Research Database
Displaying 1 - 20 of 38
Drivers and Impacts of the Record-Breaking2023 Wildfire Season in Canada
Year: 2024
The 2023 wildfire season in Canada was unprecedented in its scale andintensity, spanning from mid-April to late October and across much of theforested regions of Canada. Here, we summarize the main causes and impactsof this exceptional season. The record-breaking total area burned (~15 Mha)can be attributed to several environmental factors that converged early in theseason: early snowmelt, multiannual drought conditions in western Canada,and the rapid transition to drought in eastern Canada. Anthropogenic climatechange enabled sustained extreme fire weather conditions, as the meanMay–October…
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
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
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
Remote sensing applications for prescribed burn research
Year: 2024
Prescribed burning is a key management strategy within fire-adapted systems, and improved monitoring approaches are needed to evaluate its effectiveness in achieving social-ecological outcomes. Remote sensing provides opportunities to analyse the impacts of prescribed burning, yet a comprehensive understanding of the applications of remote sensing for prescribed burn research is lacking. We conduct a literature review of 120 peer-reviewed publications to synthesise the research aims, methodologies, limitations and future directions of remote sensing for the analysis of prescribed fire.…
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
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
The Power Grid/Wildfire Nexus: Using GIS and Satellite Remote Sensing to Identify Vulnerabilities
Year: 2023
The effects of wildfire on the power grid are a recurring concern for utility companies who need reliable information about where to prioritize infrastructure hardening. Though there are existing data layers that provide measures of burn probability, these models predominately consider long-term climate variables, which are not helpful when analyzing current season trends. Utility companies need data that are temporally and locally relevant. To determine the primary drivers of burn probability relative to power grid vulnerability, this study assessed potential wildfire drivers that are both…
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
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
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
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
Evaluating Satellite Fire Detection Products and an Ensemble Approach for Estimating Burned Area in the United States
Year: 2022
Fire location and burning area are essential parameters for estimating fire emissions. However, ground-based fire data (such as fire perimeters from incident reports) are often not available with the timeliness required for real-time forecasting. Fire detection products derived from satellite instruments such as the GOES-16 Advanced Baseline Imager or MODIS, on the other hand, are available in near real-time. Using a ground fire dataset of 2699 fires during 2017–2019, we fit a series of linear models that use multiple satellite fire detection products (HMS aggregate fire product, GOES-16,…
Publication Type: Journal Article
Wildfire controls on land surface properties in mixed conifer and ponderosa pine forests of Sierra Nevada and Klamath mountains, Western US
Year: 2022
This study examines the post-fire biogeophysical and biochemical dynamics after several high-severity wildfires that occurred in mixed conifer and ponderosa pine forest types in the Sierra Nevada and Klamath Mountains regions between 1986 and 2017. We found a consistent pattern of reduced leaf area index (LAI) in the first year after fire, followed by gradual recovery over the subsequent 25 years. Recovery rate varied between forest types. For example, average summer LAI for 16-25 years post-fire was 88% of the pre-fire average for mixed conifers in the Sierra Nevada, 64% for ponderosa pine…
Publication Type: Journal Article
Contemporary (1984–2020) fire history metrics for the conterminous United States and ecoregional differences by land ownership
Year: 2022
Background: Remotely sensed burned area products are critical to support fire modelling, policy, and management but often require further processing before use. Aim: We calculated fire history metrics from the Landsat Burned Area Product (1984–2020) across the conterminous U.S. (CONUS) including (1) fire frequency, (2) time since last burn (TSLB), (3) year of last burn, (4) longest fire-free interval, (5) average fire interval length, and (6) contemporary fire return interval (cFRI). Methods: Metrics were summarised by ecoregion and land ownership, and related to historical and cheatgrass…
Publication Type: Journal Article
Using Landsat Imagery to Assess Burn Severity of National Forest Inventory Plots
Year: 2021
As the frequency and size of wildfires increase, accurate assessment of burn severityis essential for understanding fire effects and evaluating post-fire vegetation impacts. Remotelysensedimagery allows for rapid assessment of burn severity, but it also needs to be field validated.Permanent forest inventory plots can provide burn severity information for the field validation ofremotely-sensed burn severity metrics, although there is often a mismatch between the size andshape of the inventory plot and the resolution of the rasterized images. For this study, we used twodistinct datasets: (1)…
Publication Type: Journal Article
Mixed-severity wildfire and habitat of an old-forest obligate
Year: 2019
The frequency, extent, and severity of wildfire strongly influence the structure and function of ecosystems. Mixed‐severity fire regimes are the most complex and least understood fire regimes, and variability of fire severity can occur at fine spatial and temporal scales, depending on previous disturbance history, topography, fuel continuity, vegetation type, and weather. During high fire weather in 2013, a complex of mixed‐severity wildfires burned across multiple ownerships within the Klamath‐Siskiyou ecoregion of southwestern Oregon where northern spotted owl (Strix occidentalis caurina)…
Publication Type: Journal Article
Examining post-fire vegetation recovery with Landsat time series analysis in three western North American forest types
Year: 2019
Background: Few studies have examined post-fire vegetation recovery in temperate forest ecosystems with Landsat time series analysis. We analyzed time series of Normalized Burn Ratio (NBR) derived from LandTrendr spectral-temporal segmentation fitting to examine post-fire NBR recovery for several wildfires that occurred in three different coniferous forest types in western North America during the years 2000 to 2007. We summarized NBR recovery trends, and investigated the influence of burn severity, post-fire climate, and topography on post-fire vegetation recovery via random forest (RF)…
Publication Type: Journal Article
Increasing trends in high-severity fire in the southwestern USA from 1984 to 2015
Year: 2019
In the last three decades, over 4.1 million hectares have burned in Arizona and New Mexico and the largest fires in documented history have occurred in the past two decades. Changes in burn severity over time, however, have not been well documented in forest and woodland ecosystems in the southwestern US. Using remotely sensed burn severity data from 1621 fires (>404 ha), we assessed trends from 1984 to 2015 in Arizona and New Mexico in (1) number of fires and total area burned in all vegetation types; (2) area burned, area of high-severity, and percent of high-severity fire in all forest…
Publication Type: Journal Article
Multitemporal LiDAR improves estimates of fire severity in forested landscapes
Year: 2018
Landsat-based fire severity maps have limited ecological resolution, which can hinder assessments of change to specific resources. Therefore, we evaluated the use of pre- and post-fire LiDAR, and combined LiDAR with Landsat-based relative differenced Normalized Burn Ratio (RdNBR) estimates, to increase the accuracy and resolution of basal area mortality estimation. We vertically segmented point clouds and performed model selection on spectral and spatial pre- and post-fire LiDAR metrics and their absolute differences. Our best multitemporal LiDAR model included change in mean intensity values…
Publication Type: Journal Article