This deliverable contains the reporting on stochastic mapping of bushfires as was carried out in the previous 22 months. It focuses on the secondments, carried out by the University of Twente, towards RMIT and the University of Melbourne, and the secondments of Pau Costa Foundation in SDIS2B in Corsica and to RMIT. Major findings are that voluntary geographical information serves as a major asset when collecting data, together with the data collection and validation that end-users (e.g. firefighters can done during and after a wildfire event) . A further quality assessment has to be done on those data. A large literature exists on the mapping of bushfires. The current process-based predictive models are well-equipped to deal with large disastrous fires, whereas more applied research involving end-users to be done on the development of spatial statistical models.