Research Database
Displaying 21 - 40 of 109
Leveraging the next generation of spaceborne Earth observations for fuel monitoring and wildland fire management
Year: 2024
Managing fuels is a key strategy for mitigating the negative impacts of wildfires on people and the environment. The use of satellite-based Earth observation data has become an important tool for managers to optimize fuel treatment planning at regional scales. Fortunately, several new sensors have been launched in the last few years, providing novel opportunities to enhance fuel characterization. Herein, we summarize the potential improvements in fuel characterization at large scale (i.e., hundreds to thousands of km2) with high spatial and spectral resolution arising from the use of new…
Publication Type: Journal Article
Montane springs provide regeneration refugia after high-severity wildfire
Year: 2024
In the mountainous regions of the Western United States, increasing wildfire activity and climate change are putting forests at risk of regeneration failure and conversion to non-forests. During periods with unfavorable climatic conditions, locations that are suitable for post-fire tree regeneration (regeneration refugia) may be essential for forest recovery. These refugia could provide scattered islands of recovering forest from which broader forest recovery may be facilitated. Spring ecosystems provide cool and wet microsites relative to the surrounding landscape and may act as regeneration…
Publication Type: Journal Article
Snow-cover remote sensing of conifer tree recovery in high-severity burn patches
Year: 2024
The number of large, high-severity wildfires has been increasing across the western United States over the last several decades. It is not fully understood how changes in the frequency of large, severe wildfires may impact the resilience of conifer forests, due to alterations in regeneration success or failure. Our research investigates 30 years of conifer recovery patterns within 34 high-severity wildfire complexes (1988–1991) of the Northern Rocky Mountains. We evaluate the capability of snow-cover Landsat to characterize conifer tree recolonization of high-severity burn patches. Snow-…
Publication Type: Journal Article
Before the fire: predicting burn severity and potential post-fire debris-flow hazards to conservation populations of the Colorado River Cutthroat Trout (Oncorhynchus clarkii pleuriticus)
Year: 2024
Background: Colorado River Cutthroat Trout (CRCT; Oncorhynchus clarkii pleuriticus) conservation populations may be at risk from wildfire and post-fire debris flows hazards. Aim: To predict burn severity and potential post-fire debris flow hazard classifications to CRCT conservation populations before wildfires occur. Methods: We used remote sensing, spatial analyses, and machine learning to model 28 wildfire incidents (2016–2020) and spatially predict burn severity from pre-wildfire environmental factors to evaluate the likelihood…
Publication Type: Journal Article
Landsat assessment of variable spectral recovery linked to post-fire forest structure in dry sub-boreal forests
Year: 2024
Forest disturbances such as wildfires can dramatically alter forest structure and composition, increasing the likelihood of ecosystem changes. Up-to-date and accurate measures of post-disturbance forest recovery in managed forests are critical, particularly for silvicultural planning. Measuring the live and dead vegetation post-fire is challenging because areas impacted by wildfire may be remote, difficult to access, and/or dangerous to survey. The difficulties of post-fire monitoring are compounded by the global increase in the frequency and severity of disturbances, as expansion of…
Publication Type: Journal Article
Visibility-informed mapping of potential firefighter lookout locations using maximum entropy modelling
Year: 2024
BackgroundSituational awareness is an essential component of wildland firefighter safety. In the US, crew lookouts provide situational awareness by proxy from ground-level locations with visibility of both fire and crew members.AimsTo use machine learning to predict potential lookout locations based on incident data, mapped visibility, topography, vegetation, and roads.MethodsLidar-derived topographic and fuel structural variables were used to generate maps of visibility across 30 study areas that possessed lookout location data. Visibility…
Publication Type: Journal Article
Fuel constraints, not fire weather conditions, limit fire behavior in reburned boreal forests
Year: 2024
Fire frequency in boreal forests has increased via longer burning seasons, drier conditions, and higher temperatures. However, fires have historically self-regulated via fuel limitations, mediating the effects of changes in climate and fire weather. Early post-fire boreal forests (10–15 years postfire) are often dominated by mixed conifer-broadleaf or broadleaf regeneration, considered less flammable due to the higher foliar moisture of broadleaf trees and shrubs compared to their more intact conifer counterparts. However, the strength of self-regulation in the context of changing fire…
Publication Type: Journal Article
A fast spectral recovery does not necessarily indicate post-fire forest recovery
Year: 2024
BackgroundClimate change has increased wildfire activity in the western USA and limited the capacity for forests to recover post-fire, especially in areas burned at high severity. Land managers urgently need a better understanding of the spatiotemporal variability in natural post-fire forest recovery to plan and implement active recovery projects. In burned areas, post-fire “spectral recovery”, determined by examining the trajectory of multispectral indices (e.g., normalized burn ratio) over time, generally corresponds with recovery of multiple post-fire vegetation types, including trees and…
Publication Type: Journal Article
Pixels to pyrometrics: UAS-derived infrared imagery to evaluate and monitor prescribed fire behaviour and effects
Year: 2024
Background: Prescribed fire is vital for fuel reduction and ecological restoration, but the effectiveness and fine-scale interactions are poorly understood. Aims: We developed methods for processing uncrewed aircraft systems (UAS) imagery into spatially explicit pyrometrics, including measurements of fuel consumption, rate of spread, and residence time to quantitatively measure three prescribed fires. Methods: We collected infrared (IR) imagery continuously (0.2 Hz) over prescribed burns and one experimental calibration burn, capturing…
Publication Type: Journal Article
Biogeographic patterns of daily wildfire spread and extremes across North America
Year: 2024
Introduction: Climate change is predicted to increase the frequency of extreme single-day fire spread events, with major ecological and social implications. In contrast with well-documented spatio-temporal patterns of wildfire ignitions and perimeters, daily progression remains poorly understood across continental spatial scales, particularly for extreme single-day events (“blow ups”). Here, we characterize daily wildfire spread across North America, including occurrence of extreme single-day events, duration and seasonality of fire and extremes, and ecoregional climatic…
Publication Type: Journal Article
Abiotic Factors Modify Ponderosa Pine Regeneration Outcomes After High-Severity Fire
Year: 2024
Large high-severity burn patches are increasingly common in southwestern US dry conifer forests. Seed-obligate conifers often fail to quickly regenerate large patches because their seeds rarely travel the distances required to reach core patch area. Abiotic factors may further alter the distance seeds can travel to regenerate a patch, which would change expected post-fire regeneration patterns. We used the presence and density of ponderosa pine regeneration as a proxy for seed dispersal to quantify the effect of abiotic factors on seed dispersal into high-severity patches. We established 45…
Publication Type: Journal Article
Ladder fuels rather than canopy volumes consistently predict wildfire severity even in extreme topographic-weather conditions
Year: 2024
Drivers of forest wildfire severity include fuels, topography and weather. However, because only fuels can be actively managed, quantifying their effects on severity has become an urgent research priority. Here we employed GEDI spaceborne lidar to consistently assess how pre-fire forest fuel structure affected wildfire severity across 42 California wildfires between 2019–2021. Using a spatial-hierarchical modeling framework, we found a positive concave-down relationship between GEDI-derived fuel structure and wildfire severity, marked by increasing severity with greater fuel loads until a…
Publication Type: Journal Article
Exploring the use of satellite Earth observation active wildland fire hotspot data via open access web platforms
Year: 2024
Globally, managing wildland fire is increasing in complexity. Satellite Earth Observation (EO) data, specifically active fire ‘hotspot’ data, is often used to inform wildland fire management. This study explores hotspot data usage via web traffic data (‘user counts’) for the FIRMS, GWIS and EFFIS web portals between September 2019 and April 2023. Global active fire data use is characterized by multi-month periods of relatively low, stable user counts, interspersed with periodic spikes (4.1x median monthly activity) of activity broadly aligned with the North American / European fire season (…
Publication Type: Journal Article
Carbon emissions from the 2023 Canadian wildfires
Year: 2024
The 2023 Canadian forest fires have been extreme in scale and intensity with more than seven times the average annual area burned compared to the previous four decades. Here, we quantify the carbon emissions from these fires from May to September 2023 on the basis of inverse modelling of satellite carbon monoxide observations. We find that the magnitude of the carbon emissions is 647 TgC (570–727 TgC), comparable to the annual fossil fuel emissions of large nations, with only India, China and the USA releasing more carbon per year. We find that widespread hot–dry weather was a principal…
Publication Type: Journal Article
Molecular shifts in dissolved organic matter along a burn severity continuum for common land cover types in the Pacific Northwest, USA
Year: 2024
Increasing wildfire severity is of growing concern in the western United States, with consequences for the production, composition, and mobilization of dissolved organic matter (DOM) from terrestrial to aquatic systems. Our current understanding of wildfire impacted DOM (often termed pyrogenic DOM) composition is largely built from temperature-based studies that can be difficult to extrapolate to field conditions, which are often defined by ‘burn severity’, or the post-wildfire impact observed at a site. Thus, burn severity can encapsulate a broader range of fire and environmental conditions…
Publication Type: Journal Article
Metrics and Considerations for Evaluating How Forest Treatments Alter Wildfire Behavior and Effects
Year: 2023
The influence of forest treatments on wildfire effects is challenging to interpret. This is, in part, because the impact forest treatments have on wildfire can be slight and variable across many factors. Effectiveness of a treatment also depends on the metric considered. We present and define human–fire interaction, fire behavior, and ecological metrics of forest treatment effects on wildfire and discuss important considerations and recommendations for evaluating treatments. We demonstrate these concepts using a case study from the Cameron Peak Fire in Colorado, USA. Pre-fire forest…
Publication Type: Journal Article
Using soil moisture information to better understand and predict wildfire danger: a review of recent developments and outstanding questions
Year: 2023
Soil moisture conditions are represented in fire danger rating systems mainly through simple drought indices based on meteorological variables, even though better sources of soil moisture information are increasingly available. This review summarises a growing body of evidence indicating that greater use of in situ, remotely sensed, and modelled soil moisture information in fire danger rating systems could lead to better estimates of dynamic live and dead herbaceous fuel loads, more accurate live and dead fuel moisture predictions, earlier warning of wildfire danger, and better forecasts of…
Publication Type: Journal Article
Projecting live fuel moisture content via deep learning
Year: 2023
Background: Live fuel moisture content (LFMC) is a key environmental indicator used to monitor for high wildfire risk conditions. Many statistical models have been proposed to predict LFMC from remotely sensed data; however, almost all these estimate current LFMC (nowcasting models). Accurate modelling of LFMC in advance (projection models) would provide wildfire managers with more timely information for assessing and preparing for wildfire risk. Aims: The aim of this study was to investigate the potential for deep learning models to predict LFMC across the continental United States 3 months…
Publication Type: Journal Article
Ability of seedlings to survive heat and drought portends future demographic challenges for five southwestern US conifers
Year: 2023
Climate change and disturbance are altering forests and the rates and locations of tree regeneration. In semi-arid forests of the southwestern USA, limitations imposed by hot and dry conditions are likely to influence seedling survival. We examined how the survival of 1-year seedlings of five southwestern US conifer species whose southwestern distributions range from warmer and drier woodlands and forests (Pinus edulis Engelm., Pinus ponderosa Douglas ex C. Lawson) to cooler and wetter subalpine forests (Pseudotsuga menziesii (Mirb.) Franco, Abies concolor…
Publication Type: Journal Article
Consistent, high-accuracy mapping of daily and sub-daily wildfire growth with satellite observations
Year: 2023
Background: Fire research and management applications, such as fire behaviour analysis and emissions modelling, require consistent, highly resolved spatiotemporal information on wildfire growth progression. Aims: We developed a new fire mapping method that uses quality-assured sub-daily active fire/thermal anomaly satellite retrievals (2003–2020 MODIS and 2012–2020 VIIRS data) to develop a high-resolution wildfire growth dataset, including growth areas, perimeters, and cross-referenced fire information from agency reports. Methods: Satellite fire detections were buffered using a historical…
Publication Type: Journal Article