitude of quantitative methods, the study of place remains mostly conceptual and descriptive. This paper expands upon the rich concepts of place in the literature to propose a quantitative framework for placial analysis based on events. Central to the proposed framework are three assumptions: (1) human experiences transform space to place; (2) events build human experiences in space; and (3) places emerge organically and may change characters, spatial extent and location over time through the shifts in occurrences and types of events in space and time. The proposed framework consists of three elements: clustering events, decomposing event distributions, and identifying the similarity of event clusters. We applied the framework to identify criminological places in the City of Dallas in the United States and the changes of these places from 1 June 2014 to 30 May 2018. Numéro de notice : A2019-417 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2019.1578265 Date de publication en ligne : 01/03/2019 En ligne : https://doi.org/10.1080/15230406.2019.1578265 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93544 [article]

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032-2019061	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Attention les cybercriminels veulent utiliser vos serveurs / Xavier Fodor in SIGmag, n° 17 (juin 2018)

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Spatial Analysis, Modelling and Planning / Jorge Rocha (2018)  

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Cartographie policière : une analyse ethnographique / Françoise de Blomac in DécryptaGéo le mag, n° 175 (mars 2016)

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Crime data process in Waterloo region / Victor Brinon (2016) 

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Météocrime : une cartographie interactive des cambriolages / Olivier Guéniat in Géomatique suisse, vol 114 n° 1 (janvier 2016)  

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Spatial information divergence: using global and local indices to compare geographical masks applied to crime data / Ourania Kounad in Transactions in GIS, vol 19 n° 5 (October 2015)  

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