Understanding crime using GIS and the context of COVID-19: the case of Saldanha Bay Municipality

Henrico, Ivan; Mayoyo, Nkosana; Mtshawu, Babalwa

doi:10.17159/2413-3108/2022/vn71a9539

Cited by 3 publications

(2 citation statements)

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“…There are various reasons why crime especially violent crime is prevalent, among others, the common causes are: poverty, unemployment, economic inequalities between the rich and poor, lack of education, population density (Henrico et al, 2022;Mathuthu, 2019;Bower Du Toit, 2014;Hull, 2000). Unemployment in (SA 32,7%) has been confirmed through empirical research, by Tshabalala, where the findings revealed that most of the people who commit crime are not only unemployed but are married, which indicates that their crimes are motivated by a pressure to provide for their families (Tshabalala, 2014).…”

Section: Causes Of Crimementioning

confidence: 99%

The Role of the South African Pentecostal and Charismatic Church in Sustainable Development: Focusing on Safety and Security

Matshobane

2023

pharosjot

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South Africa has one of the highest crime rates in the world, rated at number 4 globally and number 1 in the continent of Africa. Recently, the minister of Police in South Africa, Bheki Cele, revealed that violent crimes are extremely high with reported rape cases standing at an alarming 9516 between April-June 2022 while murders stand at 6424 in the same period. The question is what causes such a growth in crime but more importantly what role is played by PentecostalCharismatic churches in alleviating crime which negatively affects development in the country? A literary analysis of the nexus of crime and religion, buttressed by the case study of 2 megachurches who are part of South African Pentecostal and Charismatic churches (SAPCC), located in areas that are considered as hotspots of violent crimes, is used in this paper. The main objective of the article is to investigate the role of SAPCC in crime prevention and to position them as strategic role players in the realisation of Sustainable Development Goals with a focus on safety and security. This study proposes a decolonial theoretical framework based on the African proverb: ‘It takes a village to raise a child’, as a model for the prevention of crime caused by dysfunctional families, juxtaposed with the African practice of the ‘Palaver’, which brings all the community stakeholders in dialogue, to find a permanent solution to crime. Although the study is on SAPCC, the recommendations can be applicable to other church groups who are interested in applying a decolonial perspective to combating crime.

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Section: Causes Of Crimementioning

confidence: 99%

The Role of the South African Pentecostal and Charismatic Church in Sustainable Development: Focusing on Safety and Security

Matshobane

2023

pharosjot

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“…The Getis-Ord Gi* statistical model was applied to calculate Z-scores and p values for each point location to represent the COVID-19 incidence intensity. The ArcGIS Getis-Ord Gi* statistics tool was used to show the hotspot mapping and illustrate the spatial distribution and trends of crime in the Saldanha Bay Municipality [33]. These studies indicate the aggregation and stability of crime hot spots.…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Distribution and Influencing Factors of Theft during the Pre-COVID-19 and COVID-19 Periods: A Case Study of Haining City, Zhejiang, China

Jiang

Zheng

et al. 2023

IJGI

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Theft is an inevitable problem in the context of urbanization and poses a challenge to people’s lives and social stability. The study of theft and criminal behavior using spatiotemporal, big, demographic, and neighborhood data is important for guiding security prevention and control. In this study, we analyzed the theft frequency and location characteristics of the study area through mathematical statistics and hot spot analysis methods to discover the spatiotemporal divergence characteristics of theft in the study area during the pre-COVID-19 and COVID-19 periods. We detected the spatial variation pattern of the regression coefficients of the local areas of thefts in Haining City by modeling the influencing factors using the geographically weighted regression (GWR) analysis method. The results explained the relationship between theft and the influencing factors and showed that the regression coefficients had both positive and negative values in the pre-COVID-19 and COVID-19 periods, indicating that the spatial distribution of theft in urban areas of Haining City was not smooth. Factors related to life and work indicated densely populated areas had increased theft, and theft was negatively correlated with factors related to COVID-19. The other influencing factors were different in terms of their spatial distributions. Therefore, in terms of police prevention and control, video surveillance and police patrols need to be deployed in a focused manner to increase their inhibiting effect on theft according to the different effects of influencing factors during the pre-COVID-19 and COVID-19 periods.

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Enhancing short-term crime prediction with human mobility flows and deep learning architectures

Abrar

Awasthi

et al. 2022

EPJ Data Sci.

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Place-based short-term crime prediction models leverage the spatio-temporal patterns of historical crimes to predict aggregate volumes of crime incidents at specific locations over time. Under the umbrella of the crime opportunity theory, that suggests that human mobility can play a role in crime generation, increasing attention has been paid to the predictive power of human mobility in place-based short-term crime models. Researchers have used call detail records (CDR), data from location-based services such as Foursquare or from social media to characterize human mobility; and have shown that mobility metrics, together with historical crime data, can improve short-term crime prediction accuracy. In this paper, we propose to use a publicly available fine-grained human mobility dataset from a location intelligence company to explore the effects of human mobility features on short-term crime prediction. For that purpose, we conduct a comprehensive evaluation across multiple cities with diverse demographic characteristics, different types of crimes and various deep learning models; and we show that adding human mobility flow features to historical crimes can improve the F1 scores for a variety of neural crime prediction models across cities and types of crimes, with improvements ranging from 2% to 7%. Our analysis also shows that some neural architectures can slightly improve the crime prediction performance when compared to non-neural regression models by at most 2%.

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Understanding crime using GIS and the context of COVID-19: the case of Saldanha Bay Municipality

Cited by 3 publications

References 0 publications

The Role of the South African Pentecostal and Charismatic Church in Sustainable Development: Focusing on Safety and Security

The Role of the South African Pentecostal and Charismatic Church in Sustainable Development: Focusing on Safety and Security

Spatiotemporal Distribution and Influencing Factors of Theft during the Pre-COVID-19 and COVID-19 Periods: A Case Study of Haining City, Zhejiang, China

Enhancing short-term crime prediction with human mobility flows and deep learning architectures

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