Table 1 A summary of papers in the thematic issue
From: Editorial: crime patterns in time and space: the dynamics of crime opportunities in urban areas
Authors | Summary and contribution |
|---|---|
Daily shifts in population. The funnelling hypothesis | |
 Felson and BoivÃn | Visitors funnelling crime risk into particular census tracts and away from others. Visitors found to impact property and violent crime more than residents. Canadian case study. |
Space-time settings and the spatial-temporal landscape (school, bars and subway stations) | |
 Herrmann | Examines timing of street robbery hot spots by hour of the day. Compares school days and none school days. Finds two distinct patterns of robbery. School day 3:00 pm robbery hotspots adjacent to subway stations and schools; 1:00 am non-school day robbery hotspots close to bars and subway stations. US case study. |
 Irvin-Erickson and La Vigne | Examines crimes at subway stations. Finds multiple types of crime in highly dynamic settings, considering peak versus off-peak and daytime versus night-time. Evidence of stations crime acting spatio-temporally as attractors and crime generators. US case study. |
 Geoffrion, Sader, Ouellet and BoivÃn | Data gathered over a year for a large nightclub, with aggression disaggregated by hour of evening and location inside the bar. Spatio-temporal patterns of aggression evident within micro settings inside bar-room environment. Canadian case study. |
 Newton | Examine stability of crime hot spots around licensed premises. Consider how crime hot spots may change to different locations, to different times, or hot spots for different crime types may occur simultaneously, or at differing times of the day or days of the week at the same location. Examines disorder, criminal damage and violence. UK case study. |
Understanding crime in time and space | |
 Andresen and Malleson | Examines intra-week patterns of crime in time and space. Finds unique crime patterns for differing crime types in both time and space by different days of the week. For example on Saturdays, theft from vehicle increased in the downtown parks and recreational park areas on, and assaults also increased in the bar districts. Canadian case study. |
 Tompson and Bowers | Seasonal patterns of street robbery by hour of day and season, taking into consideration weather, thermal comfort, and likelihood that people will go out. Identifies discretionary routines more likely to be influenced by weather. UK case study. |
 Malleson and Andresen | Examines risk of crime taking into account ambient population and hour of day. Identifies significant hotspots of risk based on dynamics of underlying population in both time and space. UK case study. |
Preventing crime in time and space | |
 Boba and Santos | Hot spots examined by hours and degree of repetition, discussing how police can respond with that information. US case study. |