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1. Identity statement
Reference TypeJournal Article
Sitemtc-m21d.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP3W34T/4527H3S
Repositorysid.inpe.br/mtc-m21d/2021/07.02.13.25   (restricted access)
Last Update2021:07.02.13.25.17 (UTC) simone
Metadata Repositorysid.inpe.br/mtc-m21d/2021/07.02.13.25.17
Metadata Last Update2022:04.03.22.27.26 (UTC) administrator
DOI10.1007/s10940-020-09474-6
ISSN0748-4518
Citation KeyRamosSilvClarPrat:2021:ToFiBe
TitleToo Fine to be Good? Issues of Granularity, Uniformity and Error in Spatial Crime Analysis
Year2021
MonthJune
Access Date2024, May 19
Type of Workjournal article
Secondary TypePRE PI
Number of Files1
Size1659 KiB
2. Context
Author1 Ramos, Rafael Blakeley Guimarães
2 Silva, Bráulio F. A.
3 Clarke, Keith C.
4 Prates, Marcos
ORCID1 0000-0001-9307-5922
Group1 DIIAV-CGCT-INPE-MCTI-GOV-BR
Affiliation1 Instituto Nacional de Pesquisas Espaciais (INPE)
2 Universidade Federal de Minas Gerais (UFMG)
3 University of California Santa Barbara
4 Universidade Federal de Minas Gerais (UFMG)
Author e-Mail Address1 rafaelgramos@gmail.com
JournalJournal of Quantitative Criminology
Volume37
Number2
Pages419-443
History (UTC)2021-07-02 13:26:06 :: simone -> administrator :: 2021
2022-04-03 22:27:26 :: administrator -> simone :: 2021
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Version Typepublisher
KeywordsCrime Mapping
Criminology of Place
Error
Granularity
Scale
AbstractObjectives: Crime counts are sensitive to granularity choice. There is an increasing interest in analyzing crime at very fine granularities, such as street segments, with one of the reasons being that coarse granularities mask hot spots of crime. However, if granularities are too fine, counts may become unstable and unrepresentative. In this paper, we develop a method for determining a granularity that provides a compromise between these two criteria. Methods: Our method starts by estimating internal uniformity and robustness to error for different granularities, then deciding on the granularity offering the best balance between the two. Internal uniformity is measured as the proportion of areal units that pass a test of complete spatial randomness for their internal crime distribution. Robustness to error is measured based on the average of the estimated coefficient of variation for each crime count. Results: Our method was tested for burglaries, robberies and homicides in the city of Belo Horizonte, Brazil. Estimated optimal granularities were coarser than street segments but finer than neighborhoods. The proportion of units concentrating 50% of all crime was between 11% and 23%. Conclusions: By balancing internal uniformity and robustness to error, our method is capable of producing more reliable crime maps. Our methodology shows that finer is not necessarily better in the micro-analysis of crime, and that units coarser than street segments might be better for this type of study. Finally, the observed crime clustering in our study was less intense than the expected from the law of crime concentration.
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Languageen
Target Fileramos_too.pdf
User Groupsimone
Reader Groupadministrator
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Visibilityshown
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Update Permissionnot transferred
5. Allied materials
Next Higher Units8JMKD3MGPCW/46KUATE
DisseminationWEBSCI; PORTALCAPES; SCOPUS.
Host Collectionurlib.net/www/2021/06.04.03.40
6. Notes
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