Number Of Wildfires Research Articles

Hydrometeorology-wildfire relationship analysis based on a wildfire bivariate probabilistic framework in different ecoregions of the continental United States

Wildfires are a natural part of the ecosystem in the U.S.. It is vital to classify wildfires using a comprehensive approach that simultaneously considers wildfire activity (the number of wildfires) and burned area. On this basis, the influence of hydrometeorological variables on wildfires can be further analyzed. Therefore, this study first classified wildfire types using a wildfire bivariate probability framework. Then, by considering six hydrometeorological variables, the dominant hydrometeorological variables for different wildfire types in 17 ecoregions of the United States were quantified. In addition, based on the results of this hydrometeorology-wildfire relationship analysis, we obtained new clusters that simultaneously considered wildfire characteristics and the impact of hydrometeorology on wildfires. In particular, the results were as follows: (1) Through the probability of wildfire bivariate statistical characteristics, wildfires could be classified into five types in this paper: WT-1 (mega-wildfire), WT-2 (joint wildfire-1), WT-3 (joint extremes), WT-4 (joint wildfire-2), and WT-5 (super frequent wildfires); (2) The dominant hydrometeorological variables under different wildfire types were discussed in 17 ecoregions of the United States; and (3) In the four new cluster regions, intensifying droughts are a concern in clusters 1 and 4, while there are multiple concerns in cluster 3, namely, stronger winds, higher temperatures, and more drought.

Experimental substantiation of the risks of developing health disorders when exposed to smoke from wildfires

Introduction. An increase in the number of wildfires, along with the lack of a chemical control system for the quality of the atmosphere during smoke, leads to a risk of developing health disorders for rescuers and firefighters exposed to high concentrations of toxic smoke components.
 The study aims to identify causal relationships based on experimental modeling between exposure to natural fire smoke and the functional state of the nervous and reproductive systems.
 Materials and methods. The authors conducted studies on white rats of both sexes. The animals were placed in inhalation chambers and exposed to forest fire smoke of varying concentrations and duration of exposure. The scientists examined the functional state of the nervous system (open field method, Morris test, electroencephalography, histology of nervous tissue), the reproductive system (number of Leydig cells, average number of spermatogonia, spermatogenesis index), the presence of genotoxicity (DNA comet method), DNA methylation and the effect on offspring (postnatal development, species-specific behavior). We calculated the total exposure limit in each group of animals in accordance with the indicators of CO and PM2.5 content in the chambers.
 Results. The researchers found that with a total exposure load of 0.03–0.22 mg, there were initial changes in the morphofunctional state of the central nervous system. With an increase in the load to 4 mg, violations of the indicators of behavior and electrical activity of the brain were accompanied by significant changes in the structure of the nervous tissue of the rat brain. The reproductive function of rats under the influence of smoke changed, starting with a total exposure dose of 10.8 mg. We observed a decrease in spermatogenesis and a change in the cyclic function of the ovaries. A violation of the postnatal development of offspring has already been detected with a total dose of 0.22 to 4 mg. Prolonged exposure to tobacco smoke for one month was accompanied by a pronounced violation of the spermatogenetic function of the testicles and an increase in neonatal mortality in offspring, as well as a violation of the structure of behavior and spatial memory in adulthood. The genotoxic effect of smoke was not detected, and a change in DNA methylation in blood cells was detected at the maximum total dose of smoke components.
 Limitation. The study is limited to studying the effect of wildfire smoke on the nervous and reproductive systems of mongrel white male rats.
 Conclusion. The results obtained are a fundamental foundation for solving such tasks as the development of risk-oriented preventive health-saving measures for workers in extreme situations in conditions of smoke during wildfires and making effective management decisions.
 Ethics. The study was approved by the local Ethics Committee of the East-Siberian Institute of Medical and Ecological Research (Protocol LK of East-Siberian Institute of Medical and Ecological Research No. 32/19 dated 09/10/2019), conducted in accordance with the European Convention for the Protection of Vertebrates Used for Experiments or Other Scientific Purposes (ETS No. 123), Directive of the European Parliament and the Council of the European Union 2010/63/EC dated 09/22/2010 on the protection of animals used for scientific purposes.

A new method of nowcasting wildfires and impacts: a case study for the USA

<p>In recent years, there has been a steady increase in the intensity and frequency of wildfires worldwide mainly due to the escalating climate crisis and land-use change. Wildfires result in a decline in air quality and cause damage to property, crops, resources, wildlife, and human lives. Since models predict that the number of wildfires will rise by 50% by 2100 the reduction of the wildfire risk is more crucial than ever. We herewith attempt to develop a simple model for nowcasting such catastrophic events that may be useful for preparing authorities and policymakers. As an example, the case of the USA is presented by analyzing the count of wildfires and acres burned there over the past four decades to forecast such catastrophic events over the next ten years. The approach employed in this research can serve as an additional resource in the field of environment and fire ecology, aiding in identifying fire-adapted ecosystems and fire patterns.</p>

UNPRECEDENTED INCREASE IN THE CHARCOAL MACROPARTICLES IN THE BOTTOM SEDIMENTS OF THE LAKES OF THE NORTH-MINUSINSK VALLEY (SOUTH OF SIBERIA) IN THE RECENT TIME AS A POSSIBLE EVIDENCE OF ANTHROPOGENIC INFLUENCE

In the bottom sediments of lakes Shira and Uchum, located in the south of Siberia in the steppe zone of the North Minusinsk depression (Republic of Khakassia and Krasnoyarsk Territory), distributions of charcoal particles 100 µm. The age of the studied sediments of the two lakes was up to 1400 and 500 years ago, respectively. Charcoal particles of three types were found in the sediments of both lakes. The first group has an elongated shape and is interpreted as the remains of herbaceous plants and/or needles. The second group looks like thin flat blades and is interpreted as the remains of leaves. The third group consists of bulk particles of various irregular shapes, which are presumably the remains of the combustion of wood and coal. Particles of the first type are mainly indicators of natural fires, and their flux does not show a noticeable increase in the modern period. The flow of coal particles of the second and, to the greatest extent, the third groups has increased sharply in the last about a hundred years, which reflects an increase in the amount of wood and coal burned by people in the vicinity of the studied lakes in the modern industrial period. The data obtained reflect an increase in the amount of wood and coal burned by people in the modern industrial period, as well as a possible increase in the number of wildfires, which may also be due to human activities in the form of accidental or deliberate arson. Thus, for the first time for this region, an increase in the influx of charcoal particles into the bottom sediments of lakes over the past about a hundred years has been revealed, which is unprecedented over the period covered by our study. Thus, evidence of the anthropogenic impact on the dynamics of charcoal particles in bottom sediments has been obtained. The information obtained can be useful for reconstructing the dynamics of natural fires and paleo-climate in this region of southern Siberia in the Late Holocene.

Детонационные процессы во фронте горения растительных горючих материалов

Представлены результаты экспериментального исследования воздействия ударной волны на пламя при горении растительных горючих материалов. Ударная волна формировалась с помощью ударной трубы с различными насадками и источником энергии от порохового заряда. Для регистрации воздействия ударной волны на зону пиролиза применялись методы высокоскоростной ИК термографии в узкополосном диапазоне длины волны 2,5–2,7 мкм. Установлено, что при применении расширяющихся насадков в результате воздействия ударной волны на зону пиролиза происходит детонация продуктов пиролиза, которая приводит к прекращению пламенного горения. Much attention is currently being paid worldwide to improvement of existing and developing new effective ways to fight effectively natural fires, which occur annually in different countries and on a variety of landscapes. Given the annual increase in the number of wildfires and the often catastrophic consequences from them, it can be stated that the existing methods of firefighting are not effective enough. The methods used to extinguish large fires are usually based on the discharge of water by aircraft and the involvement of a large amount of manual labor of firefighters. This work is devoted to the study of the issue of extinguishing a natural fire by the impact of a shock wave on the burning zone. At present, the question of the interaction of the compaction shockwave with the flame during the combustion of plant combustible materials remains practically unstudied. Existing works in the field of shock waves impact on the fire front are limited to estimates of disruption of combustion conductors and formation of mineralized band. Modern research tools and methods allow to record and visualize the rapid processes, including in the flame. In particular, modern methods of infrared thermography make it possible to study both the temperature field in the flame and the structure of flow in it. Based on the original methods and approaches for application of high-speed infrared thermography developed at Tomsk State University, this work presents the results of an experimental study of the shock wave effect on the flame during combustion of plant flammable materials. A shock tube with different nozzles and an energy source from a gunpowder charge were used to form the shock wave. The impact of the shock wave on the pyrolysis zone was recorded in the narrow band infrared wavelength range of 2.5–2.7 μm. It has been established that the impact of the shock wave on the pyrolysis zone, when expanding nozzles are used, results in the detonation of pyrolysis products, which leads to the cessation of flame combustion and subsequent decrease in the surface temperature of plant combustibles below the autoignition temperature. This effect leads to a break in the chain of transformation and energy release during combustion. The obtained result should be considered as a fundamental basis for the development of new effective means of extinguishing large natural fires based on the impact of a shock wave.

Examining the potential of mobile applications to assist people to escape wildfires in real-time

Over the past couple of decades, the number of wildfires and area of land burned around the world has been steadily increasing, partly due to climatic changes and global warming. Therefore, there is a high probability that more people will be exposed to and endangered by forest fires. Hence there is an urgent need to design pervasive systems that effectively assist people and guide them to safety during wildfires. This paper examines the potential of mobile applications to be employed to assist people to escape wildfires in real-time, by means of using and evaluating EscapeWildFire, a system for suggesting evacuation paths to mobile phone users in real-time. Two different evaluation strategies are followed: (a) Considering different areas of the island of Cyprus as case studies with simulated wildfires and actual users and (b) Considering a historic wildfire that occurred in Amarillo, Texas in 2011. Results in both cases show that mobile apps can effectively be employed to assist people to escape wildfires, but their use is heavily dependent on a backend system that supports the precise modelling of the wildfire. The time between the wildfire outbreak and the notification reaching the user is crucial for their safety. Various recommendations for improvements have been recorded based on either the feedback of participants in the case studies or the observations from the Texas wildfire. The code of the mobile app, backend and administration interface used are all open-source; fire authorities around the world are encouraged to further investigate this opportunity and adopt this approach.

Landscape Planning Integrated Approaches to Support Post-Wildfire Restoration in Natural Protected Areas: The Vesuvius National Park Case Study

In recent decades in the Mediterranean basin there has been a considerable increase in both the number of wildfires and the extent of fire-damaged areas, resulting in ecological and socio-economic impacts. Protected areas are particularly vulnerable and many characteristics underpinning their legal protection are threatened. Several studies have been devoted to mitigating wildfire risks inside the protected areas, however often only in regard to natural heritage losses. Based on the adaptive wildfire resilience approaches, this work proposes a framework of actions that integrates natural, social and economic components. Starting from the Vesuvius National Park case study, affected by wildfires in 2017, the paper proposes a framework of action, envisaging two main phases: (i) the identification of priority intervention areas, by means of spatial multicriteria decision analysis, and (ii) damage assessment by using a monetary approach to value ecosystem services (ESs). The results identified priority areas where to concentrate economic and material resources, and estimated ecosystems damage, demonstrated ESs losses in areas adjacent to the burnt ones. This work, by integrating the relation between environmental sciences and policy, underpins a medium-long term development planning process. The aim of this work is to support landscape management and planning that includes socio-economic components such as sustainable development measures.

System-Level Performance Analysis of Cooperative Multiple Unmanned Aerial Vehicles for Wildfire Surveillance Using Agent-Based Modeling

In this paper, we propose an agent-based approach for the evaluation of Multiple Unmanned Autonomous Vehicle (MUAV) wildfire monitoring systems for remote and hard-to-reach areas. Emerging environmental factors are causing a higher number of wildfires and keeping these fires in check is becoming a global challenge. MUAV deployment for the monitoring and surveillance of potential fires has already been established. However, most of the scholarly work is still focused on MUAV operations details. In wildfire surveillance and monitoring, evaluations of the system-level performance in terms of the analysis of the effects of individual behavior on system surveillance has yet to be established. Especially in an MUAV system, the individual and cooperative behaviors of the team affect the overall performance of the system. Such systems are dynamic and stochastic because of an ever-changing environment. Quantifying the emergent system behavior and general performance measures of such a system by analytical methods is challenging. In our work, we present an agent-based model for MUAV surveillance missions. This paper focuses on the overall system performance of cooperative UAVs performing forest fire surveillance. The principal theme is to present the effects of three behaviors on overall performance: (1) the area allocation and (2) dynamic coverage, and (3) the effects of forest density on team allocation. For area allocation, three behaviors are simulated: (1) randomized, (2) two-layer barrier sweep coverage, and (3) full sweep coverage. For dynamic coverage, the effects of communication and resource unavailability during the mission are studied by analyzing the agent’s downtime spent on refueling. Last, an extensive simulation is carried out on wildfire models with varying forest density. It is found that cooperative complete sweep coverage strategies perform better than the rest and the performance of the team is greatly affected by the forest density.

Machine learning based wildfire susceptibility mapping using remotely sensed fire data and GIS: A case study of Adana and Mersin provinces, Turkey

In recent years, the number of wildfires has increased all over the world. Therefore, mapping wildfire susceptibility is crucial for prevention, early detection, and supporting wildfire management decisions. This study aims to generate Machine Learning (ML) based wildfire susceptibility maps for Adana and Mersin provinces, which are located in the Mediterranean Region of Turkey. To generate a wildfire inventory, this study uses active fire pixels derived from MODIS monthly MCD14ML composites. Furthermore, as a sub aim, the performance of seven ML approaches, namely, stand-alone Logistic Regression (LR), Support Vector Machine (SVM), Linear Discriminant Analysis (LDA), and ensemble algorithms, namely Random Forest (RF), Gradient Boosting (GB), eXtreme Gradient Boosting (XGB), and AdaBoost (AB), was evaluated based on wildfire susceptibility mapping. The capabilities of the corresponding ML methods were assessed using thirteen wildfire conditioning factors, which can be grouped into four main categories: topographical, meteorological, vegetation, and anthropogenic factors. The Information Gain (IG) approach was used to assess their importance scores. A multicollinearity analysis was also performed to assess the relationship between conditioning factors. To compare the predictive performances of ML algorithms, five performance metrics, namely average accuracy, precision, recall, F1 score, and area under the curve, were used. To test the significance of the generated wildfire susceptibility maps and to detect similarities and differences among the output of these ML algorithms, McNemar's test was implemented. In the end, the ML-based models were locally interpreted using the Shapley Additive exPlanations (SHAP) technique. The AUC values of seven methods varied from 0.817 to 0.879, and the accuracy scores ranged between 0.734 and 0.812. The results showed that the RF model provided the best results considering all performance metrics. The accuracy score and AUC values of the RF model were equal to 0.812 and 0.879, respectively. On the other hand, stand-alone algorithms (LDA, SVM, and LR) represented lower performance than tree-based ensemble methods. Both the IG and SHAP analyses showed that elevation, temperature, and slope factors were the most contributing factors. The RF model classifier found that 7.20% of the study area has very high wildfire susceptibility, and the majority of the wildfire samples (68.84%) correspond to the very high susceptible areas in the RF model. The outcomes of this study are likely to provide decision-makers with a better understanding of wildfires in the Eastern Mediterranean Region of Turkey.

Forecasting the regional fire radiative power for regularly ignited vegetation fires

Abstract. This paper presents a phenomenological framework for forecasting the area-integrated fire radiative power from wildfires. In the method, a region of interest is covered with a regular grid, whose cells are uniquely and independently parameterized with regard to the fire intensity according to (i) the fire incidence history, (ii) the retrospective meteorological information, and (iii) remotely sensed high-temporal-resolution fire radiative power taken together with (iv) consistent cloud mask data. The parameterization is realized by fitting the predetermined functions for diurnal and annual profiles of fire radiative power to the remote-sensing observations. After the parametrization, the input for the fire radiative power forecast is the meteorological data alone, i.e. the weather forecast. The method is tested retrospectively for south-central African savannah areas with the grid cell size of 1.5°×1.5°. The input data included ECMWF ERA5 meteorological reanalysis and SEVIRI/MSG (Spinning Enhanced Visible and Infra-Red Imager on board Meteosat Second Generation) fire radiative power and cloud mask data. It has been found that in the areas with a large number of wildfires regularly ignited on a daily basis during dry seasons from year to year, the temporal fire radiative power evolution is quite predictable, whereas the areas with irregular fire behaviour, predictability was low. The predictive power of the method is demonstrated by comparing the predicted fire radiative power patterns and fire radiative energy values against the corresponding remote-sensing observations. The current method showed good skills for the considered African regions and was useful in understanding the challenges in predicting the wildfires in a more general case.

Recent Developments in Some Long-Term Drought Drivers

The droughts that hit North and North Western Europe in 2018 and 2019 served as a wake-up call that temperate regions are also affected by these kinds of slow progressing or creeping disasters. Long-term drivers, such as land-use changes, may have exacerbated the impacts of these meteorological droughts. These changes, which are spread over a long time span, may even be difficult to perceive for an individual, but make a big difference in how these rare weather events impact a region. In this paper, we introduce three long-term drivers: forest fires in Europe, global urbanisation, and global deforestation. We attempt to provide a first assessment of their trends, mainly using statistics derived from satellite imagery published in recent literature. Due to the complexity of drought impacts, and the scarcity of quantitative impact data, the relationship between drought impact and these three processes for land use change is difficult to quantify; however, hence we present a survey of the recent trends in these land use change processes and the possible mechanics by which they affect drought impacts. Based on this survey we can conclude that the extent and the number of wildfires have increased markedly in Europe since 2010. Deforestation is still occurring in the tropics, with a loss of 12% in the last 30 years but has halted in the northern regions. Urbanisation has more than doubled in the same time span in the tropics and subtropics, mostly at the expense of forests, while in Europe urbanisation took place mainly in the northern part of the continent. We can conclude that none of these implicit drought drivers followed a favourable trend in the last 30 years. With consistent and worldwide monitoring, for example, by using satellite imagery, we can regularly inform the scientific community on the trends in these drought impact affecting processes, thus helping decision makers to understand how far we have progressed in making the world resilient to drought impacts.

A relationship between weather conditions and a number of forest fires

This work presents an approach to identifying the relationship between weather conditions in the region and a number of wild fires. On the basis on the official data, an assessment of meteorological conditions (average monthly air temperature, average monthly relative humidity, total precipitation, average wind speed) was carried out, and the hydrothermal coefficient was calculated for various areas of the Right-Bank and Left-Bank parts of the Saratov region. The obtained values are compared with the number of fires occurring in the selected territories: the study areas and parts of the Saratov region. It is shown that the best values of the correlation coefficients are observed when comparing data on the average relative air humidity and the number of fires. In some cases, a correlation is observed between the amount of precipitation and the average air temperature. Weather conditions are a combination of air temperature and relative humidity. Both of these parameters can be taken into account by calculating the hydrothermal coefficient, and its comparison with the number of fires may give a more accurate picture. Nevertheless, the calculation of the hydrothermal coefficient and the joint analysis of its values with the number of fires showed low values of the correlation coefficients. Nevertheless, if we combine the change in the values of the hydrothermal coefficient on the graph with the change in the number of forest fires, then it becomes clearly visible that there is a temporary shift in the period of occurrence of forest fires relative to the period of low level of moisture in the territory.

Complex Analysis of Wildfires in Hungary in the Last Decade

Wildfires are one of the most common natural disasters in the world, which cause millions of hectares of damage each year. This fact poses a major challenge to the defence sector. Environmental safety problems caused by wildfires affect not only the ecosystem but also all aspects of society. Research on the effects of climate change predicts a more uneven rainfall distribution and rising daily average temperatures in summer and autumn in the Carpathian Basin. The effects of climate change will be indirectly detectable, such as the extension of fire risk periods, the increase in the number of wildfires and their spatial and temporal distribution, and the increase in fire intensity. Changes due to climate change will pose an even greater challenge in the future to the Hungarian authorities, which are responsible for preventing and extinguishing wildfires. One of the purposes of the paper is to define indicators that can be used to compare the number and extent of wildfires each year with the degree of the daily fire risk and the length of periods during which the wildfires occurred. For this, it is necessary to define the concept of the high fire risk days and the endangered areas and parts of the country in the Hungarian climatic conditions. Based on previous statistical studies, the authors will examine the spring and summer fire seasons separately because of the different fuel conditions and the causes of fire ignition. They examine statistical data on wildfires and apply GIS application. Another aim of the research is to find a correlation between the daily fire risk values, the number of wildfires and the burned area. A fire risk-based investigation of the wildfires that have occurred in the last decade can later help in official preparation, annual planning and preparation of forces involved in the prevention and firefighting.

Relationship between Wildfire Smoke and Children’s Respiratory Health in the Metropolitan Cities of Central-Chile

Wildfire causes multiple problems for people living in cities. One of them is the deterioration of air quality as a result of wildfire smoke. This smoke can consequently have effects on human health. The present study aims to characterize the relationship between the occurrence of wildfires in central Chile and the effects on children’s respiratory health. Public databases provided the number of emergency care visits, wildfires, and concentration of air pollutants, demographics and meteorological variables for the regions of Santiago and Valparaiso from 2010 to 2013. Time series analysis was used monthly on health care visits to determine the relative health risk in children when in the presence of additional wildfires. Significant health risks were observed in Santiago for children younger than 1-year-old of bronchitis (RR 1.007, CI 95% 1.007–1.008; chronic lower respiratory diseases (RR 1.012, CI 95% 1.012–1.013); and pneumonia (RR 1.026 CI 95% 1.026–1.027) and in children aged one to four years old (RR 1.016 CI 95% 1.015–1.016). A dose-response relationship was also observed for pneumonia, showing that it affects younger children particularly when there is an increase in the number of wildfires. In the Region of Valparaíso, wildfires did not significantly change the risk of respiratory illness, this could be due to favorable ventilation. Currently, Santiago has an urgent need for monitoring and the evaluation of the damage to children’s respiratory health, along with the development of comprehensive prevention strategies.

Machine Learning Methods and Synthetic Data Generation to Predict Large Wildfires.

Wildfires are becoming more frequent in different parts of the globe, and the ability to predict when and where they will occur is a complex process. Identifying wildfire events with high probability of becoming a large wildfire is an important task for supporting initial attack planning. Different methods, including those that are physics-based, statistical, and based on machine learning (ML) are used in wildfire analysis. Among the whole, those based on machine learning are relatively novel. In addition, because the number of wildfires is much greater than the number of large wildfires, the dataset to be used in a ML model is imbalanced, resulting in overfitting or underfitting the results. In this manuscript, we propose to generate synthetic data from variables of interest together with ML models for the prediction of large wildfires. Specifically, five synthetic data generation methods have been evaluated, and their results are analyzed with four ML methods. The results yield an improvement in the prediction power when synthetic data are used, offering a new method to be taken into account in Decision Support Systems (DSS) when managing wildfires.

Оценка сил и средств для тушения пожаров в населённых пунктах и методов их обоснования

Introduction. Climate change leads to an increase the number of wildfires and fires in settlements, with 74 % of the country's population living in urban settlements and 26 % in rural settlements. The readiness of localities for the fire season is determined by regulatory documents that do not assess the sufficiency of measures taken by local governments to prepare territories for the fire season, and, accordingly, do not provide protection of localities from the fires. At the same time, there is no scientific and methodological approach for determining the necessary and sufficient number of fire-fighting constructions and assessing the stability of their structure to protect settlements from the effects of mass or large-scale fires. The purpose of the study. The purpose of the study is to ensure the protection of settlements from the impact of mass or large-scale fires. Research methods. To obtain the results, general scientific and special methods of scientific knowledge were used: analysis, synthesis, generalization. They were based on the provisions of the theory of systems, theory of information. The results of the study. The forces and means that can be used to extinguish fires in localities are evaluated, and the main methods used to justify the elements of the fire-fighting water supply system in localities are considered and summarized. Conclusion. There is a contradiction between the need to ensure the protection of settlements from the impact of mass or large-scale fires and the lack of scientific and methodological approach of justification of corresponding set of means and their management. The results of the study are the basis for the development of a scientific and methodological approach to assessing and justifying the forces and means to ensure the protection of settlements from the impact of mass or large-scale fires and the safety of their activities. Keywords: locality, mass or large-scale fire, fire-fighting water supply, methods of justification

Exploratory Analysis of Driving Force of Wildfires in Australia: An Application of Machine Learning within Google Earth Engine

Recent studies have suggested that due to climate change, the number of wildfires across the globe have been increasing and continue to grow even more. The recent massive wildfires, which hit Australia during the 2019–2020 summer season, raised questions to what extent the risk of wildfires can be linked to various climate, environmental, topographical, and social factors and how to predict fire occurrences to take preventive measures. Hence, the main objective of this study was to develop an automatized and cloud-based workflow for generating a training dataset of fire events at a continental level using freely available remote sensing data with a reasonable computational expense for injecting into machine learning models. As a result, a data-driven model was set up in Google Earth Engine platform, which is publicly accessible and open for further adjustments. The training dataset was applied to different machine learning algorithms, i.e., Random Forest, Naïve Bayes, and Classification and Regression Tree. The findings show that Random Forest outperformed other algorithms and hence it was used further to explore the driving factors using variable importance analysis. The study indicates the probability of fire occurrences across Australia as well as identifies the potential driving factors of Australian wildfires for the 2019–2020 summer season. The methodical approach and achieved results and drawn conclusions can be of great importance to policymakers, environmentalists, and climate change researchers, among others.

Resilience to Large, “Catastrophic” Wildfires in North America's Grassland Biome

AbstractWildfires are ecosystem‐level drivers of structure and function in many vegetated biomes. While numerous studies have emphasized the benefits of fire to ecosystems, large wildfires have also been associated with the loss of ecosystem services and shifts in vegetation abundance. The size and number of wildfires are increasing across a number of regions, and yet the outcomes of large wildfire on vegetation at large‐scales are still largely unknown. We introduce an exhaustive analysis of wildfire‐scale vegetation response to large wildfires across North America's grassland biome. We use 18 years of a newly released vegetation data set combined with 1,390 geospatial wildfire perimeters and drought data to detect large‐scale vegetation response among multiple vegetation functional groups. We found no evidence of persistent declines in vegetation driven by wildfire at the biome level. All vegetation functional groups exhibited relatively rapid recovery to pre wildfire ranges of variation across the Great Plains ecoregions, with the exception being a persistent decrease in the abundance of trees in the Northwestern Great Plains. Drought intensity magnified immediate vegetation response to wildfire. Persistent declines in vegetation cover were observed at the scale of single pixels (30 m), suggesting that these responses were localized and represent extreme cases within larger wildfires. Our findings echo over a century of research demonstrating a biome resilient to wildfire.

Satellite-Observed Soil Moisture as an Indicator of Wildfire Risk

Wildfires are a concerning issue in Canada due to their immediate impact on people’s lives, local economy, climate, and environment. Studies have shown that the number of wildfires and affected areas in Canada has increased during recent decades and is a result of a warming and drying climate. Therefore, identifying potential wildfire risk areas is increasingly an important aspect of wildfire management. The purpose of this study is to investigate if remotely sensed soil moisture products from the Soil Moisture and Ocean Salinity (SMOS) satellite can be used to identify potential wildfire risk areas for better wildfire management. We used the National Fire Database (NFDB) fire points and polygons to group the wildfires according to ecozone classifications, as well as to analyze the SMOS soil moisture data over the wildfire areas, between 2010–2017, across fourteen ecozones in Canada. Timeseries of 3-day, 5-day, and 7-day soil moisture anomalies prior to the onset of each wildfire occurrence were examined over the ecozones individually. Overall, the results suggest, despite the coarse-resolution, SMOS soil moisture products are potentially useful in identifying soil moisture anomalies where wildfire hot-spots may occur.

Effects of Climatic Warming and Wildfires on Recent Vegetation Changes in the Lake Baikal Basin

The vegetation changes in the area of the Russian part of the Lake Baikal water basin for the period 2010–2018 were investigated using MCD12C1 land cover. The decline in swamp systems area began in 2012 and continued until 2015, after which it partially recovered during the heavy rain season in 2018. During the period of 2010–2018, the area covered by forests did not exceed 20.3% of the Baikal basin of the total portion of the Baikal basin under study. Deforestation began in 2013 and continued until 2017. Over 2013–2018, the forest level decreased by 12.1% compared to the forest state in 2013. The analysis of summer rainfalls and aridity indexes was performed by using CRU TS and GPCC climatic datasets. It is shown that the interannual variations of precipitation and aridity changes are determined by the variability of the global circulation of moist air masses. The MCD64A1 (burned area) and MCD14ML (active fires) MODIS products were used for investigation of the influence of wildfires on vegetation changes. The spatial hotspot distributions and burned areas in general correspond to aridity zones, but they cannot explain the 20-fold increase in the number of wildfires. Most of the hotspot locations are away from settlements, roads, and loggings, in difficult-to-access mountainous areas, as well as in the low-inhabited areas of Siberia. We assume that the nature of such ignitions includes dry thunderstorms, pyrocumulus lightning, or remote impact.