Forensic GIS

doi:10.1007/978-94-017-8757-4

Cited by 19 publications

(2 citation statements)

References 81 publications

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“…Several scholars have studied changes in crime during and after natural disasters, particularly Atlantic hurricanes (Elmes et al 2014). Disasters cause widespread changes to routine activities through deaths, evacuations and disruption of working and leisure patterns, as well as through damage to the physical environment.…”

Section: Existing Evidencementioning

confidence: 99%

Initial evidence on the relationship between the coronavirus pandemic and crime in the United States

2020

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The COVID-19 pandemic led to substantial changes in the daily activities of millions of Americans, with many businesses and schools closed, public events cancelled and states introducing stay-at-home orders. This article used police-recorded open crime data to understand how the frequency of common types of crime changed in 16 large cities across the United States in the early months of 2020. Seasonal auto-regressive integrated moving average (SARIMA) models of crime in previous years were used to forecast the expected frequency of crime in 2020 in the absence of the pandemic. The forecasts from these models were then compared to the actual frequency of crime during the early months of the pandemic. There were no significant changes in the frequency of serious assaults in public or (contrary to the concerns of policy makers) any change to the frequency of serious assaults in residences. In some cities, there were reductions in residential burglary but little change in non-residential burglary. Thefts of motor vehicles decreased in some cities while there were diverging patterns of thefts from motor vehicles. These results are used to make suggestions for future research into the relationships between the coronavirus pandemic and different crimes.

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Section: Existing Evidencementioning

confidence: 99%

Initial evidence on the relationship between the coronavirus pandemic and crime in the United States

2020

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“…However, if the goal for using CFS is to provide a proxy data source for the traditionally-used recorded incident data, little research has been done to test the extent to which CFS could stand in for recorded incidents-especially considering that these data sets are collected with differing goals. Recent examples of research utilizing CFS data include measuring fear of crime, collective efficacy, or other concepts closely tied to measuring police presence or the request for police presence (Alpert, Macdonald, & Dunham, 2005;Boivin & Cordeau, 2011;Conley & Stein, 2014;Junior & Muniz, 2005;Klinger & Bridges, 1997;Levitt, 1998;Nesbary, 1998;Renauer, 2012;Telep, Mitchell, & Weisburd, 2014). However, there remains an underlying question of whether CFS data have the potential to reveal more information related to recorded crime or could serve as a reasonable proxy given the differences between the two datasets.…”

Section: Appendixmentioning

confidence: 99%

Boundaries and Policing: Space, Jurisdictions, and Roles in the Collection of Official Crime Data

Barnett-Ryan¹

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The Uniform Crime Reporting (UCR) Program is a law enforcement statistical system open to unreported information due to its voluntary nature. As such, there needs to be a valid and accepted means to estimate official reports of crime for those different levels of geography where reporting may be incomplete. Current methods of imputing and modeling UCR data, which have not been updated since the 1960s, are based upon conceptualizations of law enforcement agencies that may no longer be valid. These older models do not appropriately represent the law enforcement assessment of space and place and its effects on discretionary recording behavior. The number of specialized agencies that share jurisdiction and population with primary law enforcement agencies has increased since early data modeling techniques were developed around the 1960s. This study explores the connection between the policing and the collection of crime data to advance our understanding of how differences among types of law enforcement may impact the discretionary decision to record data. To explore this topic, I have divided this study into three papers touching on differing dimensions of place, scale, and uncertainty connected to the recording of law enforcement data. The data for these papers includes national UCR Program data, as well as calls for service and recorded incident data from two law enforcement agencies in the mid-South

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Geolocation in Crime Detection and Prevention

Militello

2022

Investigating and Preventing Crime in the Digital Era

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Forensic GIS

Cited by 19 publications

References 81 publications

Initial evidence on the relationship between the coronavirus pandemic and crime in the United States

Initial evidence on the relationship between the coronavirus pandemic and crime in the United States

Boundaries and Policing: Space, Jurisdictions, and Roles in the Collection of Official Crime Data

Geolocation in Crime Detection and Prevention

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