University of Guilan Geographical Studies of Coastal Areas Journal 2783-1191 6 1 2025 03 21 The Effect of Climatic Elements on Creating Criminal Opportunities for the Theft (Case Study: Bandar Anzali) The Effect of Climatic Elements on Creating Criminal Opportunities for the Theft (Case Study: Bandar Anzali) 41 61 8870 10.22124/gscaj.2025.25383.1265 FA Mohammad Reza Pourghoulami Sarvandani Associate Professor, Department of Geography, Amin Comprehensive University of Police Sciences, Tehran, Iran. Bahman Fasihi Assistant Professor, Department of Basic Sciences, Amin Comprehensive University of Police Sciences, Tehran, Iran. Journal Article 2023 08 27 This study examined the impact of weather on theft crime and its spatial distribution. Crime occurs when offenders and potential targets converge. The research highlighted the role of climatic factors in creating opportunities for theft in the coastal city of Bandar Anzali between 2016 and 2020. The study adopted a descriptive-analytical approach with a spatiotemporal analysis perspective. The unit of analysis included all burglary data collected from the Police 110 database and climatic data obtained from a reliable meteorological source. Statistical analyses were conducted using ArcMap software. The Average Nearest Neighbor (ANN) index was employed to analyze the spatial distribution of theft data, while the Inverse Distance Weighting (IDW) interpolation method was used for crime mapping. Additionally, the Kernel Density Estimation (KDE) function was applied to estimate and predict theft crime density. The study also utilized the Ordinary Least Squares (OLS) model. The findings revealed that the highest occurrence of theft was in Zone 7 of Anzali, while the lowest was in Zone 1 of Ghāziān. The summarized results of the OLS regression model showed that climatic variables influenced theft crime, with some coefficients being positive and others negative. For instance, during spring, positive coefficients for minimum temperature were associated with an increase in theft, while negative coefficients for maximum temperature corresponded to a decrease in theft. Considering the Variance Inflation Factor (VIF) values, which were below 7.5, the regression model demonstrated reliable predictions for some variables. To assess the compatibility of climatic variables with theft crime in the geographical space, the results of the Breusch-Pagan (BP) test indicated that in all seasons, the p-value was greater than 0.05, showing the model's compatibility with the variables. This study clearly revealed that offenders adapt their criminal behaviors to the climatic conditions they encounter. This study examined the impact of weather on theft crime and its spatial distribution. Crime occurs when offenders and potential targets converge. The research highlighted the role of climatic factors in creating opportunities for theft in the coastal city of Bandar Anzali between 2016 and 2020. The study adopted a descriptive-analytical approach with a spatiotemporal analysis perspective. The unit of analysis included all burglary data collected from the Police 110 database and climatic data obtained from a reliable meteorological source. Statistical analyses were conducted using ArcMap software. The Average Nearest Neighbor (ANN) index was employed to analyze the spatial distribution of theft data, while the Inverse Distance Weighting (IDW) interpolation method was used for crime mapping. Additionally, the Kernel Density Estimation (KDE) function was applied to estimate and predict theft crime density. The study also utilized the Ordinary Least Squares (OLS) model. The findings revealed that the highest occurrence of theft was in Zone 7 of Anzali, while the lowest was in Zone 1 of Ghāziān. The summarized results of the OLS regression model showed that climatic variables influenced theft crime, with some coefficients being positive and others negative. For instance, during spring, positive coefficients for minimum temperature were associated with an increase in theft, while negative coefficients for maximum temperature corresponded to a decrease in theft. Considering the Variance Inflation Factor (VIF) values, which were below 7.5, the regression model demonstrated reliable predictions for some variables. To assess the compatibility of climatic variables with theft crime in the geographical space, the results of the Breusch-Pagan (BP) test indicated that in all seasons, the p-value was greater than 0.05, showing the model's compatibility with the variables. This study clearly revealed that offenders adapt their criminal behaviors to the climatic conditions they encounter. https://hgscaj.guilan.ac.ir/article_8870_e509163901e1e8c6d45ce27de9ab5e6b.pdf