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A Raster SOLAP for the Visualization of Crime Data Fields

Authors:
Jean-Paul Kasprzyk
Jean-Paul Donnay

Keywords: Data Warehouse; Kernel Density Estimation; GIS; Business Intelligence; Crime Hotspots Analysis.

Abstract:
In order to effectively extract synthetic information from large spatial data sets, Spatial OnLine Analytical Processing (SOLAP) combines Geographic Information Systems (GIS) with Business Intelligence (BI) to query data warehouses through interactive vector maps. On the other hand, crime strategical analysis is usually based on raster maps computed by Kernel Density Estimation (KDE), then independent of any artificial boundary. This paper introduces an alternative vision of SOLAP which uses the raster model (instead of the vector one) in order to integrate crime data fields computed by KDE. It allows a continuous visualization of spatial data which, until now, has not been compatible with other SOLAP tools. The original geo-model is validated by a prototype adapted to the police needs.

Pages: 109 to 117

Copyright: Copyright (c) IARIA, 2016

Publication date: April 24, 2016

Published in: conference

ISSN: 2308-393X

ISBN: 978-1-61208-469-5

Location: Venice, Italy

Dates: from April 24, 2016 to April 28, 2016