Forest Fire Activity Research Articles

A Strategy for involving community forest managers in effective forest fire management in Nepal

Each year forest fire causes enormous damage to Nepal's forest ecosystems and landscape. For an active community involvement at the landscape level, policymakers must take the interests of local forest managers into account to increase social acceptability. This research explores the perception of community forest managers, who are constantly managing forests at the grassroots level, to understand the relationship between their priorities, needs, and attitudes toward forest fire management. Eighty–eight key informants from six districts were interviewed using a structured questionnaire. The questionnaire was divided into three major sections, (i) forest fuel management and infrastructure, (ii) forest fire management strategies and actions, and (iii) public education and awareness on forest fire management. The data were analyzed using the Kruskal–Wallis test, where the respondents rated above 4.2 out of 5 for activities like increase of insurance mechanisms, providing training for firefighting volunteer groups, and provisioning firefighting equipment. The majority of the respondents agreed on the activities under the forest fire management strategies and actions section (Kendall's Tau = 0.8501), followed by forest fuel management and infrastructure (Kendall’s Tau= 0.6757). We anticipate that the results of this study will be helpful for the local decision–makers in involving different communities and identifying their priorities while implementing various forest fire management activities in diverse landscapes or provinces of the country.

Spatial distribution of aerosol optical depth over India during COVID-19 lockdown phase-1

The present study analysed the spatial distribution of Aerosol Optical Depth (AOD) over India during the COVID-19 lockdown phase -1 (March 25 to April 15, 2020) using MODIS Terra (MOD04) AOD data (550 nm) during 2001–2020. Air temperature, rainfall, forest fire incidents, and wind patterns were analysed to understand their effect on the distribution of aerosols over India during the lockdown phase-1. Moderate absorption fine aerosol type is predominant but sparsely distributed over India during the study period compared to the reference period indicating the positive influence of the lockdown. Mean AOD has reduced by 9% over India during the lockdown phase-1 compared to the corresponding mean of the past 19 years (2001–2019). About 70% of the states/UTs of India showed a reduction in mean AOD due to restrictions on non-essential economic activities and rainfall occurrence. However, some states showed an increase in aerosol loading over specific pockets despite the restrictions on economic activities (Arunachal Pradesh, Assam, Gujarat, Orissa, Andhra Pradesh, Madhya Pradesh, Chhattisgarh, Maharashtra, Assam, Nagaland, Manipur and Karnataka) because of active forest fire cases. This study would be helpful for planners and policymakers to adopt suitable measures to control the rising concentrations of aerosols over hotspot regions of India.

Fire-Net: A Deep Learning Framework for Active Forest Fire Detection

Forest conservation is crucial for the maintenance of a healthy and thriving ecosystem. The field of remote sensing (RS) has been integral with the wide adoption of computer vision and sensor technologies for forest land observation. One critical area of interest is the detection of active forest fires. A forest fire, which occurs naturally or manually induced, can quickly sweep through vast amounts of land, leaving behind unfathomable damage and loss of lives. Automatic detection of active forest fires (and burning biomass) is hence an important area to pursue to avoid unwanted catastrophes. Early fire detection can also be useful for decision makers to plan mitigation strategies as well as extinguishing efforts. In this paper, we present a deep learning framework called Fire-Net, that is trained on Landsat-8 imagery for the detection of active fires and burning biomass. Specifically, we fuse the optical (Red, Green, and Blue) and thermal modalities from the images for a more effective representation. In addition, our network leverages the residual convolution and separable convolution blocks, enabling deeper features from coarse datasets to be extracted. Experimental results show an overall accuracy of 97.35%, while also being able to robustly detect small active fires. The imagery for this study is taken from Australian and North American forests regions, the Amazon rainforest, Central Africa and Chernobyl (Ukraine), where forest fires are actively reported.

The sensitivity of fuel moisture to forest structure effects on microclimate

An understanding of variation in dead fuel moisture content (FMC) is essential for accurate predictions of wildfire risk, particularly in productive wet forests where FMC is a primary control on fire activity. In these systems, forest structure and composition influence microclimate, which in turn effects FMC. However, changing disturbance regimes are altering forest structure and our understanding of the sensitivity of FMC to these variations is incomplete. To explore this, we quantified the relative importance of changes in microclimate resulting from altered forest structure to FMC variability. This was done by modelling FMC using microclimate scenarios extracted from observations at six field sites with contrasting structural profiles. The scenarios related to maximum, mean, and minimum fire-related microclimate conditions. To understand sensitivity in a fire management context, we summarised results using FMC thresholds of fuel availability (FA) across three seasons – corresponding to wildfire and prescribed burning conditions. Distinct differences in FA demonstrate the potential for altered structure to influence fire activity in wet forests. Structure effects on vapour pressure deficit (VPD) and longwave radiation (LWR) exerted the strongest control on FA, resulting in increases of 125% and 87% across all seasons respectively, while shortwave radiation (SWR) had a limited influence. However, FMC sensitivity to microclimate inputs changed with season. Critically, in summer, forest structure effects generating elevated VPD conditions resulted in 8 additional days (of 30) when FMC was less than 10%, a threshold for intense fire behaviour. Our research supports the hypothesis that FMC is sensitive to forest structure change, and that this sensitivity can be mechanistically linked to elevated VPD and LWR in the microclimate resulting from these changes. Given the potential for disturbances to alter forest structure in the future, the potential impact of this on microclimate and FMC should be considered in landscape predictions of wildfire risk.

Scandinavian Forest Fire Activity Correlates with Proxies of the Baffin Bay Ice Cover

Understanding factors driving fire activity helps reveal the degree and geographical variability in the resilience of boreal vegetation to large scale climate forces. We studied the association between sea ice cover in the Baffin Bay and the Labrador Sea and observational records of forest fires in two Nordic countries (Norway and Sweden) over 1913–2017. We found a positive correlation between ice proxies and regional fire activity records suggesting that the Arctic climate and the associated changes in North Atlantic circulation exercise an important control on the levels of fire activity in Scandinavia. Changes in the sea cover are likely correlated with the dynamic of the North Atlantic Current. These dynamics may favor the development of the drought conditions in Scandinavia through promoting persistent high-pressure systems over the Scandinavian boreal zone during the spring and summer. These periods are, in turn, associated with an increased water deficit in forest fuels, leading to a regionally increased fire hazard. The Arctic climate will likely be an important future control of the boreal fire activity in the Nordic region.

A Foresight inRimbawanPerformance Level: Toward A More Controllable Forest Fires Area

Rimbawan(foresters) is one of the human resources owned by the Ministry of Environment and Forestry. They need to enhance their performance in decreasing forest fire areas. It will affect future public health, economic development, ecological balance, social stability, and land aesthetics. Accordingly, scenario planning helps in contemplating how the future may develop and is especially important when needing to make sense of uncertainty in the forest sustainability management sector. Scenario planning can be narrative-based and represented quantitatively to ensureRimbawan’sperformance level. On the other hand, promoting a more controllable forest fire area has not been fully anticipated. Therefore, this study aims to help environmental policymakers by offering a discovery of basic data for forest fire precautions, forest firefighting, and post-forest fire handling. This study has conducted a descriptively quantitative method. The results suggest that the average forest fire area in South Sumatra Province based on their KPH from 2015-to 2019 is 30.71 percent of those 2,265,457.34 hectares of KPH. Whereas the 1 level of an increase in forest fire prevention activities will reduce the probability of forest fire insight into the upscaledRimbawan’sperformance level through conversation quality and engagement, learning, decision-making style, mental models, and leadership support.

Faktor Penyebab dan Upaya Pengendalian Kebakaran Hutan di KPH Majalengka

KPH Majalengka is one of the State-Owned Enterprises engaged in forest management business. KPH Majalengka also experienced disruptions arising from forest fires. BKPH Cibenda is an area with the highest fire incidence in KPH Majalengka with an area of 762.93 ha of the total area of forest fires covering 865.48 ha over the last five years (2013-2017). The purpose of this study was to analyze and describe the common cause of forest fires and control efforts in KPH Majalengka. The common cause of forest fires that often occur in BKPH Cibenda according to community perceptions are land clearing, burning deliberately, and grazing. Forms of forest fire prevention activities that have been conducted is socialization, training of forest fire control, warning signs, and firebreaks. Extinguishing activity that have been caried out by community is direct extinguishing and indirect outage, however the facilities of fire extinguishing do not fullfill the minimum aspect. Post-fire handling is often done by collecting damage and loss data, fire reporting, measurement of fire area and location sketching, analysis of damage level and writing event report in Letter A (LA).
 Keywords: BKPH Cibenda, forest fire, KPH Majalengka, land clearing, post fire

Investigation of Forest Fire Activity Changes Over the Central India Domain Using Satellite Observations During 2001-2020.

Recurrent and large forest fires negatively impact ecosystem, air quality, and human health. Moderate Resolution Imaging Spectroradiometer fire product is used to identify forest fires over central India domain, an extremely fire prone region. The study finds that from 2001 to 2020, ∼70% of yearly forest fires over the region occurred during March (1,857.5 counts/month) and April (922.8 counts/month). Some years such as 2009, 2012, and 2017 show anomalously high forest fires. The role of persistent warmer temperatures and multiple climate extremes in increasing forest fire activity over central India is comprehensively investigated. Warmer period from 2006 to 2020 showed doubling and tripling of forest fire activity during forest fire (February–June; FMAMJ) and non‐fire (July–January; JASONDJ) seasons, respectively. From 2015 JASONDJ to 2018 FMAMJ, central India experienced a severe heatwave, a rare drought and an extremely strong El Niño, the combined effect of which is linked to increased forest fires. Further, the study assesses quinquennial spatiotemporal changes in forest fire characteristics such as fire count density and average fire intensity. Deciduous forests of Jagdalpur‐Gadchiroli Range and Indravati National Park in Chhattisgarh state are particularly fire prone (>61 fire counts/grid) during FMAMJ and many forest fires are of high intensity (>45 MW). Statistical associations link high near surface air temperature and low precipitation during FMAMJ to significantly high soil temperature, low soil moisture content, low evapotranspiration and low normalized difference vegetation index. This creates a significantly drier environment, conducive for high forest fire activity in the region.

352 years long fire history of a Siberian boreal forest and its primary driving factor

Fire is a major disturbance agent in the boreal forest, affecting the structure, dynamics and biogeochemical cycles in this biome. In the Asian section of boreal forest, the records of long-term fire history are few that limits our understanding of factors forcing regional fire dynamics. We presented an annually-resolved 352-year (1666–2017) fire chronology based on fire scars of Scots pine ( Pinus sylvestris L.) and Siberian larch ( Larix sibirica Ledeb) from the Transbaikal area in the southeastern Siberia. Fire activity showed an increasing trend from 1720 to 1929 (R 2 = 0.80, P < 0.0001), and a significant decreasing trend from 1920 to 2010 (R 2 = 0.62, P < 0.001). We assessed the potential relationships between drought (as represented by the Palmer Drought Severity Index, PDSI, and the Monthly Drought Code, MDC), ocean-atmosphere circulation and forest fire by Superposed epoch analyses, cross-wavelet analysis and Granger causality analysis. Increased fire activity was associated with stronger drought from previous winter to current summer of fire event years and positive Arctic Oscillation (AO) before and during major fire season (February and April to May), as revealed by superposed epoch analysis. Granger causality pointed to the significant role of drought in driving forest fires. Our findings provide insights into the climate drivers of forest fire activity and its prediction in the Transbaikal region. • Fire history was reconstructed by fire scars in tree rings from 1666 to 2017 in southeastern Siberia. • Fire activity showed a significant increasing trend from 1720 to 1929 and a significant decreasing trend from 1920 to 2009. • Drought was the major climate driver of the fire. • Increased fire activity was associated with the positive Arctic Oscillation (AO) before and during the major fire season (February, April and May).

Lung Function Impairment Among Firefighter After Forest Fire Disaster in Riau, Sumatra

Background: The 2015 forest fire disaster affected almost 2.6 million hectares of land in Indonesia, and Riau was among the worst. Firefighters were the first responders to deal with the disaster, but a little was known about the influence of extinguishing forest fire activities with their health. This study aimed to evaluate respiratory symptoms and lung function among firefighters 6 months after forest fire exposure.Methods: Interviews were conducted regarding sociodemographic factors, respiratory symptoms, and history of forest fire exposure during the disaster. Spirometry and chest X-ray were also carried out with standard techniques. Statistical analysis was performed based on the existing data. Ninety firefighters participated in this study, most were male with mean age of 33 years old. About 66% were smoker, had been working as firefighters for 2 to 10 years, and had been on extinguishing forest fire duty around 2–5 hours/day during the disaster.Results: All firefighters reported respiratory symptoms after 3 months. Pulmonary function was abnormal in 50% of subjects with mild restrictive characteristic. The analysis showed that body mass index (BMI) and duration of exposure had a significant correlation with pulmonary function abnormality.Conclusion: Pulmonary function was found abnormal in most subjects 6 months after forest fire exposure in Riau.

Effects of Climate Change on Natural-Caused Fire Activity in Western U.S. National Forests

Climate change, with warming temperatures and shifting precipitation patterns, may increase natural-caused forest fire activity. Increasing natural-caused fires throughout western United States national forests could place people, property, and infrastructure at risk in the future. We used the fine K nearest neighbor (KNN) method coupled with the downscaled Multivariate Adaptive Constructed Analogs (MACA) climate dataset to estimate changes in the rate of natural-caused fires in western United States national forests. We projected changes in the rate of minor and major forest fires from historical (1986–2015) to future (2070–2099) conditions to characterize fire-prone national forests under a range of climate change scenarios. The results indicate that climate change can add to the occurrence of forest fires in western United States national forests, particularly in Rocky Mountain, Pacific Southwest, and Southwestern United States Forest Service regions. Although summer months are projected to have the highest rate of natural-caused forest fire activity in the future, the rate of natural-caused forest fires is likely to increase from August to December in the future compared to the historical conditions. Improved understanding of altered forest fire regimes can help forest managers to better understand the potential effects of climate change on future fire activity and implement actions to attenuate possible negative consequences.

Effects of Spatial Resolution on Burned Forest Classification With ICESat-2 Photon Counting Data

Accurately monitoring forest fire activities is critical to understanding carbon dynamics and climate change. Three-dimensional (3D) canopy structure changes caused by fire make it possible to adopt Light Detection and Ranging (LiDAR) in burned forest classification. This study focuses on the effects of spatial resolution when using LiDAR data to differentiate burned and unburned forests. The National Aeronautics and Space Administration’s (NASA) Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) mission provides LiDAR datasets such as the geolocated photon data (ATL03) and the land vegetation height product (ATL08), which were used in this study. The ATL03 data were filtered by two algorithms: the ATL08 algorithm (ILV) and the adaptive ground and canopy height retrieval algorithm (AGCH), producing classified canopy points and ground points. Six typical spatial resolutions: 10, 30, 60, 100, 200, and 250 m were employed to divide the classified photon points into separate segments along the track. Twenty-six canopy related metrics were derived from each segment. Sentinel-2 images were used to provide reference land cover maps. The Random Forest classification method was employed to classify burned and unburned segments in the temperate forest in California and the boreal forest in Alberta, respectively. Both weak beams and strong beams of ICESat-2 data were included in comparisons. Experiment results show that spatial resolution can significantly influence the canopy structures we detected. Classification accuracies increase along with coarser spatial resolutions and saturate at 100 m segment length, with overall accuracies being 79.43 and 92.13% in the temperate forest and the boreal forest, respectively. Classification accuracies based on strong beams are higher than those of using weak beams due to a larger point density in strong beams. The two filtering algorithms present comparable accuracies in burned forest classification. This study demonstrates that spatial resolution is a critical factor to consider when using spaceborne LiDAR for canopy structure characterization and classification, opening an avenue for improved measurement of forest structures and evaluation of terrestrial vegetation responses to climate change.

Scarce fire activity in north and north-western Amazonian forests during the last 10,000 years

ABSTRACT Background Fire is known to affect forest biodiversity, carbon storage, and public health today; however, comparable fire histories from across forest regions in Amazonia are lacking. Consequently, the degree to which past fires could have preconditioned modern forest resilience to fire remains unknown. Aim We characterised the long-term (multi-millennial) fire history of forests in Amazonia to determine spatial and temporal differences in fire regimes. Methods We collated and standardised all available charcoal data extracted from continuously deposited lake sediments (n = 31) to reconstruct a ca. 10,000-year fire history for: (i) north and north-western, (ii) south-western, and (iii) eastern parts of Amazonia. Results Charcoal was found across Amazonia, but it was less abundant in the north and north-western regions. Regionally distinct periods of elevated charcoal deposition were identified at between ca. 4000 and 1500 (eastern), 3000–1000 (south-western) and 2500–2000 (north and north-western) years ago. Conclusions Forests in eastern and south-western Amazonia have been exposed to fire activity over recent millennia, while the forests in north and north-western Amazonia have grown under conditions largely free of fire activity. Consequently, we hypothesise that the forests in eastern and south-western Amazonia are preconditioned to be relatively more resilient to the threat of increased modern fire activity.

Detecting vulnerability of humid tropical forests to multiple stressors

Detecting vulnerability of humid tropical forests to multiple stressors

ESTIMATING FINE DEAD FUEL MOISTURE CONTENT UNDER EQUATORIAL CLIMATE CONDITIONS

The measurement of the fine dead fuel moisture content (FDFMC) is extremely important for forest fire prevention and suppression activities, as it has a great influence on the ignition probability and fire behavior. The Fine Fuel Moisture Code (FFMC) from the Fire Weather Index (FWI), is one of the most used models to estimate the FDFMC. Nevertheless, studies that assess the efficiency of this model in Brazil or in low latitude regions are rare. The present study aimed to evaluate the efficiency of the FFMC in an equatorial climate area and to develop a new model capable of estimating the FDFMC with greater precision. For this purpose, 861 random samples of fine dead fuel had their moisture content determined through oven drying. The obtained values were compared with those estimated by the FFMC and correlated with meteorological parameters to build a regression model. The results obtained show that the FDFMC was overestimated by the FFMC. The independent variables with the greatest influence on the FDFMC were, in decreasing order of significance: air relative humidity, air temperature, amount of rainfall in the last 24 hours and number of days without rainfall. The developed model presented good statistical parameters (r2 = 0.86; p &lt;0.0001; RMSE = 0.22) and can be used, in areas with similar characteristics of the study area, to estimate the daily fire risk and to determine ideal conditions for prescribed burns.

Rocky Mountain subalpine forests now burning more than any time in recent millennia

The 2020 fire season punctuated a decades-long trend of increased fire activity across the western United States, nearly doubling the total area burned in the central Rocky Mountains since 1984. Understanding the causes and implications of such extreme fire seasons, particularly in subalpine forests that have historically burned infrequently, requires a long-term perspective not afforded by observational records. We place 21st century fire activity in subalpine forests in the context of climate and fire history spanning the past 2,000 y using a unique network of 20 paleofire records. Largely because of extensive burning in 2020, the 21st century fire rotation period is now 117 y, reflecting nearly double the average rate of burning over the past 2,000 y. More strikingly, contemporary rates of burning are now 22% higher than the maximum rate reconstructed over the past two millennia, during the early Medieval Climate Anomaly (MCA) (770 to 870 Common Era), when Northern Hemisphere temperatures were ∼0.3 °C above the 20th century average. The 2020 fire season thus exemplifies how extreme events are demarcating newly emerging fire regimes as climate warms. With 21st century temperatures now surpassing those during the MCA, fire activity in Rocky Mountain subalpine forests is exceeding the range of variability that shaped these ecosystems for millennia.

Trends and patterns in annually burned forest areas and fire weather across the European boreal zone in the 20th and early 21st centuries

Fire remains one of the main natural disturbance factors in the European boreal zone and understanding climatic forcing on fire activity is important for projecting effects of climate change on ecosystem services in this region. We analyzed records of annually burned areas in 16 administrative regions of the European boreal zone (countries or administrative units within countries) and fire weather variability to test for their spatio-temporal patterns over the 1901-2017 period.Over the 1992-2017 period, the region exhibited large variability in forest fire activity with the fire cycles varying from ~1600 (St. Petersburg region) to ~37000 years (Finland). The clustering of administrative units in respect to their burned area, suggested the presence of sub-regions with synchronous annual variability in burned areas. Large fire years (LFYs) in each of the clusters were associated with the development of the high pressure cell over or in immediate proximity of the regions in question in July, indicating climatic forcing of LFYs. Contingency analysis indicated that there was no long-term trend in the synchrony of LFYs observed simultaneously in several administrative units. We documented a trend towards higher values of Monthly Drought Code (MDC) for the months of April and May in the western (April) and northern (April and May) sections. The significant positive correlation between biome-wide fire activity index and June SNAO (Summer North Atlantic Oscillation) (r = 0.53) pointed to the importance of large-scale atmospheric circulation, in particular the summer European blocking pattern, in controlling forest fires across EBZ. The forest fire activity of the European boreal zone remains strongly connected to the annual climate variability. Higher frequency of strongly positive SNAO states in the future will likely synchronize years with a large area burned across the European boreal zone.

Germination responses of two key mountain tree species to single and combined fire-related stresses: does elevational origin matter?

Since climate change is expected to increase fire activity and drought stress in forests across the globe, studying seed resistance to heat stress and drought is imperative to predict future mountain forest regeneration scenarios. Here, stress co-occurrence and among population variation in stress resistance are key elements to consider. We hypothesized that i) increasing heat/osmotic stress intensity decreases germination performance; ii) seeds from higher elevations (i.e. cooler and wetter climatic conditions) exhibit lower resistance to heat/osmotic stress showing a stronger decline in germination performance as compared to seeds from lower elevations (i.e. warmer and drier climatic conditions); and that iii) elevational differences in seed stress resistance vary depending on whether stresses are applied alone or in combination. We exposed seeds from Polylepis australis and Escallonia cordobensis from low (1200 – 1400 m), mid (1650 – 1800 m) and high (2000 – 2200 m) elevational origins to different heat (control, 75, 105 °C) and osmotic (0, -0.3, -0.6 MPa polyethylene glycol) stress intensities. Germination performance decreased with increasing heat/osmotic stress intensity and clear differences among elevational origins were observed. In both species low-mid elevation seeds showed lowest performances but exhibited slightly higher stress resistance than high elevation seeds; yet the nature of these responses was species-specific. Our results demonstrate that germination response to a combination of heat stress and drought is different from the response to each of these stresses applied individually. Therefore, understanding how interactions of climate change with fire events can influence germination timing and success in mountain trees requires considering the effect of multiple stressors on seed physiology. Our findings also highlight the potential population-specific and species-specific responses, which could be used as guidance for ongoing restoration plans.

Environmental changes during MIS6-3 in the Basin of Mexico: A record of fire, lake productivity history and vegetation

The responses of lake productivity, vegetation, and fire events in the Basin of Mexico to orbital changes from late MIS 6 to MIS 3 (146–35 ka) have been studied based on geochemical (Ti, TIC, TOC, C/N), charcoal (CHAR) and pollen data of the sediment core CHA08 from Lake Chalco. The paleoenvironmental reconstruction identifies the MIS 6 as a wetter period with episodes of dry conditions, low forest cover and low fire activity. A sudden change from wetter to dry environments with low to high forest cover and fire activity episodes characterized the end of the MIS 6 (132–130 ka) coincident with high spring insolation. Variations in vegetation composition, with a tendency towards higher forest cover, fire-activity, runoff, and organic matter availability, are recorded during the MIS 5, MIS 4, and MIS 3. However, a reduction in the fire-activity was recorded for the cold and dry MIS 4. Spectral analysis based on the titanium concentration record of Lake Chalco suggests a precessional forcing on runoff variations. We explored the impact of the Intertropical Convergence Zone latitudinal migrations which have been related to the summer insolation at 65° N by comparing runoff data with other sedimentary records from North and Central America. Our results highlight the sensitivity of the high altitude tropical basin to climate variations.

A Deep Learning Approach to Downscale Geostationary Satellite Imagery for Decision Support in High Impact Wildfires

Scarcity in wildland fire progression data as well as considerable uncertainties in forecasts demand improved methods to monitor fire spread in real time. However, there exists at present no scalable solution to acquire consistent information about active forest fires that is both spatially and temporally explicit. To overcome this limitation, we propose a statistical downscaling scheme based on deep learning that leverages multi-source Remote Sensing (RS) data. Our system relies on a U-Net Convolutional Neural Network (CNN) to downscale Geostationary (GEO) satellite multispectral imagery and continuously monitor active fire progression with a spatial resolution similar to Low Earth Orbit (LEO) sensors. In order to achieve this, the model trains on LEO RS products, land use information, vegetation properties, and terrain data. The practical implementation has been optimized to use cloud compute clusters, software containers and multi-step parallel pipelines in order to facilitate real time operational deployment. The performance of the model was validated in five wildfires selected from among the most destructive that occurred in California in 2017 and 2018. These results demonstrate the effectiveness of the proposed methodology in monitoring fire progression with high spatiotemporal resolution, which can be instrumental for decision support during the first hours of wildfires that may quickly become large and dangerous. Additionally, the proposed methodology can be leveraged to collect detailed quantitative data about real-scale wildfire behaviour, thus supporting the development and validation of fire spread models.