Malleson, N orcid.org/0000-0002-6977-0615, Steenbeek, W and Andresen, MA (2019) Identifying the appropriate spatial resolution for the analysis of crime patterns. PLoS ONE, 14 (6). e0218324. ISSN 1932-6203
Abstract
BACKGROUND:A key issue in the analysis of many spatial processes is the choice of an appropriate scale for the analysis. Smaller geographical units are generally preferable for the study of human phenomena because they are less likely to cause heterogeneous groups to be conflated. However, it can be harder to obtain data for small units and small-number problems can frustrate quantitative analysis. This research presents a new approach that can be used to estimate the most appropriate scale at which to aggregate point data to areas. DATA AND METHODS:The proposed method works by creating a number of regular grids with iteratively smaller cell sizes (increasing grid resolution) and estimating the similarity between two realisations of the point pattern at each resolution. The method is applied first to simulated point patterns and then to real publicly available crime data from the city of Vancouver, Canada. The crime types tested are residential burglary, commercial burglary, theft from vehicle and theft of bike. FINDINGS:The results provide evidence for the size of spatial unit that is the most appropriate for the different types of crime studied. Importantly, the results are dependent on both the number of events in the data and the degree of spatial clustering, so a single 'appropriate' scale is not identified. The method is nevertheless useful as a means of better estimating what spatial scale might be appropriate for a particular piece of analysis.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | (c) 2019, Malleson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License [https://creativecommons.org/licenses/by/4.0/], which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Geography (Leeds) > Centre for Spatial Analysis & Policy (Leeds) |
Funding Information: | Funder Grant number ESRC ES/L009900/1 ESRC ES/L011891/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 23 Jul 2019 11:32 |
Last Modified: | 23 Jul 2019 15:25 |
Status: | Published |
Publisher: | Public Library of Science |
Identification Number: | 10.1371/journal.pone.0218324 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:148905 |
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