Research Database
Displaying 21 - 40 of 102
Unlocking the potential of Airborne LiDAR for direct assessment of fuel bulk density and load distributions for wildfire hazard mapping
Year: 2024
Large-scale mapping of fuel load and fuel vertical distribution is essential for assessing fire danger, setting strategic goals and actions, and determining long-term resource needs. The Airborne LiDAR system can fulfil such goal by accurately capturing the three-dimensional arrangement of vegetation at regional and national scales. We developed a novel method to estimate multiple metrics of fuel load and vertical bulk density distribution for any type of vegetation. The approach uses Beer-Lambert law for inverting the ALS point cloud into vertical plant area density profiles, which are…
Publication Type: Journal Article
Global variation in ecoregion flammability thresholds
Year: 2024
Anthropogenic climate change is altering the state of worldwide fire regimes, including by increasing the number of days per year when vegetation is dry enough to burn. Indices representing the percent moisture content of dead fine fuels as derived from meteorological data have been used to assess geographic patterns and temporal trends in vegetation flammability. To date, this approach has assumed a single flammability threshold, typically between 8 and 12%, controlling fire potential regardless of the vegetation type or climate domain. Here we use remotely sensed burnt area products and a…
Publication Type: Journal Article
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
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
Wildfire probability estimated from recent climate and fine fuels across the big sagebrush region
Year: 2024
BackgroundWildfire is a major proximate cause of historical and ongoing losses of intact big sagebrush (Artemisia tridentata Nutt.) plant communities and declines in sagebrush obligate wildlife species. In recent decades, fire return intervals have shortened and area burned has increased in some areas, and habitat degradation is occurring where post-fire re-establishment of sagebrush is hindered by invasive annual grasses. In coming decades, the changing climate may accelerate these wildfire and invasive feedbacks, although projecting future wildfire dynamics requires a better…
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
Disentangling drivers of annual grass invasion: Abiotic susceptibility vs. fire-induced conversion to cheatgrass dominance in the sagebrush biome
Year: 2024
Invasive annual grasses are often facilitated by fire, yet they can become ecologically dominant in susceptible locations even in the absence of fire. We used an extensive vegetation plot database to model susceptibility to the invasive annual grass cheatgrass (Bromus tectorum L.) in the sagebrush biome as a function of climate and soil water availability variables. We built random forest models predicting cheatgrass presence or dominance (>15 % relative cover) under unburned (37,219 plots) and burned conditions (6340 plots). We mapped predicted probability of cheatgrass…
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
Review of fuel treatment effects on fuels, fire behavior and ecological resilience in sagebrush (Artemisia spp.) ecosystems in the Western U.S.
Year: 2024
BackgroundSagebrush ecosystems are experiencing increases in wildfire extent and severity. Most research on vegetation treatments that reduce fuels and fire risk has been short term (2–3 years) and focused on ecological responses. We review causes of altered fire regimes and summarize literature on the longer-term effects of treatments that modify (1) shrub fuels, (2) pinyon and juniper canopy fuels, and (3) fine herbaceous fuels. We describe treatment effects on fuels, fire behavior, ecological resilience, and resistance to invasive annual grasses.ResultsOur review revealed tradeoffs in…
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
Fire needs annual grasses more than annual grasses need fire
Year: 2023
Sagebrush ecosystems of western North America are experiencing widespread loss and degradation by invasive annual grasses. Positive feedbacks between fire and annual grasses are often invoked to explain the rapid pace of these changes, yet annual grasses also appear capable of achieving dominance among vegetation communities that have not burned for many decades. Using a dynamic, remotely-sensed vegetation dataset in tandem with remotely-sensed fire perimeter and burn severity datasets, we examine the role of fire in transitions to and persistence of annual grass dominance in the U.S. Great…
Publication Type: Journal Article
Deterioration of air quality associated with the 2020 US wildfires
Year: 2023
The wildfires of August and September 2020 in the western part of the United States were characterized by an unparalleled duration and wide geographical coverage. A particular consequence of massive wildfires includes serious health effects due to short and long-term exposure to poor air quality. Using a variety of data sources including aerosol optical depth (AOD) and ultraviolet aerosol index (UVAI), obtained with the Moderate-Resolution Imaging Spectroradiometer (MODIS), Multi-Angle Implementation of Atmospheric Correction (MAIAC) and Tropospheric Monitoring Instrument (TROPOMI), combined…
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
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
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
Different approaches make comparing studies of burn severity challenging: a review of methods used to link remotely sensed data with the Composite Burn Index
Year: 2023
The Composite Burn Index (CBI) is commonly linked to remotely sensed data to understand spatial and temporal patterns of burn severity. However, a comprehensive understanding of the tradeoffs between different methods used to model CBI with remotely sensed data is lacking. To help understand the current state of the science, provide a blueprint towards conducting broad- scale meta-analyses, and identify key decision points and potential rationale, we conducted a review of studies that linked remotely sensed data to continuous estimates of burn severity measured with the CBI and related…
Publication Type: Journal Article