Research on geographical crime prediction which combine short-term (explicit) and longterm (implicit) crime risks are found today. However, their combining methodologies do not match criminological theories. In the current study, we try to build a new prediction method which combines two kind of risks according with existing criminological research. Using Risk Terrain Modeling (RTM), which is the most promising crime prediction method in Japan, we consider the shortterm risk elevation (that is, near repeat victimization) associated with the latest crime occurrence. Moreover, we use the residual obtained from a regression analysis of crime occurrence by the RTM risk value. Then, we present a case study using data on thefts from vehicle in Japan to verify prediction accuracy and reliability of the new model. Finally, we discuss the possibility of new prediction methods that combine environments attracting crime and crime itself.

To analyze the long-term trend of areal changes, areas of the black pine and all other species forests were investigated using GIS software on aerial photographs. The percentage of the black pine forest areas in 1988 increased by 23% compared with 1976 and that in 2009 decreased by 11% compared with 1988 in Miho no Matsubara. Those in Senbon Matsubara similarly increased by 23% and decreased by 17%, respectively. On the other hand, the areas of all other species consistently increased during the observed years and have come to be about four and three times their original areas in Miho no Matsubara and Senbon Matsubara, respectively. These results suggest that the increases in areas of the black pine forests may be due to the afforestation in two coastal forests and that their decreases may be due to cutting after pine wilt disease spread in Miho no Matsubara, and to the severe drought in 1995 and the typhoon hitting in the following year in Senbon Matsubara. The results also suggest that the increases in areas of all other species may be due to the management reduction for black pine forests in the two coastal forests.

Near repeat victimization (NRV) is a criminological phenomenon that makes it easier for the subsequent crime to occur within close spatiotemporal proximity from the occurrence of the first crime. However, this phenomenon is yet to be examined with threat incidents or street harassments including molestation, flashing, and haunting. In this study, we investigated NRV on threat incidents against children and women and examined how NRV trends change with relation to periods of time or characteristics of place. Three findings emerged: (1) NRV can be applied to many types of threat incidents experienced by children and women; (2) the degree of NRV is stronger in periods when the threat incident is frequent; and (3) the degree of NRV is linked to characteristics of places where women are victims of threat incidents, but not so in the case of children. In light of these results, we discussed practical implications to prevent threat incidents against children and women.

The study examined characteristics of crime maps and tables released at websites of all 47 prefectural police headquarters in Japan, in terms of spatio-temporal resolutions, crime types and population of jurisdiction.

The results are summarized as follows:

1) There were differences in type of map by crime type; larceny offenses were featured by density maps, while moral offenses and suspicious person informations were featured pin maps.

2) There were differences in crime map by population of jurisdiction; felonious offenses and violent offenses were more released to websites in large-scale prefectures than in small-scale prefectures.

3) There were differences in resolutions by crime type; High spatial resolution was used in violent offenses and larceny offenses than in elonious and intellectual offenses.

4) The spatio-temporal resolution of crime tables was insufficient to describe crime concentration, specially in small-scale prefectures.

Existing geographic profiling software that performs the widely tested probability distance strategies has issues when implemented in criminal investigation in Japan. Therefore, we developed the Spatial Analysis Methods of Offender's Nodes (SAMON) software based on a free software environment, R. Given the issues involving existing software, SAMON includes the following three features: (1) prediction of an offender's home base using different distance decay functions constructed from Japanese burglars' Journey-to-Crime distances; (2) validation of prediction accuracy in the solved case; and (3) calibration of the distance decay functions using a sample of solved cases in a type and region that the user is interested in. We expect that SAMON will improve the availability of probability distance strategies and its accuracy in the Japanese context.

The purpose of this research is to reconstruct Kichijoji Village's land allotment using records from a land survey conducted in 1664. In the drafting process, coordinate geometry and versioning functions were used to maintain the accuracy and efficiency of the work process involved in searching for the precise land allotment. From the reconstructed land allotment, it was revealed that the conversion of the unit of length 1 “Ken” as approximately 1.97 m was used for the zoning of Kichijoji Village instead of the conventional conversion of approximately 1.82 m. This paper also points out the possibility that the land survey conducted by the urban planner of Tokugawa Shogunate with the Dutch East India Company before its development of Kichijoji Village influenced the difference in the conversion of “Ken.”