Abstract: Valparaiso, a central-southern region in Chile, has one of the highest rates of wildfire occurrence in the country. The constant threat of fires is mainly due to its highly flammable forest plantation, composed of 97.5% Pinus radiata and Eucalyptus globulus. Fuel moisture content is one of the most relevant parameters for studying fire spreading and risk, and can be estimated from the reflectance of leaves in the short wave infra-red (SWIR) range, not easily available in most vision-based sensors. Therefore, this work addresses the problem of estimating the water content of leaves from the two previously mentioned species, without any knowledge of their spectrum in the SWIR band. To this end, and for validation purposes, the reflectance of 90 leaves per species, at five dehydration stages, were taken between 350 nm and 2500 nm (full spectrum). Then, two machine-learning regressors were trained with 70% of the data set to determine the unknown reflectance, in the range 1000 nm-2500 nm. Results were validated with the remaining 30% of the data, achieving a root mean square error less than 9% in the spectrum estimation, and an error of 10% in spectral indices related to water content estimation. (C) 2020 IAgrE. Published by Elsevier Ltd. All rights reserved.

Abstract: Forests are suffering water stress due to climate change; in some parts of the globe, forests are being exposed to the highest temperatures historically recorded. Machine learning techniques combined with robotic platforms and artificial vision systems have been used to provide remote monitoring of the health of the forest, including moisture content, chlorophyll, and nitrogen estimation, forest canopy, and forest degradation, among others. However, artificial intelligence techniques evolve fast associated with the computational resources; data acquisition, and processing change accordingly. This article is aimed at gathering the latest developments in remote monitoring of the health of the forests, with special emphasis on the most important vegetation parameters (structural and morphological), using machine learning techniques. The analysis presented here gathered 108 articles from the last 5 years, and we conclude by showing the newest developments in AI tools that might be used in the near future.

Abstract: The theory to predict ignition of solid fuels exposed to incident radiant heat fluxes has permitted to obtain simple correlations of the ignition delay time with the incident heat flux which are useful in practical engineering applications. However, the theory was developed under the assumption that radiation does not penetrate into the solid phase. In the case of semi-transparent solids, where the penetration of radiation plays an important role in the heating and subsequent ignition of the fuel, the predictions of the classical ignition theory are not applicable. A new theory for the piloted ignition of optically thin cylindrical fuels has been developed. The theory uses an integral method and an approximation of the radiative transfer equation within the solid to predict the heating of an inert solid. An exact and an approximate analytical solution are obtained. The predictions are compared with piloted ignition experiments of clear PMMA cylinders. The results indicate that for opticallythin media, the heating and ignition are not sensible to the thermal conductivity of the solid, they are highly dependent on the in-depth absorption coefficient. Using the approximate solution, the correlation 1/t(ig) proportional to (q)over dot(inc)'' was established. This correlation is adequate for engineering applications, and allows the estimation of effective properties of the solid fuel. The form of the correlation that was obtained is due to the integral method used in the solution of the heat equation, and does not imply that the semi-transparent solid behaves like a thermally thin material. The approximate solution presented in this article constitutes a useful tool for pencil-and-paper calculations and is an advancement in the understanding of solid-phase ignition processes. (C) 2018 The Combustion Institute. Published by Elsevier Inc. All rights reserved.

Abstract: Heat fluxes from fires are strongly time-dependent. Historically, the thermal ignition theory in its classical form has neglected this time dependency until recent years, where theories have been developed to include time-varying incident heat fluxes. This article proposes a simplified general model formulation for the heating of solid fuels exposed to four different heat flux behaviors, considering the penetration of radiation into the medium. The incident heat flux cases developed where: Constant, Linear, Exponential and Polynomial, which represent different situations related to structural and wildland fires. The analytical models consider a spatially averaged medium temperature and exact and approximate solutions are presented, based on the critical ignition temperature criterion, which are valid for solids of any optical thickness. The results were validated by comparison with various models presented in the literature, where the model granted in this work was capable to adjust to all of them, especially when high heat fluxes are involved. Therefore, the proposed model acquires a significant engineering utility since it provides a single model to be used as a general and versatile tool to predict the ignition delay time in a manageable way for solid fuels exposed to different fire conditions.

Abstract: Experiments were carried out in the Idealized-Firebrand Ignition Test (I-FIT), a bench scale apparatus specifically designed to test the ignition of forest fuel layers from a representative firebrand. A cylindrical heater was used to model the firebrand, which allowed to control the incident radiative heat flux on the specimen, from the critical heat flux up to 25 kW/m2, for five different porosities of the fuel layer. Experimental ignition delay times were interpreted based on a theoretical model of the radiative heating of the fuel layer. Radiative heat transfer within the fuel layer was modeled by using the P1 approximation. In the limit of small ignition delay times an analytical expression was derived to correlate the inverse of the ignition time to the incident heat flux. This analytical expression is used to obtain the ignition temperature and effective properties for the forest fuel layers, namely the product of the fuel volume fraction by solid fuel density and solid heat capacity. Analytical solutions were found to be consistent with experimental data and a correlation relating the inverse of the non-dimensional time-toignition to the non-dimensional heat flux is provided.

Abstract: Background. Wildfires have caused significant damage in Chile, with critical infrastructure being vulnerable to extreme wildfires. Aim. This work describes a methodology for estimating wildfire risk that was applied to an electrical substation in the wildland-urban interface (WUI) of Valparaiso, Chile. Methods. Wildfire risk is defined as the product between the probability of a wildfire reaching infrastructure at the WUI and its consequences or impacts. The former is determined with event trees combined with modelled burn probability. Wildfire consequence is considered as the ignition probability of a proxy fuel within the substation, as a function of the incident heat flux using a probit expression derived from experimental data. The heat flux is estimated using modelled fire intensity and geometry and a corresponding view factor from an assumed solid flame. Key results. The probability of normal and extreme fires reaching the WUI is of the order of 10(-4) and 10(-6) events/year, respectively. Total wildfire risk is of the order of 10(-5) to 10(-4) events/year Conclusions. This methodology offers a comprehensive interpretation of wildfire risk that considers both wildfire likelihood and consequences. Implications. The methodology is an interesting tool for quantitatively assessing wildfire risk of critical infrastructure and risk mitigation measures.

Abstract: The effect of decreasing incident heat fluxes on the ignition delay time of dry pine needles is addressed in the present study. A customized modular instrument (I-FIT) that uses radiant heaters to simulate idealized firebrands ensures experimental repeatability for combustion experiments. Linear incident heat flux ramps are obtained by controlling the power of the heating element, thus simulating idealized firebrands. An analytical model based on the thermal ignition theory was developed and solved analytically using an integral approach. This model includes convective losses and in-depth penetration of radiation. Radiation was modeled using the P1 approximation. The theoretical model is complemented and validated by experimental data, showing increments of the ignition delay times when the negative slope steepness over time increases for the same heat flux. For given values of the initial incident heat flux on the sample, a critical slope beta(cri) is observed. For slopes steeper than this critical value, ignition is not attained.

Abstract: Fuel moisture content (FMC) proved to be one of the most relevant parameters for controlling fire behavior and risk, particularly at the wildland-urban interface (WUI). Data relating FMC to spectral indexes for different species are an important requirement identified by the wildfire safety community. In Valparaiso, the WUI is mainly composed of Eucalyptus Globulus and Pinus Radiata-commonly found in Mediterranean WUI areas-which represent the 97.51% of the forests plantation inventory. In this work we study the spectral signature of these species under different levels of FMC. In particular, we analyze the behavior of the spectral reflectance per each species at five dehydration stages, obtaining eighteen spectral indexes related to water content and, for Eucalyptus Globulus, the area of each leave-associated with the water content-is also computed. As the main outcome of this research, we provide a validated linear regression model associated with each spectral index and the fuel moisture content and moisture loss, per each species studied.