Spatial decision tree for accident data analysis

Accident data analysis deals with identifying a set of conditions of accident occurrences and the importance of the corresponding implication. It is of prime importance because it gives an insight into the reasons behind the number of fatal and other major injuries. Accident data has an inherent spatial context associated with it, as the location of the accident has an important role to play in its severity. This paper aims at categorizing and analyzing the accident data and drawing some meaningful inferences, that are implicit to the data. A spatial decision tree based approach has been used and implemented to draw some useful conclusions, which are spatially relevant with the severity of the accident. The experimentation has been carried out on the accident dataset, collected from the National Highway (NH6) connecting Kharagpur and Kolkata, India. The results exhibit some latent patterns, useful for further accident management.