@article {bnh-5279, title = {A lightning-caused wildfire ignition forecasting model for operational use}, journal = {Agricultural and Forest Meteorology}, volume = {253-254}, year = {2018}, month = {05/2018}, pages = {16}, chapter = {233}, abstract = {

Lightning-caused wildfires are responsible for substantial losses of lives and property worldwide. Convective storms can create large numbers of ignitions that can overwhelm suppression efforts. Both long- and short-term risk planning could benefit from daily, spatially-explicit forecasts of lightning ignitions. We fitted a logistic regression generalised additive model to lightning-caused ignitions in the state of Victoria, Australia. We proposed a new method for model selection that complemented existing methods and further reduced the number of variables in the model with minimal change to predictive power. We introduced an approach for deconstructing ignition forecasts into contributions from the individual covariates, which could allow model output to be more readily integrated with existing intuitive understandings of ignition likelihood. Our method of model selection reduced the number of variables in the model by 37.5\% with little change to the predictive power. The final model showed good predictive ability (AUC 0.859) and we demonstrated the utility of the model for short term forecasting by comparing model predictions with observed lightning-caused fires over three time periods, two of which had extreme fire conditions, while the third was randomly chosen from our validation dataset. The model presented in this paper shows good predictive power and advancements in model output could allow fire managers to more easily interpret model forecasts.

}, doi = {10.1016/j.agrformet.2018.01.037}, url = {https://www.sciencedirect.com/science/article/pii/S0168192318300376}, author = {Nicholas Read and Thomas Duff and Peter Taylor} } @article {BF-3174, title = {Procrustes based metrics for spatial validation and calibration of two-dimensional perimeter spread models: A case study considering fire}, journal = {Agricultural and Forest Meteorology}, volume = {160}, year = {2012}, month = {7/2012}, pages = {110 - 117}, abstract = {A number of phenomena in natural systems exhibit spread from a point source facilitated by a transport vector. Such occurrences are an important focus of landscape management, and include fires, wind driven disease and pollutant spills. Two-dimensional dynamic spread models are used to simulate the impacts of such events, determine risks and optimise responses. These models produce spatially coherent outputs that are not easily verified through traditional regression approaches. Validation of predictions is an essential part of model development and is necessary for the improvement of predictive performance. Current methods of evaluation are rarely systematic and are typically undertaken through subjective comparison of simulation outputs with observed features. There are few methods suitable for the objective analysis of freeform spread patterns, and it is proposed that a pseudo-landmark approach be adopted to allow the use of landmark based analysis methods. Vector driven spread patterns exhibit a degree of spatial structure, with distinct origin points and elongate shapes resulting from the predominant vector trajectory. These can be used as references to generate analogous landmarks for perimeter comparison. To describe differences, three indices derived from Procrustes analysis are proposed. These provide metrics to evaluate differences in perimeter orientation, size and shape. A case study simulating wildfire spread was used to demonstrate the proposed methodology. It was found to be effective for the description of perimeter differences and has potential for the validation and calibration of spread models. A number of assumptions were recognised and limitations in assigning pseudo-landmarks considered.}, issn = {01681923}, doi = {10.1016/j.agrformet.2012.03.002}, author = {Thomas Duff and Chong, Derek and Peter Taylor and Tolhurst, K.G.} }