Search Results (12)

Monitoring the fuel moisture content (FMC) of 10 h dead vegetation is crucial for managing and mitigating the impact of wildland fires. The combination of in situ FMC observations, numerical weather prediction (NWP) models, and satellite retrievals has facilitated the development of machine learning (ML) models to estimate 10 h dead FMC retrievals over the contiguous US (CONUS). In this study, ML models were trained using variables from the National Water Model, the High-Resolution Rapid Refresh (HRRR) NWP model, and static surface properties, along with surface reflectances and land surface temperature (LST) retrievals from the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument on the Suomi-NPP satellite system. Extensive hyper-parameter optimization resulted in skillful FMC models compared to a daily climatography RMSE (+44%) and an hourly climatography RMSE (+24%). Notably, VIIRS retrievals played a significant role as predictors for estimating 10 h dead FMC, demonstrating their importance as a group due to their high band correlation. Conversely, individual predictors within the HRRR group exhibited relatively high importance according to explainability techniques. Removing both HRRR and VIIRS retrievals as model inputs led to a significant decline in performance, particularly with worse RMSE values when excluding VIIRS retrievals. The importance of the VIIRS predictor group reinforces the dynamic relationship between 10 h dead fuel, the atmosphere, and soil moisture. These findings underscore the significance of selecting appropriate data sources when utilizing ML models for FMC prediction. VIIRS retrievals, in combination with selected HRRR variables, emerge as critical components in achieving skillful FMC estimates. Full article

Electromagnetic radiation at 1550 nm is highly absorbed by water and offers a novel way to collect fuel moisture data, along with 3D structures of wildland fuels/vegetation, using lidar. Two terrestrial laser scanning (TLS) units (FARO s350 (phase shift, PS) and RIEGL vz-2000 (time of flight, TOF)) were assessed in a series of laboratory experiments to determine if lidar can be used to estimate the moisture content of dead forest litter. Samples consisted of two control materials, the angle and position of which could be manipulated (pine boards and cheesecloth), and four single-species forest litter types (Douglas-fir needles, ponderosa pine needles, longleaf pine needles, and southern red oak leaves). Sixteen sample trays of each material were soaked overnight, then allowed to air dry with scanning taking place at 1 h, 2 h, 4 h, 8 h, 12 h, and then in 12 h increments until the samples reached equilibrium moisture content with the ambient relative humidity. The samples were then oven-dried for a final scanning and weighing. The spectral reflectance values of each material were also recorded over the same drying intervals using a field spectrometer. There was a strong correlation between the intensity and standard deviation of intensity per sample tray and the moisture content of the dead leaf litter. A multiple linear regression model with a break at 100% gravimetric moisture content produced the best model with R2 values as high as 0.97. This strong relationship was observed with both the TOF and PS lidar units. At fuel moisture contents greater than 100% gravimetric water content, the correlation between the pulse intensity values recorded by both scanners and the fuel moisture content was the strongest. The relationship deteriorated with distance, with the TOF scanner maintaining a stronger relationship at distance than the PS scanner. Our results demonstrate that lidar can be used to detect and quantify fuel moisture across a range of forest litter types. Based on our findings, lidar may be used to quantify fuel moisture levels in near real-time and could be used to create spatial maps of wildland fuel moisture content. Full article

Firebrands are the primary source of ignition for large wildfires and urban wildfires (WUIs). China is a country with a high incidence of forest fires, and there are great differences in the terrain, climate, and other natural conditions in different regions; the frequency of forest fire will lead to greater regional differences. In the process of fighting forest fire, the fire commander should make an accurate analysis and judgment according to the various signs of the fire, which are the key to ensure the safety of the participants and to realize a quick decision. Existing studies of firebrands formation have been performed using limited quantities of wildland fuels with limited MC fuel levels and environmental conditions and lacking comprehensive data analysis including typical wildland timbers basic fuel, pyrolysis and flammability properties, and forest fire dynamic knowledge (including forest fire development period analysis and the harm of heat flux to the human body) to guide the firefighting strategy. To better understand the characteristics of firebrand formation in different Chinese regional places, a systematic study to quantify wildland fuels ignition formation by testing different fuels under different conditions is needed. The objective of this study was to determine the basic pyrolysis and flammability of wildland fuels with high fire intensity in typical areas of China to provide relevant property data, offering insight into how wildland fuels arrangement can determine the movement of wildfires for firefighting strategy. Thermogravimetric analysis (TGA) was used to determine the pyrolysis performance of selected wild fuels under different heating rates and different fuel MC values. The flammability of selected wildland fuels at different heat fluxes and at different moisture contents was determined using a cone calorimeter. This study measured the pyrolysis and flammability of some selected wildland fuels and found that some controlling factors (MC levels, heating conditions) influenced the outcome variables, especially the flammability of wildland timber. Fire behavior refers to the intensity at which a fire burns and how it moves. This research results point out the following: (1) Forest fire barriers or fuel breaks should be separated among Eucalyptus robusta Smith and Pinus massoniana before or in the fire due to high risk for ignition and strong flammability, and it is suggested to remove, control, and replace high-risk flammable timbers with low-risk flammable timbers as a part of long-term wildland fire management strategies. (2) Fire commanders could utilize some research to test conclusions and make an accurate analysis and judgment: The TTI time for each material indicates the ideal time for firefighters to put out fire, the peak of heat-release time indicates a fully developed fire to suggest firefighters finish work before the forest fire spirals out of control, and the flameout time represents the moment of low risk of fuel ignition, so firefighters could allow the fuel to burn out and change the extinguishing target to other regions of developing forest firebrands. Full article

The susceptibility of plants to burn raises concerns about fire hazard that green roofs may pose to buildings. Main concerns relate to cases when such roofs are poorly maintained or stressed by drought conditions which leads to drying out of plants and the accumulation of dead organic material, greatly increasing the availability of fuel load. Existing standard safety measures aim to prevent the spread of fire through the vegetation cover. However, fire spread by thermal radiation is not considered. In this study, fire risk of exposure of adjacent buildings to radiant heat flux produced by fire on green roofs was assessed. Based on generally accepted maximum tolerable radiant heat flux to exposed facades of 12.5 kW/m², the minimum safe separation distances were obtained for different conditions. Wildland fire behavior model was used to determine flame lengths which is the necessary parameter for a radiation model. Several vegetation types, moisture content scenarios and wind speeds were taken as variables. It was found that by providing the vegetation with reasonably high moisture content the fire risk can be greatly reduced, especially for grass-covered roofs. Since wind also has a strong effect on flame size, considering the exposure of a green roof to wind can bring better understanding of fire risk to adjacent buildings. At no-wind condition and at extremely low moisture content separation distances are as short as 3.1 m for dense shrubs and 2.4 m for tall dense grass. Full article

Remotely sensed vegetation indices have been widely used to estimate live fuel moisture content (LFMC). However, marked differences in vegetation structure affect the relationship between field-measured LFMC and reflectance, which limits spatial extrapolation of these indices. To overcome this limitation, we explored the potential of random forests (RF) to estimate LFMC at the subcontinental scale in the Mediterranean basin wildland. We built RF models (LFMC_RF) using a combination of MODIS spectral bands, vegetation indices, surface temperature, and the day of year as predictors. We used the Globe-LFMC and the Catalan LFMC monitoring program databases as ground-truth samples (10,374 samples). LFMC_RF was calibrated with samples collected between 2000 and 2014 and validated with samples from 2015 to 2019, with overall root mean square errors (RMSE) of 19.9% and 16.4%, respectively, which were lower than current approaches based on radiative transfer models (RMSE ~74–78%). We used our approach to generate a public database with weekly LFMC maps across the Mediterranean basin. Full article

The summer season of 2019–2020 has been named Australia’s Black Summer because of the large forest fires that burnt for months in southeast Australia, affecting millions of Australia’s citizens and hundreds of millions of animals and capturing global media attention. This extensive fire season has been attributed to the global climate crisis, a long drought season and extreme fire weather conditions. Our aim in this study was to examine the factors that have led some of the wildfires to burn over larger areas for a longer duration and to cause more damage to vegetation. To this end, we studied all large forest and non-forest fires (>100 km²) that burnt in Australia between September 2019 and mid-February 2020 (Australia’s Black Summer fires), focusing on the forest fires in southeast Australia. We used a segmentation algorithm to define individual polygons of large fires based on the burn date from NASA’s Visible Infrared Imaging Radiometer Suite (VIIRS) active fires product and the Moderate Resolution Imaging Spectroradiometer (MODIS) burnt area product (MCD64A1). For each of the wildfires, we calculated the following 10 response variables, which served as proxies for the fires’ extent in space and time, spread and intensity: fire area, fire duration (days), the average spread of fire (area/days), fire radiative power (FRP; as detected by NASA’s MODIS Collection 6 active fires product (MCD14ML)), two burn severity products, and changes in vegetation as a result of the fire (as calculated using the vegetation health index (VHI) derived from AVHRR and VIIRS as well as live fuel moisture content (LFMC), photosynthetic vegetation (PV) and combined photosynthetic and non-photosynthetic vegetation (PV+NPV) derived from MODIS). We also computed more than 30 climatic, vegetation and anthropogenic variables based on remotely sensed derived variables, climatic time series and land cover datasets, which served as the explanatory variables. Altogether, 391 large fires were identified for Australia’s Black Summer. These included 205 forest fires with an average area of 584 km² and 186 non-forest fires with an average area of 445 km²; 63 of the forest fires took place in southeast (SE) Australia (the area between Fraser Island, Queensland, and Kangaroo Island, South Australia), with an average area of 1097 km². Australia’s Black Summer forest fires burnt for more days compared with non-forest fires. Overall, the stepwise regression models were most successful at explaining the response variables for the forest fires in SE Australia (n = 63; median-adjusted R² of 64.3%), followed by all forest fires (n = 205; median-adjusted R² of 55.8%) and all non-forest fires (n = 186; median-adjusted R² of 48.2%). The two response variables that were best explained by the explanatory variables used as proxies for fires’ extent, spread and intensity across all models for the Black Summer forest and non-forest fires were the change in PV due to fire (median-adjusted R² of 69.1%) and the change in VHI due to fire (median-adjusted R² of 66.3%). Amongst the variables we examined, vegetation and fuel-related variables (such as previous frequency of fires and the conditions of the vegetation before the fire) were found to be more prevalent in the multivariate models for explaining the response variables in comparison with climatic and anthropogenic variables. This result suggests that better management of wildland–urban interfaces and natural vegetation using cultural and prescribed burning as well as planning landscapes with less flammable and more fire-tolerant ground cover plants may reduce fire risk to communities living near forests, but this is challenging given the sheer size and diversity of ecosystems in Australia. Full article

Across the Boreal, there is an expansive wildland–society interface (WSI), where communities, infrastructure, and industry border natural ecosystems, exposing them to the impacts of natural disturbances, such as wildfire. Treed peatlands have previously received little attention with regard to wildfire management; however, their role in fire spread, and the contribution of peat smouldering to dangerous air pollution, have recently been highlighted. To help develop effective wildfire management techniques in treed peatlands, we use seismic line disturbance as an analog for peatland fuel modification treatments. To delineate below-ground hydrocarbon resources using seismic waves, seismic lines are created by removing above-ground (canopy) fuels using heavy machinery, forming linear disturbances through some treed peatlands. We found significant differences in moisture content and peat bulk density with depth between seismic line and undisturbed plots, where smouldering combustion potential was lower in seismic lines. Sphagnum mosses dominated seismic lines and canopy fuel load was reduced for up to 55 years compared to undisturbed peatlands. Sphagnum mosses had significantly lower smouldering potential than feather mosses (that dominate mature, undisturbed peatlands) in a laboratory drying experiment, suggesting that fuel modification treatments following a strategy based on seismic line analogs would be effective at reducing smouldering potential at the WSI, especially under increasing fire weather. Full article

In recent years, severe and deadly wildland-urban interface (WUI) fires have resulted in an increased focus on this particular risk to humans and property, especially in Canada, USA, Australia, and countries in the Mediterranean area. Also, in areas not previously accustomed to wildfires, such as boreal areas in Sweden, Norway, and in the Arctic, WUI fires have recently resulted in increasing concern. January 2014, the most severe wooden town fire in Norway since 1923 raged through Lærdalsøyri. Ten days later, a wildfire raged through the scattered populated community of Flatanger and destroyed even more structures. These fires came as a surprise to the fire brigades and the public. We describe and analyze a proposed way forward for exploring if and how this increasing fire incidence can be linked to concomitant changes in climate, land-use, and habitat management; and then aim at developing new dynamic adaptive fire risk assessment and management tools. We use coastal Norway as an example and focus on temporal changes in fire risk in wooden structure settlements and in the Norwegian Calluna vulgaris L. dominated WUI. In this interface, the fire risk is now increasing due to a combination of land-use changes, resulting in large areas of early successional vegetation with an accumulation of biomass, and the interactive effects of climatic changes resulting in increased drought risk. We propose a novel bow-tie framework to explore fire risk and preventive measures at various timescales (years, months, weeks, hours) as a conceptual model for exploring risk contributing factors and possibilities for risk management. Ignition is the top event of the bow-tie which has the potential development towards a fire disaster as a worst case outcome. The bow-tie framework includes factors such as changes in the built environment and natural habitat fuel moisture content due to the weather conditions, WUI fuel accumulation, possibly improved ecosystem management, contribution by civic prescribed burner groups, relevant fire risk modeling, and risk communication to the fire brigades and the public. We propose an interdisciplinary research agenda for developing this framework and improving the current risk understanding, risk communication, and risk management. This research agenda will represent important contributions in paving the road for fire disaster prevention in Norway, and may provide a model for other systems and regions. Full article

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

Fine-fuel moisture is an important variable in the wildland fire environment, but measuring live fuel moisture is time-consuming. There is a strong incentive to develop technologies that provide instantaneous measurements of fine-fuel moisture. Campbell Scientific, Inc. markets a device that uses dielectric permittivity to measure the moisture content of duff fuels in forests; this Duff Moisture Meter (DMM600) might also be applied to herbaceous grassland fuels but its effectiveness has not been tested. This paper describes how grassland fuel samples collected for the DMM600 do well to represent the broader fuelbed, and that the dielectric permittivity values of the DMM600 correlate well with the actual moisture content of uncured grassland fuels. Results suggest the DMM600 can effectively estimate moisture content in uncured grassland fuels, including the overall fuelbed as well as live herbaceous fuels and well-aggregated samples of the grassland litter layer. Calibration equations and tips to ensure representative data are provided. Full article

The most destructive wildland fires occur in mixtures of living and dead vegetation, yet very little attention has been given to the fundamental differences between factors that control their flammability. Historically, moisture content has been used to evaluate the relative flammability of live and dead fuels without considering major, unreported differences in the factors that control their variations across seasons and years. Physiological changes at both the leaf and whole plant level have the potential to explain ignition and fire behavior phenomena in live fuels that have been poorly explained for decades. Here, we explore how these physiological changes violate long-held assumptions about live fuel dynamics and we present a conceptual model that describes how plant carbon and water cycles independently and interactively influence plant flammability characteristics at both the leaf and whole plant scale. This new ecophysiology-based approach can help us expand our understanding of potential plant responses to environmental change and how those physiological changes may impact plant flammability. Furthermore, it may ultimately help us better manage wildland fires in an uncertain future. Full article

The goal of the research reported here is to assess the capability of satellite vegetation indices from the Moderate Resolution Imaging Spectroradiometer onboard both Terra and Aqua satellites, in order to replicate live fuel moisture content of Southern California chaparral ecosystems. We compared seasonal and interannual characteristics of in-situ live fuel moisture with satellite vegetation indices that were averaged over different radial extents around each live fuel moisture observation site. The highest correlations are found using the Aqua Enhanced Vegetation Index for a radius of 10 km, independently verifying the validity of in-situ live fuel moisture measurements over a large extent around each in-situ site. With this optimally averaged Enhanced Vegetation Index, we developed an empirical model function of live fuel moisture. Trends in the wet-to-dry phase of vegetation are well captured by the empirical model function on interannual time-scales, indicating a promising method to monitor fire danger levels by combining satellite, in-situ, and model results during the transition before active fire seasons. An example map of Enhanced Vegetation Index-derived live fuel moisture for the Colby Fire shows a complex spatial pattern of significant live fuel moisture reduction along an extensive wildland-urban interface, and illustrates a key advantage in using satellites across the large extent of wildland areas in Southern California. Full article