Investigating spatial diffusion pattern of residential burglary in Mashhad in the 2011-2017 Period

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BAZARGAN MEHDI; AJZA SHOKOUHI MOHAMMAD

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Journal: GEOGRAPHICAL DATA Year:2020 | Volume:29 | Issue:113 Page(s): 73-91

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Title

Investigating spatial diffusion pattern of residential burglary in Mashhad in the 2011-2017 Period

Author(s)

BAZARGAN MEHDI | AJZA SHOKOUHI MOHAMMAD | Issue Writer Certificate

Keywords

Spatial diffusionQ2

Spatial analysisQ1

crimesQ1

Residential burglaryQ1

MashhadQ1

Abstract

Introduction Nowadays, theft-especially Residential burglary-is considered as one of the most common and frequent crimes in many countries of the world, including Iran. As such, it has become a pervasive and serious problem with various social, economic, and security-related aspects. Investigating geographical dimensions of this crime facilitates the process of exploring this phenomenon. Space and its special features play an important and undeniable role in crime commitment, because space has always been considered as one of the most important factors in commitment of financial crimes such as Residential burglary. Spatial analysis and geographical investigation of crimes seek to provide a spatial presentation of criminal actions, crime dispersion, and crime hotspots. This type of crime analysis basically aims to provide a model for decreasing crime commitment in urban spaces. Accordingly, the present research seeks tomodel Spatial diffusion of Residential burglary crimes in MashhadusingHogstrand’ s Spatial diffusion theory. Materials and methods The present study is performed based on descriptive-analytic and qualitative methods. The research sample includes cases of Residential burglary committed in Mashhad in the 2011-2017period. Data analysis was performed using ArcGIS software. Case study area includes Mashhad, with an area of about 35187 hectares, a population of more than 3057679, and a population density of 87 people per hectare. Results and discussion Police reports in Mashhad suggest that the highest crime rates belong to the 2nd and 3thdistricts, and the lowest rates belong toSamen (around Razavi Shrine), the 12th, and 8thdistricts. 70% of crimes in Mashhad are committed in informal settlements including the 2nd, 3th, 4th, 5th, 6th, 7th, and 10thdistricts. However, only 10. 6% of the city area and 29. 3% of its population belong to these districts. Furthermore, the highest crime rates have been reported in 2017. In 2011, only two major crime hotspots were observed in Mashahd (in the 2nd and 3thdistricts). Results suggest that crimes have spread from one place to anotherin Mashhad, which indicates a close relationship between crime and distance factor. In other words, proximity to a crime hotspothas resulted in rapid spread of crimes, and due to the short distance, nearby places have been affected more quickly. Informal settlements of Mashhad are located in eastern, northern, and northeastern districts, which contain 99% of crime hotspots. This indicates that spatial autocorrelation of crimes in informal settlements of Mashhad is relatively high, which has led to formation of crime hotspots in these districts. However, moving from marginalized areas towards southern districts of Mashhad (more prosperous regions), spatial correlation of crimes decreases, and lead to formation of 99% of cold spots. Conclusion The present research has investigated the Spatial diffusion pattern of crimes in Mashhad in 2011-2017period. To reach this end, crime hotspots were investigated by quantitative methods such as Kernel density, Moran coefficient, and crime hotspot analysis. Results suggest that the highest crime rates are reported in the 2nd and 3thdistricts, while the lowest rates are reported in Samen (around Razavi Shrine), the 12th, and 8th regions. In fact, 70% of crimes in Mashhad are committed in informal settlements including the 2nd, 3th, 4th, 5th, 6th, 7th, and 10thdistricts. Moreover, statistics indicate that for every100000 people, anaverage of 75/2 cases of crimes have been reported in the 2011-2017period. Results of Moran coefficient for Spatial diffusion of crimes indicated the presence of a cluster distribution of crimes in Mashhad. Meanwhile, Spatial diffusion pattern of crimes in Mashhad suggests that the first crime hotspots were formed in northern, eastern, and northeastern districtsof Mashhad, and crimes have spread from these to other districts (more central and prosperous regions such as the 8th and 9thdistricts). In fact, investigations suggest that crimes are spreading from informal settlements to other regionsof Mashhad, and acompatible Spatial diffusion pattern of crimes exists in this city.

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APA: Copy

BAZARGAN, MEHDI, & AJZA SHOKOUHI, MOHAMMAD. (2020). Investigating spatial diffusion pattern of residential burglary in Mashhad in the 2011-2017 Period. GEOGRAPHICAL DATA, 29(113 ), 73-91. SID. https://sid.ir/paper/381047/en

Vancouver: Copy

BAZARGAN MEHDI, AJZA SHOKOUHI MOHAMMAD. Investigating spatial diffusion pattern of residential burglary in Mashhad in the 2011-2017 Period. GEOGRAPHICAL DATA[Internet]. 2020;29(113 ):73-91. Available from: https://sid.ir/paper/381047/en

IEEE: Copy

MEHDI BAZARGAN, and MOHAMMAD AJZA SHOKOUHI, “Investigating spatial diffusion pattern of residential burglary in Mashhad in the 2011-2017 Period,” GEOGRAPHICAL DATA, vol. 29, no. 113 , pp. 73–91, 2020, [Online]. Available: https://sid.ir/paper/381047/en

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