Spectral analysis of forest fire noise for early detection using wireless sensor networks

Background Fire behaviour assessments of past wildfire events have major implications for anticipating post-fire ecosystem responses and fuel treatments to mitigate extreme fire behaviour of subsequent wildfires. Aims This study evaluates for the first time the potential of remote sensing techniques to provide explicit estimates of fire type (surface fire, intermittent crown fire, and continuous crown fire) in Mediterranean ecosystems. Methods Random Forest classification was used to assess the capability of spectral indices and multiple endmember spectral mixture analysis (MESMA) image fractions (char, photosynthetic vegetation, non-photosynthetic vegetation) retrieved from Sentinel-2 data to predict fire type across four large wildfires Key results MESMA fraction images procured more accurate fire type estimates in broadleaf and conifer forests than spectral indices, without remarkable confusion among fire types. High crown fire likelihood in conifer and broadleaf forests was linked to a post-fire MESMA char fractional cover of about 0.8, providing a direct physical interpretation. Conclusions Intrinsic biophysical characteristics such as the fractional cover of char retrieved from sub-pixel techniques with physical basis are accurate to assess fire type given the direct physical interpretation. Implications MESMA may be leveraged by land managers to determine fire type across large areas, but further validation with field data is advised.

Ecological techniques for wildfire mitigation: Two distinct fuelbreak approaches and their fusion

In this study, we propose a new approach to detect and map active fire area by means of Sentinel-2 data. Sentinel-2 Multi-Spectral Instrument (MSI) is comprised of visible spectral bands, near infrared (NIR), and short wave infrared (SWIR) spectral bands. These spectral bands, band 8A (865 nm), band 11 (at 1.61 μm), and band 12 (at 2.19 μm), are employed to roughly approximate the temperature within the forest fire range (400 − 1500°C) using Planck’s blackbody radiation law. The Normalised Difference Indices (NDI) of band 11 with 8A and band 12 with 11 are formulated, namely NDI1 and NDI2, respectively. The criteria of NDI1, NDI2, and band 12 ranges are estimated empirically to identify forest fire area into four thermal anomaly levels, i.e., high-temperature crown fire, typical crown fire, surface fire or smoldering area and remains of the fire. For the high-temperature crown fire area, band 12 value is very high, all indices are positive, and the NDI2 is lower than NDI1, following Planck’s curve for temperature higher than 1200 K. For the typical crown fire area, the band 12 value is high, and the NDI2 can be higher than NDI1. For the smolder area, the band 12 value is in the middle range, and the NDI2 must be larger than 0.2. Finally, for remains area, the band 12 value is in the lower range, and NDI1 must be higher than –0.27. This work shows that the active fire area can be identified and mapped into four thermal anomaly levels. This approach can be employed for rapid fire management as soon as the image data is obtained.

Forest fires resulting from long periods of drought cause extensive forest ecosystemdestruction and can impact on the carbon balance and air quality and feed back to theclimate system, regionally and globally. Past fire frequency is reconstructed for TuvanScots pine stands using dendrochronology and statistics. Central Tuvan Scotspine (Pinus sylvestris) stands are subject to annual fire regimes; however highintensity fires are rare but they are responsible for most of the damage. Low,medium, and high severity fires have shaped the multi-story Scots pine communities,locally and regionally. Fire type and frequency are directly related to weather andclimate and are also dependent on anthropogenic influences. The primary dryperiod, which promotes fire ignition and spread, in Tuva occurs in April andMay. In some years, the precipitation deficit combined with high air temperaturesinduces long periods of drought. Unlike the typical surface fire regime, forest firesthat burn during these extreme droughts often become crown fires that resultin substantial forest damage and carbon release. The mean fire interval (MFI)is found to be 10.4 years in Balgazyn stands, and the landscape-scale MFI is22.4 years. High severity, stand-replacing crown fires have a longer MFI. Thewarmer and dryer weather that is predicted by global climate models is evident inTuva, and we believe that these changes in weather and climate have resulted inincreased fire intensity and severity, rather than fire frequency in the Tuvan region.

Graham, Russell T.; McCaffrey, Sarah; Jain, Theresa B. (tech. eds.) 2004. Science basis for changing forest structure to modify wildfire behavior and severity. Gen. Tech. Rep. RMRS-GTR-120. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 43 p. Fire, other disturbances, physical setting, weather, and climate shape the structure and function of forests throughout the Western United States. More than 80 years of fire research have shown that physical setting, fuels, and weather combine to determine wildfire intensity (the rate at which it consumes fuel) and severity (the effect fire has on vegetation, soils, buildings, watersheds, and so forth). Millions of acres of forestlands (mainly in dry forests dominated by ponderosa pine and/or Douglas-fir) contain a high accumulation of flammable fuels compared to conditions prior to the 20th century. Forests with high stem density and fuel loading combined with extreme fire weather conditions have led to severe and large wildfires (such as those seen in the summers of 2000, 2002, and 2003) that have put a number of important values at risk. Although homes in the path of a wildfire are perhaps the most immediately recognized value, these wildfires also put numerous other human and ecological values at risk, such as power grids, drinking water supplies, firefighter safety, critical habitat, soil productivity, and air quality. For a given set of weather conditions, fire behavior is strongly influenced by stand and fuel structure. Crown fires in the dry forest types represent an increasing challenge for fire management as well as a general threat to the ecology of these forests and the closely associated human values. Crown fires are dependent on the sequence of available fuels starting from the ground surface to the canopy. Limiting crown fire in these forests can be accomplished by actions that manage in concert the surface, ladder, and crown fuels. Reducing crown fire and wildland fire growth across landscapes decreases the chances of developing large wildfires that affect human values adjacent to forested areas. However, a narrow focus on minimizing crown fire potential will not necessarily reduce the damage to homes and ecosystems when fires do occur. Homes are often ignited by embers flying far from the fire front, and by surface fires. Fire effects on ecosystems can also occur during surface fires where surface and understory fuels and deep organic layers are sufficient to generate high temperatures for long periods. Fuel treatments can help produce forest structures and fuel characteristics that then reduce the likelihood that wildfires will cause large, rapid changes in biophysical conditions. Fuel treatments can also help modify fire behavior sufficiently so that some wildfires can be suppressed more easily. Subsequent, sustained fuel treatments can maintain these conditions. Different fuel reduction methods target different components of the fuel bed. Thinning mainly affects standing vegetation, and other types of fuel treatments such as prescribed fire and pile burning woody fuels are needed to modify the combustion environment of surface fuels. In forests that have not experienced fire for many decades, multiple fuel treatments—that is, thinning and surface fuel reduction—may be required to significantly affect crown fire and surface fire hazard. Fuel treatments cannot guarantee benign fire behavior but can reduce the probability that extreme fire behavior will occur. Fuel treatments can be designed to restore forest conditions to a more resilient and resistant condition than now exists in many forests, and subsequent management could maintain these conditions, particularly in dry forests (ponderosa pine and Douglas-fir) where crown fires were historically infrequent. The degree of risk reduction will depend to some degree on the level of investment, social and economic acceptability of treatments, and concurrent consideration of other resource values (for example,

Among the predominant natural disturbances affecting Mediterranean regions, nowadays forest fires frequently occur in Central and Northern Europe, potentially leading to several issues in ecological, geomorphological, economic and social terms. In this regard, local authorities are becoming gradually confident with their management even where forest fires were historically scarce. In this context, semi-empirical models are particularly useful in estimating fire behaviour, in order to predict key factors related with wildfires risk (e.g., flames length, fire type, rate of spread). At the same time, accurate estimation of models inputs actually represents the principal limitation to outputs reliability, mainly due to the difficulty in retrieving specific data like canopy fuel characteristics or fire behaviour fuel models. In light with the above, there is a growing need to find new methods able to infer such simulation variables, for example starting from remote sensing data acquisition and elaboration, as well as by adapting already existing equations and workflows to European specific contexts. The project RETURN aims therefore to enhance the spatial mapping of fire simulators inputs layers within the Alpine region by coupling an extensive field data collection with high-resolution Light Detection and Ranging (LiDAR) and Unmanned Aerial Vehicle (UAV)-based data collection. The results of the Project could be useful in increasing the amount of information available for local administrations of the Alpine region, aiming to ease the application of fire behavior simulators to manage such a natural disturbance increasingly frequent in this mountain area.

Based on analysis of the interaction between a spreading fire and its surrounding environment, in nominally constant and uniform boundary conditions, it is observed that the evolution of the fire front is characterised by fluctuations of its properties, including (in particular) its rate of spread (ROS). Using a database with a wide range of fires with different time–space scales, it is shown that the amplitude of the fluctuation in ROS is proportional to the average value of the ROS and that the frequency of oscillation varies with the type of fire, and for a given fuel, increases with the average ROS. In fast-spreading fires, the large amplitude of ROS increase and sudden decrease promote the intermittent behaviour of the fire. In general, the amplitude and period required for the ROS increase are larger than for its decrease. However, the acceleration and deceleration phases in junction fires do not follow this rule, suggesting the existence of different convective processes of interaction between the flow and fire. This oscillation explains the variability in many fires at all scales and challenges the current interpretation based on the three factors affecting fire spread and the classification of wind or topography-driven fires.

In North American temperate forests, white pine ( Pinus strobus L.) and red pine ( Pinus resinosa Ait.) establish on sites cleared by infrequent high-severity crown fires and persist in the long-term when low-severity surface fires clear the understory and expose mineral seedbeds, facilitating regeneration. Considerable reduction of white pine and red pine abundance over the last two centuries due to overharvesting and fire suppression prompted experiments with prescribed burning. In La Mauricie National Park (LMNP; southern Québec, Canada) all natural fires have been actively suppressed since the 1970s, and only prescribed (surface) burns occurred since the 1990s. Taking advantage of this unique setting, we quantified charcoal particles in the sediments of three lakes within LMNP to identify a tentative charcoal accumulation threshold differentiating surface fires from crown fires. We then compared the signal left by the current regime of surface fires with the fire regimes of other periods of the Holocene. Based on the threshold, we showed that a mixed regime of frequent low-severity surface fires and infrequent high-severity crown fires was associated to high abundance of white pine and red pine during the Holocene Thermal Maximum (ca. 8400–4500 cal. yr BP). Regimes of only surface fires during the early neoglacial period (ca. 4500–1500 cal. yr BP) or only crown fires during the early Holocene (before 8400 cal. yr BP) were less conducive to the establishment and persistence of white pine and red pine. Instead of systematically suppressing crown fires, they should be allowed to burn while protecting infrastructures.

Mount Rushmore National Memorial in the Black Hills of South Dakota is known worldwide for its massive sculpture of four of the United States' most respected presidents. The Memorial landscape also is covered by extensive ponderosa pine (Pinus ponderosa) forest that has not burned in over a century. We compiled dendroecological and forest structural data from 29 plots across the 517-ha Memorial and used fire behavior modeling to reconstruct the historical fire regime and forest structure and compare them to current conditions. The historical fire regime is best characterized as one of low-severity surface fires with occasional (> 100 years) patches (< 100 ha) of passive crown fire. We estimate that only approximately 3.3% of the landscape burned as crown fire during 22 landscape fire years (recorded at > or = 25% of plots) between 1529 and 1893. The last landscape fire was in 1893. Mean fire intervals before 1893 varied depending on spatial scale, from 34 years based on scar-to-scar intervals on individual trees to 16 years between landscape fire years. Modal fire intervals were 11-15 years and did not vary with scale. Fire rotation (the time to burn an area the size of the study area) was estimated to be 30 years for surface fire and 800+ years for crown fire. The current forest is denser and contains more small trees, fewer large trees, lower canopy base heights, and greater canopy bulk density than a reconstructed historical (1870) forest. Fire behavior modeling using the NEXUS program suggests that surface fires would have dominated fire behavior in the 1870 forest during both moderate and severe weather conditions, while crown fire would dominate in the current forest especially under severe weather. Changes in the fire regime and forest structure at Mount Rushmore parallel those seen in ponderosa pine forests from the southwestern United States. Shifts from historical to current forest structure and the increased likelihood of crown fire justify the need for forest restoration before a catastrophic wildfire occurs and adversely impacts the ecological and aesthetic setting of the Mount Rushmore sculpture.

Динамика развития лесного пожара является важной составляющей его прогнозирования. Для прогнозирования низовых пожаров используют математическую модель развития пожара, связывающую скорость распространения кромки пожара с породным составом леса, условиями местности и погоды. Исходные данные, изложенные в методических указаниях и справочниках по профилактике и тушению лесных пожаров, содержат сведения, полученные на основании статистической обработки лесных пожаров севера европейской части Российской Федерации. Известно, что пожароопасный период в этом регионе длится всего 2-3 месяца, а класс пожарной опасности по условиям погоды не поднимается выше IV. Климат и погодные условия юга европейской части России в значительной мере отличаются от севера. Пожароопасный период в лесах длится 6-7 месяцев, класс пожарной опасности по условиям погоды может достигать V, а породный состав лесных массивов близок к средней полосе России и ее северной части: сосна обыкновенная (Pinus sylvestris L., 1753) и дуб черешчатый (Quercus robur L., 1753). В связи с этим интересным было определить динамику развития лесных низовых пожаров и сравнить ее со справочными значениями. Для этого был проведен анализ развития лесных низовых пожаров в массивах с преобладающей породой - сосна и дуб, а также выявить влияние погодных условий на динамику лесных пожаров. Показано, что динамика лесных низовых пожаров в хвойных лесах Саратовской области в 2-4 раза выше справочных значений, а в лиственных лесах разница может достигать 5-10 раз. The dynamics of forest fire is an important component of wild fires forecasting and prevention. These days a mathematical model for forecasting wild fires is used. This model was formulated from certain quantitative relationship between wild fire rate and natural conditions (type of forest and landscape, weather conditions, etc.). The initial data for wild fire behaviour calculation can be found in basic manuals for wild fire fighting completed for north of European part of Russian Federation. It is known that wild fire season in this region lasts for 2-3 months only with the fire danger class achieving VI, while fire season in the south of European part is much longer and equals to 6-7 months with the wild fire danger index reaching V. The forest composition of these territories is close to the one of Central Russia and its northern territories and includes such species as commom pine (Pinus sylvestris L., 1753) and English oak (Quercus robur L., 1753). This indicates fundamentally different weather conditions between the northern and southern parts of the country. In this case it can be interesting to compare the dynamics of wild fires in the Saratov region to northern forests. For this the analysis of wild ground fires growth was performed in the areas with predominant number of pines and oaks. Also, it was necessary to identify influence of weather conditions on wild fire dynamics. It is shown that the dynamics of ground fires in the same types forests of the Saratov region is 2-4 times higher for coniferous forests than the reference values, and in deciduous forests the difference can reach 5-10 times.

Wildfires are an increasing threat in Mediterranean regions, where extreme fire weather and long-term fuel accumulation are driving more frequent and severe events. In this context, fast and reliable fire spread simulations are essential to support both risk mitigation planning and real-time emergency management. PROPAGATOR is a stochastic Cellular Automata (CA) wildfire spread simulator designed to generate ensemble-based fire spread forecasts. The model, currently available as both an online application and open-source software, operates within a raster-based framework in which each cell is described by static attributes (e.g. fuel type, topography) and dynamic drivers (e.g. wind, fuel moisture). Fire propagation is modelled through a stochastic contamination process between burning and unburned cells, allowing the production of probabilistic maps of fire spread, as well as statistics on rate of spread and fireline intensity. PROPAGATOR also includes the capability to simulate the spotting phenomenon and suppression actions such as water drops or firebreak construction, making it suitable for both operational decision support during active fires and pre-event risk mitigation analyses. A current limitation of operational applications of PROPAGATOR is its focus on surface fire propagation, with no explicit representation of vertical fuel structure or transitions to crown fire. Crown fires, however, are characterized by higher spread rates, greater energy release, and increased unpredictability, with major implications for suppression effectiveness and ecological impacts. To address this limitation, an enhanced version of PROPAGATOR has been developed by extending the model to a quasi-three-dimensional (2.5D) representation of fuels, enabling the simulation of crown fire processes within the stochastic CA framework. The proposed Crown Fire Module relies on established empirical and semi-empirical formulations for crown fire initiation and spread that are compatible with a cellular automata approach. Crown fire initiation is governed by surface fireline intensity and crown base height, while crown fire rate of spread depends primarily on canopy bulk density and fire behaviour. These mechanisms have been integrated into the propagation rules of PROPAGATOR, allowing dynamic transitions between surface and crown fire behaviour within a probabilistic modelling framework. The implementation of these processes requires detailed information on both surface and canopy fuel structure and characteristics, which remains challenging at operational scales. To address this issue, we investigated the use of UAV-based LiDAR remote sensing to derive key fuel structure parameters using semi-automatic algorithms available in the literature. This approach offers a balance between spatial detail and areal coverage that is suitable for operational wildfire applications. A pilot study conducted in the Venafro area (Molise, Italy), based on a past wildfire event with a comprehensive dataset describing fire evolution, provided high-resolution inputs to test the enhanced model. By explicitly simulating surface-to-crown fire transitions, the upgraded version of PROPAGATOR aims to improve decision support for wildfire risk management, supporting applications ranging from fuel treatment planning to operational response under extreme fire weather conditions.

Crown fire and surface fire: effects on myxomycetes inhabiting pine plantations

Statistical denoising of signals in the S-transform domain

Chapter 8 - Forest and Land Fires in Indonesia: Assessment and Mitigation

The development of sandy soils under pine forests and the influence of forest fires on the soil properties have been studied in the Baikal region, The profile of background soils consists of a litter layer and a thin humus-accumulative horizon with features of grain bleaching in the lower part. In the WRB system, such soils are classified as Eutric Arenosols (Ochric). They have an acid reaction, fulvate humus, and slightly developed features of the Al–Fe-humus process. Post-pyrogenic soil successions depend on the type of fire. In fifteen years after the ground fire, a soil with specific pyrogenic horizons in the upper part of the profile was formed. It had a high content of carbonaceous matter and humus, a slightly acid reaction, and a relatively high content of exchangeable and total calcium. The soil humus was of the fulvate–humate type, and the humus pool considerably increased. These changes were related to the presence of charcoal microparticles adsorbing dispersed substances on their surface and detected in thin sections. After the crown fire with the destruction of the tree stand and activation of wind erosion, the features of pyrogenesis were poorly expressed in the soils. In this case, post-pyrogenic soils had a weakly developed immature profile, acid reaction, and a low content of humus of the humate–fulvate type. The properties of the background soils allow us to classify them as podzolized humic psammozems (Eutric Arenosols (Ochric)); the soils of post-pyrogenic successions after the ground fire can be classified as post-pyrogenic humic psammozems; after the crown fire, as humic psammozems.