A cartographic image was created for each of these factors, once again divided into pixels of 20 metres by 20. In the case of the image referring to the itineraries, the pixels which presented a withdrawal zone whose distance accumulated with the different crime scenes was close to 100km had the highest score. For the image representing proximity to main roads, the pixels closest to these roads also had a higher score. The same goes, finally, for the pixels in the image which position zones according to their rural character. Each of these factors, depending on their importance had a greater or lesser weight. Respecting the distance was the most important, followed by proximity to main roads, and finally, the rural character of the region. ‘We then added up the results of each of these images by offsetting the points according to their weight. The higher the value of the pixels, the greater the chance that the criminals had hidden their vehicle there.’ For basic information technology reasons the value of each pixel varied between 0 and 255.

The search had nevertheless not yet been completed. Once again following a discussion with the police it turned out that the pixels had to accommodate a built up area. In all likelihood the criminals had needed a place to hide (garage, house, hangar, etc.). If this constraint was respected the pixel was validated. If not, it was discarded. This was technically possible thanks to a simple question of arithmetic. Whether or not a pixel contained a built up zone was differentiated in a binary manner. In the case were nothing had been built the pixel obtained a value of 0. In the opposite case it was accorded the value of 1. The three added up factors were thus multiplied by the constraint. The sum of a figure multiplied by 0 is always equal to 0. The cells which obtained a zero score were ruled out. As for the pixels with the best scores, they were extracted and represented the zone to be investigated. ‘In keeping only these cells, there remained only a small portion of road possible in the region studies,’ report the delighted researchers. ‘If we had not been in a simulation situation, we would have dispatched a police raid on the basis of these results.’

Helping to refine, and not resolve, the investigations

‘Once we had classed the pixels according to these criteria, we asked the police to provide us with the solution,’ says Marie Trotta. ‘It turned out that the pixel which housed the warehouse where the criminals hid had a value of 252 out of 255 on our map. It figured, based on our reasoning, amongst the most plausible withdrawal zones.’ In the present case, the geographical appraisal worked. But obviously it consists of an aid based on hypotheses, which cannot guarantee an absolute success rate. These types of information remain pathways to be explored.

A transposable approach

The data to which the researchers had access to certainly reflected a specific case. Each series of crimes has its unique characteristics, its clues and its unknowns. For example the unusual fact that the vehicle’s owner knew the mileage was a key piece of information to retrace the criminals’ route.