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A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Hazards and Sustainability".

Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 16346

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Special Issue Editors

Prof. Lin Liu

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Guest Editor

Department of Geography and Geographic Information Science, University of Cincinnati, Cincinnati, OH, 45221, USA
Interests: GIS; remote sensing; GIS applications; crime analysis; public safety; big data

Prof. Guangwen Song

E-Mail Website
Guest Editor

Center of GeoInformatics for Public Security, School of Geography and Remote Sensing，Guangzhou University, Guangzhou, China.
Interests: spatial–temporal behavior; crime geography; public safety

Special Issue Information

Dear Colleagues,

Crime analysis for crime prevention and policing helps ensure public safety. Theories, methodologies and applications of crime analysis have evolved rapidly in the era of big data. Theories of environmental criminology have guided crime analysis for many years. Lately, new data generated from big data have led to new opportunities for theoretical and empirical research. For example, ambient population derived from high-resolution spatio-temporal big data have greatly improved the performance of various crime models. Streetview images provide a new data source for micro environmental audit, which has facilitated place-based research at a finer spatial scale. New methodologies such as machine learning have been used crime analysis and crime prediction at increased spatio-temporal resolutions. Such detailed knowledge has shown imporved effectiveness in targeted crime prevention. At the same time, new challenges have emerged as well. For example, fraud has replaced traditional crime types as the dominant crime in many cities. We have not been able to fight fraud effectively as this time. This special issue of Sustainability on Crime Analysis and Public Safety takes an interdisciplinary approach to tackle the above complex issues. This special issue aims to explore the interdisciplinary innovation to enhance research and application of crime analysis and public safety. We welcome contributions in theories, methods and applications.

On behalf of Sustainability, a peer-reviewed open-access journal, we are honored to invite you to contribute papers for the upcoming special issue on "Crime Analysis and Public Safety". Papers published in this journal could potentially reach broader audience, compared to traditional crime and geography journals.

This special issue focuses on the frontier research of crime analysis and public safety, especially those of interdisciplinary nature that take advantage of new data and new methodologies.

Scope:

New theories and new methods for crime analysis
Spatial analysis of public safety with urban GIS
Crime analysis in virtual environments
Crime hot spot and crime mapping
Crime location choice and offender behavior
Big data, machine learning and crime prediction
Micro environment and public safety
Crime prevention and policing
Assessment of crime prevention strategies
Fraud and cyber crime
Perception of safety

Keywords

crime analysis
public safety
spatial and temporal analysis
GIS technology

Published Papers (7 papers)

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Research

17 pages, 11359 KiB

Open AccessArticle

Trivariate Kernel Density Estimation of Spatiotemporal Crime Events with Case Study for Lithuania

by Michael Govorov, Giedrė Beconytė and Gennady Gienko

Sustainability 2023, 15(11), 8524; https://0-doi-org.brum.beds.ac.uk/10.3390/su15118524 - 24 May 2023

Viewed by 1015

Abstract

The paper presents the results of the investigation of the applicability of spatiotemporal kernel density estimation (KDE) methods for density mapping of violent crime in Lithuania. Spatiotemporal crime research helps to understand and control specific types of crime, thereby contributing to Sustainable Development Goals. The target dataset contained 135,989 records of the events registered by the police of Lithuania from 2015–2018 that were classified as violent. The research focused on choosing appropriate KDE functions and their parameters for modeling the spatiotemporal point pattern of this particular type of crime. The aim was to estimate density, mass, and intensity function(s) so that they can be used in further confirmatory spatial modeling. The application-driven objective was to obtain reliable and practically interpretable KDE surfaces of crime events. Several options for improving and extending the investigated KDE methods are demonstrated. Full article

(This article belongs to the Special Issue Sustainability on Crime Analysis and Public Safety)

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11 pages, 254 KiB

Open AccessArticle

Why Do People Trust the Police? A Case Study of Thailand

by Waiphot Kulachai and Sutham Cheurprakobkit

Sustainability 2023, 15(4), 3249; https://0-doi-org.brum.beds.ac.uk/10.3390/su15043249 - 10 Feb 2023

Cited by 1 | Viewed by 2535

Abstract

Trust in the police is considered vitally important in ensuring that citizens obey the law and cooperate with police officers. However, in recent times, the Royal Thai Police has been facing difficulties with the image of the organization, including lack of public trust resulting from the actions of some police officers. Therefore, this study investigated the level of trust in the police, as well as the factors that cause the public to trust the police. The samples used in this study were 971 residents in eastern Thailand. A questionnaire was used as a tool to collect data that were subjected to ordinary multiple regression analysis to test the hypotheses. The findings showed police effectiveness and fairness had a positive relationship with trust in the police. Age, corruption, and fear of crime had negative relationships with trust in the police. However, victimization had no association with trust in the police. Hence, the Royal Thai Police should place great importance on increasing the efficiency and effectiveness of police officers and treating people equally and fairly. In addition, corruption issues and the solving of crimes should be addressed to provide people with peace of mind and greater trust in the police. Full article

(This article belongs to the Special Issue Sustainability on Crime Analysis and Public Safety)

16 pages, 927 KiB

Open AccessArticle

Pattern and Explanation of Inter-City Crime Variation in South Korea

by Hyunjoong Kim and Eunyoung Seong

Sustainability 2022, 14(22), 15458; https://0-doi-org.brum.beds.ac.uk/10.3390/su142215458 - 21 Nov 2022

Viewed by 1977

Abstract

The primary purpose of this paper is to test the applicability of environmental criminology in South Korea. Moreover, it explores effective strategies from a spatial planning perspective by taking control of diverse spatial planning factors. The study area is South Korea, and the base year is 2016. A spatial econometric model is built to analyze the relationship between the built environment and three crimes (theft, violence, and sexual assault). As a result, the best spatial regression models for violent crime rate and sexual assault rate are a spatial error model (SEM) and a spatial autoregressive model (SAC), respectively. The most prominent finding is that the regression results in the three crimes are slightly different. The broken windows effect was negligible for significant crimes in South Korea. The influence of regional disorders on the incidence of crimes was marginal. In the three crime types, mixed land use affected rising crime rates, which aligns with some previous studies that mixed land use increases the likelihood of crime incidences. In contrast with a series of relevant works, brighter nighttime light has not effectively decreased crimes in South Korea. In South Korea, closed-circuit television (CCTV) did not play a role in deterring crimes. Lastly, socio-economic characteristics were closely connected with crime rates in South Korea. The theft rate, violent crime rate, and sexual assault rate confirm the reliability of environmental criminology. Although this study has examined the likelihood of applying environmental criminology, further research and discussions are followed for concrete plans. Full article

(This article belongs to the Special Issue Sustainability on Crime Analysis and Public Safety)

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24 pages, 9964 KiB

Open AccessArticle

Analyzing Street Crime Hotspots and Their Associated Factors in Chittagong City, Bangladesh

by Mohammad Ali Haider and Pawinee Iamtrakul

Sustainability 2022, 14(15), 9322; https://0-doi-org.brum.beds.ac.uk/10.3390/su14159322 - 29 Jul 2022

Cited by 8 | Viewed by 3305

Abstract

Urban street crime (USC) hotspots severely affect the residential and business neighborhood (RBN) areas of any urban center. This study analyzes USC hotspots and identifies the associated risk factors of becoming a USC hotspot in the residential and business neighborhood areas of Chittagong city. Primary and secondary data sources were used, but primary data played a primary role in this study. It was found that male, married, landlord, and middle-income groups of people are more likely to be victimized than the female, unmarried, renters, rich, and no-income groups. More street crime hotspots were found in the residential than in the business neighborhood. The statistical analysis of the logistic regression model for street crime victimization, a hotspot analysis model of a contour map, and a spatial autocorrelation map identified vulnerable locations in the residential and business neighborhood areas where people are frequently victimized by street crime. Qualitative and statistical analysis results show social, economic, geographical, governance, and planning and urban design factors play a vital role in developing USC hotspots in Chittagong city. The study outcomes need to be considered for an integrated approach to monitor and reduce street crime hotspots by policymakers, urban local government, and community leaders in Chittagong city. Full article

(This article belongs to the Special Issue Sustainability on Crime Analysis and Public Safety)

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13 pages, 3876 KiB

Open AccessArticle

Effects of Air Pollution on Assaults: Findings from South Korea

by Jeongin Eum and Hyungkyoo Kim

Sustainability 2021, 13(20), 11545; https://0-doi-org.brum.beds.ac.uk/10.3390/su132011545 - 19 Oct 2021

Cited by 3 | Viewed by 2124

Abstract

This study investigates the effects of concentration of air pollution on assault rates for 204 police districts of South Korea from 2001 to 2018. A series of panel spatial Durbin models for the concentration of ozone, fine dust, and nitrogen dioxide—three key air pollutants of the country—identify the significant impacts of air pollution on assault rates that vary from each other. Ozone is expected to induce more assaults both locally and regionally. Fine dust decreases assault rates of an area and also in neighboring areas. Nitrogen dioxide yields positive effects on the surrounding areas’ assault rates but not in area of pollution itself. Findings of this study suggest the need to incorporate active measures on air pollution and violent crime at both city and inter-city levels. They also propose the active sharing of information on air pollution and crime between cities and regions as a collaborative response. Full article

(This article belongs to the Special Issue Sustainability on Crime Analysis and Public Safety)

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15 pages, 2426 KiB

Open AccessArticle

Understanding the Spatiotemporal Pattern of Crimes in Changchun, China: A Bayesian Modeling Approach

by Daqian Liu, Wei Song, Chunliang Xiu and Jun Xu

Sustainability 2021, 13(19), 10500; https://0-doi-org.brum.beds.ac.uk/10.3390/su131910500 - 22 Sep 2021

Cited by 2 | Viewed by 1572

Abstract

Chinese cities have been undergoing extraordinary changes in many respects during the process of urbanization, which has caused crime patterns to evolve accordingly. This research applies a Bayesian spatiotemporal model to explore and understand the spatiotemporal patterns of crime risk from 2008 to 2017 in Changchun, China. The overall temporal trend of crime risk, the effects of land use covariates, spatial random effects, and area-specific differential trends are estimated through a Bayesian spatiotemporal model fitted using the Integrated Nested Laplace Approximation (INLA). The analytical results show that the regression coefficient for the overall temporal trend of crime risk changed from significantly positive to negative after the land use variables are incorporated into the Bayesian spatiotemporal model. The covariates of road density, commercial and recreational land per capita, residential land per capita, and industrial land per capita are found to be significantly associated with crime risk, which relates to classic theories in environmental criminology. In addition, some areas still exhibit significantly increasing crime risks compared with the general trend even after controlling for the land use covariates and the spatial random effects, which may provide insights for law enforcement and researchers regarding where more attention is required since there may be some unmeasured factors causing higher crime trend in these areas. Full article

(This article belongs to the Special Issue Sustainability on Crime Analysis and Public Safety)

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15 pages, 1493 KiB

Open AccessArticle

Multicriteria Ranking for the Efficient and Effective Assessment of Police Departments

by Thyago C. C. Nepomuceno, Cinzia Daraio and Ana Paula C. S. Costa

Sustainability 2021, 13(8), 4251; https://0-doi-org.brum.beds.ac.uk/10.3390/su13084251 - 12 Apr 2021

Cited by 7 | Viewed by 2244

Abstract

The nonparametric assessment of police efficiency and effectiveness is challenging due to the stochastic nature of criminal behavior and the subjective dependence on multiple decision criteria, leading to different prospects depending on the regulation, necessity, or organizational objective. There is a trade-off between sustainable efficiency and effectiveness in many police performance assessments, because many departments can be crime-specialized or cannot reproduce good results effectively on more severe or complex occurrences. This study aims to provide a non-compensatory ranking classification combining Conditional Frontier Analysis with the PROMETHEE II methodology for the multidimensional efficiency and effectiveness analysis of police. The results on Pernambuco (Brazil) Police departments offer interesting perspectives for public administrations concerning prioritizations of units based on the mitigation of resources and strategic objectives. Full article

(This article belongs to the Special Issue Sustainability on Crime Analysis and Public Safety)

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