Exploratory spatial data analysis methodologies (ESDA): how they can be used to analyse forensic case data

Détails

ID Serval
serval:BIB_327C19866811
Type
Partie de livre
Sous-type
Chapitre: chapitre ou section
Collection
Publications
Institution
Titre
Exploratory spatial data analysis methodologies (ESDA): how they can be used to analyse forensic case data
Titre du livre
The Routledge International Handbook of Forensic Intelligence and Criminology
Auteur⸱e⸱s
Baechler Simon, Caneppele Stefano
Editeur
Routledge
Lieu d'édition
New York
ISBN
978-1-138-68821-6
Statut éditorial
Publié
Date de publication
01/01/2018
Peer-reviewed
Oui
Editeur⸱rice scientifique
Rossy Quentin, Décary-Hétu David, Delémont Olivier, Mulone Massimiliano
Numéro de chapitre
18
Pages
212-224
Langue
anglais
Résumé
Exploratory spatial data analysis methodologies (ESDA) have become popular and accessible in the last 20 years. Similarly to exploratory data analysis (EDA), ESDA methodologies focus on data and to their exploration/visualisation in order to find out what patterns/models can be found to better understand data. Many disciplines across social and hard sciences benefited from this new perspective on looking at spatial data, and criminology is no exception to that. Albeit the study of crime through the projection of forensic case data in the spatial dimension is still in its early stage, some examples pave an interesting way ahead.
This chapter briefly illustrates the characteristics of ESDA methodologies. Then it presents how they have been used in relation to several fields of forensic science (DNA, shoemarks, toolmarks, glovemarks, images and others). In conclusion, the authors discuss why and how spatial (and time) analysis of forensic case data may foster an original prospect to the study of crime, they address future developments and emphasise the need to bridge together different disciplines in that endeavour.
Création de la notice
12/01/2018 9:18
Dernière modification de la notice
20/08/2019 14:18
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