@book {bnh-6841, title = {Feeling the heat: International perspectives on the prevention of wildfire ignition}, series = {Series on Climate Change and Society}, year = {2020}, pages = {319}, publisher = {Vernon Press}, organization = {Vernon Press}, edition = {1st}, address = {Wilmington}, abstract = {

In the context of climate change, world population growth and crashing ecological systems, wildfire is often a catastrophic and traumatic event. Its impact can include loss of life, life-changing injuries, long-term psychological stress; increases in domestic violence; destruction of properties, business and livestock; long-term housing insecurity; increased insurance premiums, fire-fighting, legal and health costs; as well as significant changes and species losses in the natural environment.

}, keywords = {ignition, Planning, prevention, response, risk, Wildfire}, issn = {978-1-64889-010-9}, url = {https://vernonpress.com/book/890}, author = {Janet Stanley and Alan March and James Ogloff and James Thompson} } @article {bnh-5688, title = {Assessment of the Dual Polarimetric Sentinel-1A Data for Forest Fuel Moisture Content Estimation}, journal = {Remote Sensing}, volume = {11}, year = {2019}, month = {07/2019}, abstract = {

Fuel moisture content (FMC) is a crucial variable affecting fuel ignition and rate of fire spread. Much work so far has focused on the usage of remote sensing data from multiple sensors to derive FMC; however, little attention has been devoted to the usage of the C-band Sentinel-1A data. In this study, we aimed to test the performance of C-band Sentinel-1A data for multi-temporal retrieval of forest FMC by coupling the bare soil backscatter linear model with the vegetation backscatter water cloud model (WCM). This coupled model that linked the observed backscatter directly to FMC, was firstly calibrated using field FMC measurements and corresponding synthetic aperture radar (SAR) backscatters (VV and VH), and then a look-up table (LUT) comprising of the modelled VH backscatter and FMC was built by running the calibrated model forwardly. The absolute difference (MAEr) of modelled and observed VH backscatters was selected as the cost function to search the optimal FMC from the LUT. The performance of the presented methodology was verified using the three-fold cross-validation method by dividing the whole samples into equal three parts. Two parts were used for the model calibration and the other one for the validation, and this was repeated three times. The results showed that the estimated and measured forest FMC were consistent across the three validation samples, with the root mean square error (RMSE) of 19.53\% (Sample 1), 12.64\% (Sample 2) and 15.45\% (Sample 3). To further test the performance of the C-band Sentinel-1A data for forest FMC estimation, our results were compared to those obtained using the optical Landsat 8 Operational Land Imager (OLI) data and the empirical partial least squares regression (PLSR) method. The latter resulted in higher RMSE between estimated and measured forest FMC with 20.11\% (Sample 1), 26.21\% (Sample 2) and 26.73\% (Sample 3) than the presented Sentinel-1A data-based method. Hence, this study demonstrated that the good capability of C-band Sentinel-1A data for forest FMC retrieval, opening the possibility of developing a new operational SAR data-based methodology for forest FMC estimation.

}, keywords = {bare soil backscatter linear model, dual polarimetric Sentinel-1A, fuel moisture content, ignition, remote sensing, vegetation backscatter water cloud model}, doi = {https://doi.org/10.3390/rs11131568}, url = {https://www.mdpi.com/2072-4292/11/13/1568}, author = {Long Wang and Xingwen Quan and Binbin He and Marta Yebra and Minfeng Xing and Xiangzhuo Liu} } @article {bnh-5648, title = {Developing and testing models of the drivers of anthropogenic and lightning-caused wildfire ignitions in south-eastern Australia}, journal = {Journal of Environmental Management}, volume = {235}, year = {2019}, month = {01/2019}, chapter = {34-41}, abstract = {

Considerable investments are made in managing fire risk to human assets, including a growing use of fire behaviour simulation tools to allocate expenditure. Understanding fire risk requires estimation of the likelihood of ignition, spread of the fire and impact on assets. The ability to estimate and predict risk requires both the development of ignition likelihood models and the evaluation of these models in novel environments. We developed models for natural and anthropogenic ignitions in the south-eastern Australian state of Victoria incorporating variables relating to fire weather, terrain and the built environment. Fire weather conditions had a consistently positive effect on the likelihood of ignition, although they contributed much more to lightning (57\%) and power transmission (55\%) ignitions than the 7 other modelled causes (8{\textendash}32\%). The built environment played an important role in driving anthropogenic ignitions. Housing density was the most important variable in most models and proximity to roads had a consistently positive effect. In contrast, the best model for lightning ignitions included a positive relationship with primary productivity, as represented by annual rainfall. These patterns are broadly consistent with previous ignition modelling studies. The models developed for Victoria were tested in the neighbouring fire prone states of South Australia and Tasmania. The anthropogenic ignition model performed well in South Australia (AUC = 0.969) and Tasmania (AUC = 0.848), whereas the natural ignition model only performed well in South Australia (AUC = 0.972; Tasmania AUC = 0.612). Model performance may have been impaired by much lower lightning ignition rates in South Australia and Tasmania than in Victoria. This study shows that the spatial likelihood of ignition can be reliably predicted based on readily available meteorological and biophysical data. Furthermore, the strong performance of anthropogenic and natural ignition models in novel environments suggests there are some universal drivers of ignition likelihood across south-eastern Australia.

}, keywords = {Bushfire, ignition, Risk modelling, Wildfire}, doi = {https://doi.org/10.1016/j.jenvman.2019.01.055}, url = {https://www.sciencedirect.com/science/article/pii/S0301479719300568}, author = {Hamish Clarke and Rebecca Gibson and Brett Cirulis and Ross Bradstock and Trent Penman} } @article {bnh-7242, title = {The effect of ignition protocol on grassfire development}, journal = {International Journal of Wildland Fire}, volume = {29}, year = {2019}, month = {11/2019}, pages = {70-80}, abstract = {

The effect of ignition protocol on the development of grassfires is investigated using physics-based simulation. Simulation allows measurement of the forward rate of spread of a fire as a function of time at high temporal resolution. Two ignition protocols are considered: the inward ignition protocol, where the ignition proceeds in a straight line from the edges of the burnable fire plot to the centre of the plot; and the outwards ignition protocol, where the ignition proceeds from the centre of the burnable fire plot to the edges of the plot. In addition to the two ignition protocols, the wind speed, time taken for the ignition to be completed and ignition line length are varied. The rate of spread (R) of the resultant fires is analysed. The outwards ignition protocol leads to an (approximately) monotonic increase in\ R, whereas the inward ignition protocol can lead to a peak in\ R\ before decreasing to the quasi-equilibrium\ R. The fires simulated here typically take 50 m from the ignition line to develop a quasi-equilibrium\ R. The results suggest that a faster ignition is preferable to achieve a quasi-equilibrium\ R\ in the shortest distance from the ignition line.

}, keywords = {grassfire, ignition, physics simulation}, doi = {https://doi.org/10.1071/WF19046}, url = {https://www.publish.csiro.au/WF/WF19046}, author = {Duncan Sutherland and Jason J. Sharples and Khalid Moinuddin} } @article {bnh-4819, title = {Simulation of fuel bed ignition by wildland firebrands}, journal = {International Journal of Wildland Fire}, volume = {27}, year = {2018}, month = {07/2018}, abstract = {

A 3-D mathematical model of fuel bed (FB) ignition initiated by glowing firebrands originating during wildland fires is proposed. In order to test and verify the model, a series of experiments was conducted to determine the FB ignition time by a single pine bark and twig firebrand (Pinus sylvestris). Irrespective of the pine bark sample sizes and experimental conditions, the ignition of the FB was not observed. Conversely, pine twigs, under certain parameters, ignited the FB in the range of densities (60{\textendash}105 kg m-3) and with the airflow velocity of >=2 m s-1. The results of the mathematical modelling have shown that a single pine bark firebrand <=5 cm long with a temperature of T <= 1073 K does not ignite in the flaming mode the FB, and only the thermal energy of larger particles is sufficient for flaming ignition of the adjacent layers of the FB. The analysis of the results has shown that the firebrand length is a major factor in the initiation of ignition. Comparison of the calculated and observed FB ignition times by a single firebrand have shown that our modelling accords well with the experimental results.

}, keywords = {critical conditions, experiment, ignition, modelling, spotting.}, url = {https://www.publish.csiro.au/WF/WF17083}, author = {O. V. Matvienko and D. P. Kasymov and Alex Filkov and O. I. Daneyko and D. A. Gorbatov} }