ABSTRACT
The methods in the previous chapter were developed to study locations in a continuous plane (referred to as planar spatial analysis). Point-level crime data, however, has an inherent structure to it. Since typically the data will be geocoded at the street level address, crime data almost always will appear alongside the spatial network of roads and streets. Put simply: crimes won't appear randomly anywhere in our 2 dimensional representation of the city, they will only appear along the street network covering this city. Clearly the offences are constrained to only occur along the street network. In this chapter we provide an introduction to the study of crime along networks by exploring the creation of network representations from geographical vector objects, linking data to meaningful micro-places such as street segment (or in in a transportation example, train line segment) or street junction (or for transport research a train or bus station), introducing the idea of hot routes, evaluating crime concentration in these types of micro places using Gini coefficient and Lorenz curve, street profile analysis - an alternative (non-spatial) way to visualise crime along a network, and introducing the functionality of spatstat for the analysis of events along networks.
