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This brief report aims to reveal crime concentration at the district level in Tokyo and Osaka, Japan, two cities characterized by low crime rates. Eight types of property crimes that occurred between 2008 and 2017 in Tokyo and Osaka and had been aggregated by the census enumeration district were analyzed using the Gini coefficient based on the Poisson-Gamma method. The results indicated three patterns. First, crime concentration was identified. Second, the degree of concentration depended upon crime type. Commercial burglary was the most concentrated crime type, and theft from vehicle and theft from vending machine were the most dispersed. Third, crime concentration patterns either remained stable or became more concentrated over time. Additionally, while theft of bicycle was found to display stable concentration levels over time, the concentration level of purse snatching was fluid. On the basis of the results, this report discusses the possibility of establishing the "Law of Crime Concentration" (LCC) in two Japanese cities.

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Geographical crime prediction have been the focus of much research in western countries over the past decade and crime prediction systems are already in use several countries including Japan where a prefectural police department have recently introduced a certain system. However there has been no prior research into this field in Japan. This paper presents a systematic review of geographical crime prediction and discusses their relevance to the Japanese context. We identify four categories of geographical crime prediction methods: 1 surveillance of space-time clusters of crime; 2 estimation of crime intensity based on space-time interaction; 3 prediction of crime risk based on environmental factors; and 4 prediction of crime numbers/possibilities. These categories are based on established theories and have been developed independently of each other. Finally, we suggest directions for future developments of this research field in Japan.

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