Cell2Fire: A Cell-Based Forest Fire Growth Model to Support Strategic Landscape Management Planning

Abstract

Cell2Fire is a new cell-based wildland fire growth simulator designed to integrate data-driven landscape management planning models. The fire environment is modeled by partitioning the landscape into cells characterized by fuel, weather, moisture content, and topographic attributes. The model can use existing fire spread models such as the Canadian Forest Fire Behavior Prediction System to model fire growth. Cell2Fire is structured to facilitate its use for predicting the growth of individual fires or by embedding it in landscape management simulation models. Decision-making models such as fuel treatment/harvesting plans can be easily integrated and evaluated. It incorporates a series of out-of-the-box planning heuristics that provide benchmarks for comparison. We illustrate their use by applying and evaluating a series of harvesting plans for forest landscapes in Canada. We validated Cell2Fire by using it to predict the growth of both real and hypothetical fires, comparing our predictions with the fire scars produced by a validated fire growth simulator (Prometheus). Cell2Fire is implemented as an open-source project that exploits parallelism to efficiently support the modeling of fire growth across large spatial and temporal scales. Our experiments indicate that Cell2Fire is able to efficiently simulate wildfires (up to 30x faster) under different conditions with similar accuracy as state-of-the-art simulators (above 90% of accuracy). We demonstrate its effectiveness as part of a harvest planning optimization framework, identifying relevant metrics to capture and actions to mitigate the impact of wildfire uncertainty.

A fire spread simulator to support tactical management decisions for Mediterranean landscapes

“…Recently, a fire spread simulator based on the Canadian Forest Fire Behavior Prediction (FBP) Systems has been developed that is designed to support short term forest planning decisions (Pais et al, 2021a). Known as Cell2Fire, the new simulator overcomes certain limitations of the Prometheus spatial growth model (Tymstra et al, 2010), offering increased computational capacity, the ability to simulate multiple fire events, automatic generation of different metrics, maps of risk and fire propagation patterns.…”

“…Among the most important methods included in the "cell class" for fuel management planning is the ability to change the state of a cell dynamically (e.g., when a management is assigned to a specific cell: firebreak allocation, fuel conversion, etc.). This feature makes Cell2Fire different from other dedicated systems for these purposes, because Cell2Fire does not need to incur the effort of modifying the input fuel layers to apply an action on a cell or portion of the landscape (Pais et al, 2021a). The capacity to simulate and evaluate different management actions across the landscape, allows to create an objective function that could be optimized using different kinds of algorithms ranging from Metaheuristics (Zuuring et al, 1995;Chung et al, 2013), Simulation-based Optimization (Rytwinski and Crowe, 2010), to more advanced techniques that have taken advantage these days such as Reinforcement Learning techniques Lauer et al (2017).…”

“…Therefore, a first step before developing a complete decision support system for tactical forest planning, as the conceptually proposed in Figure 1, should be to develop a fire spread simulator called Cell2Fire_SB based on Pais et al (2021a). This simulator while providing all the advantages for fuel management planning associated to Cell2Fire, should be able to apply those rules for surface and canopy fire spread, that are commonly used in Europe and USA.…”

“…Each landscape cell has eight immediate neighbors known as adjacent cells, so a burning cell can potentially propagate a fire in eight directions (0, 45, 90, 135, 180, 225, 270, 315•). Fire is assumed to propagate between cells in a straight line from the center of a given cell to the center of an adjacent one [for more details, see Pais et al (2021a)].…”

“…Other, more novel metrics generated by Cell2Fire_SB can assist in defining specific policies to mitigate fire impacts by identifying which landscape cells are most prone to acting as fire corridors. As described in Pais et al (2021a), the Cell2Fire simulator records the shortest propagation paths during simulation time thanks to its ability to generate propagation graphs known as fire propagation trees in which the full spread dynamic is represented including the ROS, traveling times and other relevant information associated with the cells involved in a fire. The union of these individual graphs produces a multi-digraph (or a global propagation tree) containing all the fire dynamics information generated by multiple stochastic simulations.…”