Author Archives: A Crime Mapper
I wrote a post a couple of weeks ago about using facial features as the primary key in a database. Today, the Tapei Times published a news article about the Tapei Police Department’s new suspect tracking system that has integrated over 13,000 traffic cameras, a proposed 27,000 high resolution cameras, GPS, GIS and the incident reporting telephone reporting system.
The $68.9 million image monitoring system automatically matches facial pictures with identity card images and other databases to help the police to identify suspects. I guess it was closer than I had expected…
The other day I had a conversation with someone who was facing an issue that most of us have faced; not knowing the exact time when an event occurred but knowing the time range when it happened. Example: a business was burgled after the shop closed at 7p and before it opened at 9a.
We were talking about how to handle this type of situation, how can it be included in the analysis even though we do not have an exact time of occurrence? I was searching for different methods when I came across an article and paper written by Jerry Ratcliffe back in 2002 on aoristic crime analysis.
It is an interesting way of looking at the temporal nature of events, the article defines three ways of searching when time is a factor:
Rigid – search to determine whether an the event occurred within in a defined time range. This method will only select events that happened between the start and end time point.
Average – search to determine if the average time calculated by the possible start time and end time of the event occurred in the defined time range. The average will take the midpoint of the time range and determine if it falls within the time range.
Aoristic – this type of search looks to determine if the event might have occurred within the search time range.
I can see this as being another good tool in the toolbox when time is one of the variables. Now I just need to figure out how to write that as a query in my GIS application…
Source Information: Ratcliffe, J.H. (2002) Aoristic signatures and the spatio-temporal analysis of high volume crime patterns. Journal of Quantitive Criminology, 2002, Volume 18 Issue 1: 23-43