At this stage of the project we are investigating the types of spatial data that are available and how they might help to provide contextual information to supplement crime data. For example, the figure below shows some burglary rates in two areas that are very close to each other. We have used the OS MasterMap Topography layer and spatially analysed each of the buildings to try to work out whether they are terraced, semi-detached, flats or detached.
Of course there are a number of other explanations for the difference in the crime rates between the two neighbourhoods, but undoubtedly the physical environment will have an effect. Therefore this type of information might be extremely useful to crime analysts or other people who are interested in understanding the context behind crime rates. The GeoCrimeData project will continue to explore these types of data and perform analyses that might reveal interesting spatial information.
Sometimes an end terrace is counted as semi-detached but not always. Is the house-type colouring from a datasource or done by the GeoCrimeData team based on visually looking at the OS MasterMap(ie counting the adjoining sides)?ReplyDelete
Gregory, the colouring has been done by the team using a computer algorithm (there are too many buildings for us to do this sort of thing by hand). It works by looking at each building and counting the number of adjacent buildings that share a common boundary. As you've pointed out it doesn't work perfectly yet, but we're going to improve the technique. In particular, we'd like to be able to distinguish between end-terraces and genuine semi-detached houses as this is important in a crime context.ReplyDelete
Ah okay, it makes sense now I know it was an automated process, I understand how the algorithm would be tricky and need refining.ReplyDelete