Fuel-Specific Aggregation of Active Fire Detections for Rapid Mapping of Forest Fire Perimeters in Mexico

Context and Background. Active fires have the potential to provide early estimates of fire perimeters, but there is a lack of information about the best active fire aggregation distances and how they can vary between fuel types, particularly in large areas of study under diverse climatic conditions. Objectives. The current study aimed at analyzing the effect of aggregation distances for mapping fire perimeters from active fires for contrasting fuel types and regions in Mexico. Materials and Methods. Detections of MODIS and VIIRS active fires from the period 2012–2018 were used to obtain perimeters of aggregated active fires (AGAF) at four aggregation distances (750, 1000, 1125, and 1500 m). AGAF perimeters were compared against MODIS MCD64A1 burned area for a total of 24 fuel types and regions covering all the forest area of Mexico. Results/findings. Optimum aggregation distances varied between fuel types and regions, with the longest aggregation distances observed for the most arid regions and fuel types dominated by shrubs and grasslands. Lowest aggregation distances were obtained in the regions and fuel types with the densest forest canopy and more humid climate. Purpose/Novelty. To our best knowledge, this study is the first to analyze the effect of fuel type on the optimum aggregation distance for mapping fire perimeters directly from aggregated active fires. The methodology presented here can be used operationally in Mexico and elsewhere, by accounting for fuel-specific aggregation distances, for improving rapid estimates of fire perimeters. These early fire perimeters could be potentially available in near-real time (at every satellite pass with a 12 h latency) in operational fire monitoring GIS systems to support rapid assessment of fire progression and fire suppression planning.

Fires Drive Long-Term Environmental Degradation in the Amazon Basin

The Amazon Basin is undergoing extensive environmental degradation as a result of deforestation and the rising occurrence of fires. The degradation caused by fires is exacerbated by the occurrence of anomalously dry periods in the Amazon Basin. The objectives of this study were: (i) to quantify the extent of areas that burned between 2001 and 2019 and relate them to extreme drought events in a 20-year time series; (ii) to identify the proportion of countries comprising the Amazon Basin in which environmental degradation was strongly observed, relating the spatial patterns of fires; and (iii) examine the Amazon Basin carbon balance following the occurrence of fires. To this end, the following variables were evaluated by remote sensing between 2001 and 2019: gross primary production, standardized precipitation index, burned areas, fire foci, and carbon emissions. During the examined period, fires affected 23.78% of the total Amazon Basin. Brazil had the largest affected area (220,087 fire foci, 773,360 km2 burned area, 54.7% of the total burned in the Amazon Basin), followed by Bolivia (102,499 fire foci, 571,250 km2 burned area, 40.4%). Overall, these fires have not only affected forests in agricultural frontier areas (76.91%), but also those in indigenous lands (17.16%) and conservation units (5.93%), which are recognized as biodiversity conservation areas. During the study period, the forest absorbed 1,092,037 Mg of C, but emitted 2908 Tg of C, which is 2.66-fold greater than the C absorbed, thereby compromising the role of the forest in acting as a C sink. Our findings show that environmental degradation caused by fires is related to the occurrence of dry periods in the Amazon Basin.

Characterization of global wildfire burned area spatiotemporal patterns and underlying climatic causes

Wildfires are widespread disasters and are concurrently influenced by global climatic drivers. Due to the widespread and far-reaching influence of climatic drivers, separate regional wildfires may have similar climatic cause mechanisms. Determining a suite of global climatic drivers that explain most of the variations in different homogeneous wildfire regions will be of great significance for wildfire management, wildfire prediction, and global wildfire climatology. Therefore, this study first identified spatiotemporally homogeneous regions of burned area worldwide during 2001–2019 using a distinct empirical orthogonal function. Eight patterns with different spatiotemporal characteristics were identified. Then, the relationships between major burned area patterns and sixteen global climatic drivers were quantified based on wavelet analysis. The most significant global climatic drivers that strongly impacted each of the eight major wildfire patterns were identified. The most significant combinations of hotspots and climatic drivers were Atlantic multidecadal Oscillation-East Pacific/North Pacific Oscillation (EP/NP)-Pacific North American Pattern (PNA) with the pattern around Ukraine and Kazakhstan, El Niño/Southern Oscillation-Arctic Oscillation (AO)-East Atlantic/Western Russia Pattern (EA/WR) with the pattern in Australia, and PNA-AO-Polar/Eurasia Pattern-EA/WR with the pattern in Brazil. Overall, these results provide a reference for predicting wildfire and understanding wildfire homogeneity.

Soil Chemical Properties and Fire Severity Assessment Using VNIR Proximal Spectroscopy in Fire-Affected Abandoned Orchard of Mediterranean Croatia

This paper aims to evaluate the ability of VNIR proximal soil spectroscopy to determine post-fire soil chemical properties and discriminate fire severity based on soil spectra. A total of 120 topsoil samples (0–3 cm) were taken from 6 ha of unburned (control (CON)) and burned areas (moderate fire severity (MS) and high fire severity (HS)) in Mediterranean Croatia within one year after the wildfire. Partial least squares regression (PLSR) and an artificial neural network (ANN) were used to build calibration models of soil pH, electrical conductivity (EC), CaCO3, plant-available phosphorus (P2O5) and potassium (K2O), soil organic carbon (SOC), exchangeable calcium (exCa), magnesium (exMg), potassium (exK), sodium (exNa), and cation exchange capacity (CEC), based on soil reflectance data. In terms of fire severity, CON samples exhibited higher average reflectance than MS and HS samples due to their lower SOC content. The PCA results pointed to the significance of the NIR part of the spectrum for extracting the variance in reflectance data and differentiation between the CON and burned area (MS and HS). DA generated 74.2% correctly classified soil spectral samples according to the fire severity. Both PLSR and ANN calibration techniques showed sensitivity to extract information from soil features based on hyperspectral reflectance, most successfully for the prediction of SOC, P2O5, exCa, exK, and CEC. This study confirms the usefulness of soil spectroscopy for fast screening and a better understanding of soil chemical properties in post-fire periods.

Health and Economic Burden of the 2017 Portuguese Extreme Wildland Fires on Children

Wildland fires release substantial amounts of hazardous contaminants, contributing to a decline in air quality and leading to serious health risks. Thus, this study aimed to understand the contributions of the 2017 extreme wildland fires in Portugal on children health, compared to 2016 (with burned area, in accordance with the average of the previous 15 years). The impact of long-term exposure to PM10 and NO2 concentrations, associated with wildland fires, on postneonatal mortality, bronchitis prevalence, and bronchitis symptoms in asthmatic children was estimated, as well as the associated costs. The excess health burden in children attributable to exposure to PM10 and NO2, was calculated based on WHO HRAPIE relative risks. Fire emissions were obtained from the Fire INventory from NCAR (FINN). The results obtained indicate that the smoke from wildfires negatively impacts children’s lung function (PM10 exposure: increase of 320 and 648 cases of bronchitis in 2016 and 2017; NO2 exposure: 24 and 40 cases of bronchitis symptoms in asthmatic children in 2016 and 2017) and postneonatal mortality (PM10 exposure: 0.2 and 0.4 deaths in 2016 and 2017). Associated costs were increased in 2017 by around 1 million € for all the evaluated health endpoints, compared to 2016.

A mathematical model to study the dynamics of carbon capture in forest plantations

Fast-growing forest plantations play an important role in reducing global warming and have great potential for carbon capture. In this study, we aimed to model the dynamics of carbon capture in fast-growing plantations. A mathematical model is proposed consisting of a tridimensional nonlinear system. The variables involved are the amount of living biomass, the intrinsic growth of biomass, and the burned area by forestry fire. The environmental humidity is also considered, assumed as a parameter by simplicity. The solutions of the model are approximated numerically by the Runge-Kutta fourth-order method. Once the equilibria of the model have been obtained and its local stability determined, the analysis of the model reveals that the living biomass, as well as the stored carbon, decreases in each harvest cycle as a consequence of the negative effects of fire on soil properties. Furthermore, the model shows that the maximum area burned is attained always after the maximum volume of biomass is obtained. Numerical simulations show that the model solutions are reasonable for the growth dynamics of a plantation, from a theoretical perspective. The mathematical results suggest that a suitable optimal management strategy to avoid biomass losses in the successive regeneration cycles of the plantation is the prevention of fires together with soil fertilization, applied to fast-growing plantations.

Post-Fire Vegetation Recovery in Elwasita Area of Al-Jabal Al-Akhdar-Libya - Based on Remote Sensing Information

Satellite-based remote sensing technologies and Geographical Information Systems (GIS) present operable and cost-effective solutions for mapping fires and observing post-fire regeneration. Elwasita wildfire, which occurred during April and May in 2013 in Libya, was selected as a study site. This study aims to monitor vegetation recovery and investigate the relationship between vegetation recovery and topographic factors by using multi-temporal spectral indices together with topographical factors. Landsat 8 (OLI and TIRS) images from different data were obtained which were for four years; April 2013, June 2014, July 2015, and July 2016, to assess the related fire severity using the widely-used Normalized Burn Ratio (NBR). Normalized difference Vegetation Index (NDVI) was used to determine vegetation regeneration dynamics for four consecutive years. Also, the state of damage, vegetation recovery and, damage dimensions about the burned area were capable of being effectively detected using the result of supervised classification of Landsat satellite images. In addition, aspect, slope, and altitude images derived from Digital Elevation Model (DEM) were used to determine the fire severity of the study area. The results have found that it could be possible to figure out the degree of vegetation recovery by calculating the NDVI and NBR using Landsat 8 OLI and TIRS images. Analysis showed that it mainly oriented towards the northwest (47%), north (29%), and northeast (12%). The statistical analysis showed that fire was concentrated on the incline by 76%, and the most affected areas are those between 200 m-450 m above sea level, with a percentage of 80%. It is expected that the information can be acquired by various satellite data and digital forests. This study serves as a window to an understanding of the process of fire severity and vegetation recovery that is vital in wildfire management systems.

Assessing the role of compound drought and heatwave events on unprecedented 2020 wildfires in the Pantanal

The year 2020 had the most catastrophic fire season over the last two decades in the Pantanal, which led to outstanding environmental impacts. Indeed, much of the Pantanal has been affected by severe dry conditions since 2019, with evidence of the 2020’s drought being the most extreme and widespread ever recorded in the last 70 years. Although it is unquestionable that this mega-drought contributed significantly to the increase of fire risk, so far, the 2020’s fire season has been analyzed at the univariate level of a single climate event, not considering the co-occurrence of extreme and persistent temperatures with soil dryness conditions. Here, we show that similarly to other areas of the globe, the influence of land-atmosphere feedbacks contributed decisively to the simultaneous occurrence of dry and hot spells (HPs), exacerbating fire risk. The ideal synoptic conditions for strong atmospheric heating and large evaporation rates were present, in particular during the HPs, when the maximum temperature was, on average, 6 ºC above the normal. The short span of the period during those compound drought-heatwave (CDHW) events accounted for 55% of the burned area of 2020. The vulnerability in the northern forested areas was higher than in the other areas, revealing a synergistic effect between fuel availability and weather-hydrological conditions. Accordingly, where fuel is not a limiting factor, fire activity tends to be more modelled by CDHW events. Our work advances beyond an isolated event-level basis towards a compound and cascading natural hazards approach, simultaneously estimating the contribution of drought and heatwaves to fuelling extreme fire outbreaks in the Pantanal such as those in 2020. Thus, these findings are relevant within a broader context, as the driving mechanisms apply across other ecosystems, implying higher flammability conditions and further efforts for monitoring and predicting such extreme events.

Frequency of Fires in the Miombo Woodland of the Gilé National Park. Province of Zambezia

Fires occur in a widespread manner in various types of vegetation cover at national level, and are often associated with human hunting, grazing and above all the practice of itinerant agriculture. With the purpose to propose the map of frequency of fire, remote sensing data was collected from 2014 to 2018, using the Moderate Resolution Image Spectroradiometer (MODIS) of the burned area (MCD64A1), which allowed the construction of the map of frequency and intensity of fires, associated with data collected in 59 plots on field. It was observed that the Gilé National Park (PNAG) records an average fire frequency of 0.38 times/year and the return interval of 5.38 years, and an average fire return interval of 2.62 years. During the study period, the PNAG burned 92.8% of the area, which means that on average for each year it burned about 18.56% of its area, there are no significant differences in relation to the area burned per year (p> 0.942037) but there are significant differences in relation to the area burned per month (p <1.24e-07).