Cellular Automata (CA) represent a formal frame for dynamical systems, which evolve on the base of local interactions. Some types of landslide, such as debris flows, match well this requirement. The latest hexagonal release (S_3–hex) of the deterministic model SCIDDICA, specifically developed for simulating debris flows, is described. For CA simulation purposes, landslides can be viewed as a dynamical system, subdivided into elementary parts, whose state evolves exclusively as a consequence of local interactions within a spatial and temporal discretum. Space is the world of the CA, here constituted by hexagonal cells. The attributes of each cell ("substates") describe physical characteristics. For computational reasons, the natural phenomenon is "decomposed" into a number of elementary processes, whose proper composition makes up the "transition function" of the CA. By simultaneously applying this function to all the cells, the evolution of the phenomenon can be simulated in terms of modifications of the substates. SCIDDICA S_3–hex exhibits a great flexibility in modelling debris flows. With respect to the previous releases of the model, the mechanism of progressive erosion of the soil cover has been added to the transition function. Considered substates are: altitude; thickness and energy of landslide debris; depth of erodable soil cover; debris outflows. Considered elementary processes are: mobilisation triggering and effect (T₁), debris outflows (I₁), update of landslide debris thickness and energy (I₂), and energy loss (T₂). Simulations of real debris flows, occurred in Campania (Southern Italy) in May 1998 (Sarno) and December 1999 (San Martino V.C. and Cervinara), have been performed for model calibration purposes; some examples of analysis are briefly described. Possible applications of the method are: risk mapping, also based on a statistical approach; evaluating the effects of mitigation actions (e.g. stream deviations, topographic alterations, channelling, embankments, bridges, etc.) on flow development.

Cell-based methods for simulating wildfires can be computationally more efficient than techniques based on the fire perimeter expansion. In spite of this, their success has been limited by the distortions that plague the simulated shapes. This article presents a novel algorithm for wildfire simulation through Cellular Automata (CA), which is able to effectively mitigate the problem of distorted fire shapes. Such a result is obtained allowing spread directions that are not constrained to the few angles imposed by the lattice of cells and the neighborhood size. The characteristics of the proposed algorithm are empirically investigated under homogeneous conditions through some comparisons with the outcomes of a typical CA-based simulator. Also, using two significant heterogeneous landscapes, a comparison with the vector-based simulator FARSITE is discussed. According to the results of this study, the proposed approach performs significantly better, in terms of accuracy, than the CA taken as reference. In addition, at a far less computational cost, it provides burned regions that are equivalent, for practical purposes, to those given by FARSITE.