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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Oregon Wildfires: Integrating ECOSTRESS to Map & Analyze Vegetation Moisture for Wildfire Modeling

Wildfire season in the western USA is starting earlier and gaining in intensity. The Bootleg Fire in Southern Oregon began on July 6th, 2021, and burned over 1675 km2 before it was fully contained on August 15th, 2021. Evapotranspiration (ET) is one indicator of vegetation moisture and there is interest in using high-resolution ET products from ECOsystem and Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) in future wildfire modeling. In partnership with the Pacific Northwest National Laboratory and US Forest Service, the team examined ECOSTRESS ET for the two years before the Bootleg Fire and assessed the relationship between ET, topography, and vegetation. Remotely sensed data from Shuttle Radar Topography Mission (SRTM) and Global Ecosystem Dynamics Investigation (GEDI) along with ancillary data from the National Land Cover Database (NLCD) and Landscape Fire Resource Management Planning Tools (LANDFIRE) were incorporated. The team examined data in relation to soil burn severity from the Burned Area Emergency Response (BAER) program. From ET median composites for April 1st – July 5th, 2021 and 2019, the Bootleg Fire area showed a 7 mm/day decrease in ET and a relative 75% decrease in ET between 2019 and 2021. Approximately 6% of the Bootleg Fire area was identified as having a high soil burn severity and these areas were found predominantly in the evergreen forest land cover class and northward facing slopes with a mean ET decrease of 3 mm/day between 2019 and 2021. The team also analyzed ECOSTRESS Water Use Efficiency products as an additional vegetation moisture indicator of pre-fire conditions in the study area. The end products will allow the partners to assess if higher resolution vegetation moisture datasets from ECOSTRESS will improve wildfire modeling for other susceptible areas.

Brenna Hatch↗
NASA NTRS2023

StratoFIRE: Modeling Wildfire Smoke in the Stratosphere

The most extreme manifestation of a fire–weather interaction is the formation of pyrocumulonimbus (pyroCb) thunderstorms, triggered by super-heated updrafts, which can eject smoke at altitudes exceeding 20 Km. In this study, we investigated climate-related impacts from the most intensive pyroCb-triggered injection of smoke in the stratosphere: the Australian New Year wildfires in 2019/2020. We first provide a general overview of the vision and objectives of the StratoFIRE project. With the aid of the global chemistry-climate model EMAC, we then simulate radiative and chemical perturbations in the stratosphere in relation to 0.9 Tg smoke in the stratosphere assuming different injection heights, from 13 to 16 Km. The simulation of stratospheric optical depth perturbations were found to be sensitive to the assumed injection height, with a maximum height at 16 Km showing the best agreement with the GLOSSAC and SAGE-ISS aerosol extinction observations.

PyroCb↗
NASA NTRSDate not supplied

NASA's New Wildland Fire Earth Observation Science & Applications Programmatic Developments

In 2021, the U.S. National Aeronautics & Space Administration (NASA) initiated new programmatic elements within the Science Mission Directorate (SMD) and the Aeronautics Research Mission Directorate (ARMD) focused on supporting wildland fire science and applications improvements, employing the vast array of NASA scientific knowledge, airborne and space-borne Earth Observations (EO) capabilities, technology development (sensor systems, etc.), and large framework modeling efforts. Within the Science Mission Directorate, the NASA Earth Science Division (ESD) will focus on improving our understanding of wildland fire through EO tools and applying rigorous-tested modeling and results of that research into operational use. The ESD Wildfire strategy is to invest in new technology and to better integrate NASA’s satellite, airborne, and ground-based observations with wildfire models to provide the wildfire stakeholders with the information they need to make informed decisions about the pre-, active-, and post-fire conditions. The Applied Science Program has restarted the Wildland Fire Applications Program with a focus on engaging wildland fire management and the fire science community in transitioning EO science efforts into routine use by land management entities at the local, state, national and international level. The NASA Aeronautics Research Mission Directorate will focus on arenas where their aeronautics science and engineering outcomes can benefit the fire management community as well, specifically in the innovative development of Uncrewed Aircraft systems, congested mixed-use platform airspace management issues, new platform configurations supporting wildland fire missions, and other aeronautics-related science / engineering capabilities which may benefit the fire management community. In total, these developments represent a major thrust forward, supporting the goals of utilizing NASA science to benefit humankind. This presentation will highlight the various wildland fire science focus areas identified through collaborations with the wildland fire science and management community and highlight the plans of this new NASA focus area.

NASA↗
NASA NTRS2001

Modeling and Prediction of Wildfire Hazard in Southern California, Integration of Models with Imaging Spectrometry

Large urban wildfires throughout southern California have caused billions of dollars of damage and significant loss of life over the last few decades. Rapid urban growth along the wildland interface, high fuel loads and a potential increase in the frequency of large fires due to climatic change suggest that the problem will worsen in the future. Improved fire spread prediction and reduced uncertainty in assessing fire hazard would be significant, both economically and socially. Current problems in the modeling of fire spread include the role of plant community differences, spatial heterogeneity in fuels and spatio-temporal changes in fuels. In this research, we evaluated the potential of Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Airborne Synthetic Aperture Radar (AIRSAR) data for providing improved maps of wildfire fuel properties. Analysis concentrated in two areas of Southern California, the Santa Monica Mountains and Santa Barbara Front Range. Wildfire fuel information can be divided into four basic categories: fuel type, fuel load (live green and woody biomass), fuel moisture and fuel condition (live vs senesced fuels). To map fuel type, AVIRIS data were used to map vegetation species using Multiple Endmember Spectral Mixture Analysis (MESMA) and Binary Decision Trees. Green live biomass and canopy moisture were mapped using AVIRIS through analysis of the 980 nm liquid water absorption feature and compared to alternate measures of moisture and field measurements. Woody biomass was mapped using L and P band cross polarimetric data acquired in 1998 and 1999. Fuel condition was mapped using spectral mixture analysis to map green vegetation (green leaves), nonphotosynthetic vegetation (NPV; stems, wood and litter), shade and soil. Summaries describing the potential of hyperspectral and SAR data for fuel mapping are provided by Roberts et al. and Dennison et al. To utilize remotely sensed data to assess fire hazard, fuel-type maps were translated into standard fuel models accessible to the FARSITE fire spread simulator. The FARSITE model and BEHAVE are considered industry standards for fire behavior analysis. Anderson level fuels map, generated using a binary decision tree classifier are available for multiple dates in the Santa Monica Mountains and at least one date for Santa Barbara. Fuel maps that will fill in the areas between Santa Barbara and the Santa Monica Mountains study sites are in progress, as part of a NASA Regional Earth Science Application Center, the Southern California Wildfire Hazard Center. Species-level maps, were supplied to fire managing agencies (Los Angeles County Fire, California Department of Forestry). Research results were published extensively in the refereed and non-refereed literature. Educational outreach included funding of several graduate students, undergraduate intern training and an article featured in the California Alliance for Minorities Program (CAMP) Quarterly Journal.

Roberts, Dar A.↗
NASA NTRS2022

Canadian and Alaskan Wildfire Smoke Particle Properties, Their Evolution and Controlling Factors, From Satellite Observations

The optical and chemical properties of biomass burning (BB) smoke particles greatly affect the impact that wildfires have on climate and air quality. Previous work has demonstrated some links between smoke properties and factors such as fuel type and meteorology. However, the factors controlling BB particle speciation at emission are not adequately understood nor are the factors driving particle aging during atmospheric transport. As such, modeling wildfire smoke impacts on climate and air quality remains challenging. The potential to provide robust, statistical characterizations of BB particles based on ecosystem type and ambient environmental conditions with remote sensing data is investigated here. Space-based Multi-angle Imaging SpectroRadiometer (MISR) observations, combined with the MISR Research Aerosol (RA) algorithm and the MISR Interactive Explorer (MINX) tool, are used to retrieve smoke plume aerosol optical depth (AOD) and to provide constraints on plume vertical extent; smoke age; and particle size, shape, light-absorption properties, and absorption spectral dependence. These tools are applied to numerous wildfire plumes in Canada and Alaska, across a range of conditions, to create a regional inventory of BB particle-type temporal and spatial distribution. We then statistically compare these results with satellite measurements of fire radiative power (FRP) and land cover characteristics, as well as short-term climate, meteorological, and drought information from the Modern-Era Retrospective analysis for Research and Applications (MERRA-2) reanalysis and the North American Drought Monitor. We find statistically significant differences in the retrieved smoke properties based on land cover type, with fires in forests producing the thickest plumes containing the largest, brightest particles and fires in savannas and grasslands exhibiting the opposite. Additionally, the inferred dominant aging mechanisms and the timescales over which they occur vary systematically between land types. This work demonstrates the potential of remote sensing to constrain BB particle properties and the mechanisms governing their evolution over entire ecosystems. It also begins to realize this potential, as a means of improving regional and global climate and air quality modeling in a rapidly changing world.

Katherine T. Junghenn Noyes↗
NASA NTRS2021

NASA ARMD Wildfire Management Workshop

In response to the increasing severity and cost of wildfires in the United States, the NASA Aeronautics Research Mission Directorate (ARMD) conducted a one-day Wildfire Management Workshop on May 13, 2021. The NASA Aeronautics Research Institute (NARI) at the NASA Ames Research Center organized the event. The goal of the workshop was to provide a forum for representatives from wildfire organizations (government, private, and academic) to raise important issues and discuss solutions. The proceedings consisted of presentations from the U.S. Forest Service, NASA Space Technology Mission Directorate, and NASA Applied Sciences Disasters Program. Also included were two sessions of breakout groups that focused on specific wildfire management issues. Some major themes that emerged from the breakout groups included data access and management, wildfire modeling, improving organizational collaboration, the use of aircraft in fighting fires and collecting data, and providing front line firefighters with the information tools they need to be effective. The output of the workshop will be used by ARMD to consider avenues that NASA might take to help with wildfire management.

Wildfire Management↗
NASA NTRS2021

NASA ARMD Wildfire Management Workshop

In response to the increasing severity and cost of wildfires in the United States, the NASA Aeronautics Research Mission Directorate (ARMD) conducted a one-day Wildfire Management Workshop on May 13, 2021. The NASA Aeronautics Research Institute (NARI) at the NASA Ames Research Center organized the event. The goal of the workshop was to provide a forum for representatives from wildfire organizations (government, private, and academic) to raise important issues and discuss solutions. The proceedings consisted of presentations from the U.S. Forest Service, NASA Space Technology Mission Directorate, and NASA Applied Sciences Disasters Program. Also included were two sessions of breakout groups that focused on specific wildfire management issues. Some major themes that emerged from the breakout groups included data access and management, wildfire modeling, improving organizational collaboration, the use of aircraft in fighting fires and collecting data, and providing front line firefighters with the information tools they need to be effective. The output of the workshop will be used by ARMD to consider avenues that NASA might take to help with wildfire management.

Parimal Kopardekar↗
NASA NTRS2021

NASA ARMD Wildfire Management Workshop

In response to the increasing severity and cost of wildfires in the United States, the NASA Aeronautics Research Mission Directorate (ARMD) conducted a one-day Wildfire Management Workshop on May 13, 2021. The NASA Aeronautics Research Institute (NARI) at the NASA Ames Research Center organized the event. The goal of the workshop was to provide a forum for representatives from wildfire organizations (government, private, and academic) to raise important issues and discuss solutions. The proceedings consisted of presentations from the U.S. Forest Service, NASA Space Technology Mission Directorate, and NASA Applied Sciences Disasters Program. Also included were two sessions of breakout groups that focused on specific wildfire management issues. Some major themes that emerged from the breakout groups included data access and management, wildfire modeling, improving organizational collaboration, the use of aircraft in fighting fires and collecting data, and providing front line firefighters with the information tools they need to be effective. The output of the workshop will be used by ARMD to consider avenues that NASA might take to help with wildfire management.

Wildfire↗
NASA NTRS2010

NASA Tech Briefs, November 2010

Topics covered include: Portable Handheld Optical Window Inspection Device; Salience Assignment for Multiple-Instance Data and Its Application to Crop Yield Prediction; Speech Acquisition and Automatic Speech Recognition for Integrated Spacesuit Audio Systems ; Predicting Long-Range Traversability from Short-Range Stereo-Derived Geometry; Browser-Based Application for Telemetry Monitoring of Robotic Assets; Miniature Low-Noise G-Band I-Q Receiver; Methods of Using a Magnetic Field Response Sensor Within Closed, Electrically Conductive Containers; Differential Resonant Ring YIG Tuned Oscillator; Microfabricated Segmented-Involute-Foil Regenerator for Stirling Engines; Reducing Seal Adhesion in Low Impact Docking Systems; Optimal Flow Control Design; Corrosion-Resistant Container for Molten-Material Processing; Reusable Hot-Wire Cable Cutter; Deployment of a Curved Truss; High-Volume Airborne Fluids Handling Technologies to Fight Wildfires; Modeling of Alkane Oxidation Using Constituents and Species; Fabrication of Lanthanum Telluride 14-1-11 Zintl High-Temperature Thermoelectric Couple; A Computer Model for Analyzing Volatile Removal Assembly; Analysis of Nozzle Jet Plume Effects on Sonic Boom Signature; Optical Sidebands Multiplier; Single Spatial-Mode Room-Temperature-Operated 3.0 to 3.4 micrometer Diode Lasers; Self-Nulling Beam Combiner Using No External Phase Inverter; Portable Dew Point Mass Spectrometry System for Real-Time Gas and Moisture Analysis; Maximum Likelihood Time-of-Arrival Estimation of Optical Pulses via Photon-Counting Photodetectors; Handheld White Light Interferometer for Measuring Defect Depth in Windows; Decomposition Algorithm for Global Reachability on a Time-Varying Graph; Autonomous GN and C for Spacecraft Exploration of Comets and Asteroids; Efficient Web Services Policy Combination; Using CTX Image Features to Predict HiRISE-Equivalent Rock Density; Isolation of the Paenibacillus phoenicis, a Spore-Forming Bacterium; Monolithically Integrated, Mechanically Resilient Carbon-Based Probes for Scanning Probe Microscopy; Cell Radiation Experiment System; Process to Produce Iron Nanoparticle Lunar Dust Simulant Composite; Inversion Method for Early Detection of ARES-1 Case Breach Failure; Use of ILTV Control Laws for LaNCETS Flight Research;and Evaluating Descent and Ascent Trajectories Near Non-Spherical Bodies.

Source record↗
NASA NTRS2020

SMARt-STEReO: Preliminary Model Description

Wildfires have increasingly become major threat to US towns and cities, with California alone having its most destructive wildfire seasons to date in 2017 and 2018 and 2020 already becoming one of the worst fire years on record, causing the large-scale evacuations, the destruction of towns and property, and a significant release of hazardous smoke over the entire west coast. Thus, the U.S. Forest Service recently spent over 50% of its budget on wildfire management – funds which could otherwise be directed to science that could support fire prevention. Aerial support plays a major role in fighting wildfires. Airtankers, helicopters, and other aerial assets support the construction of fire-lines, gather data, and transport crews and equipment. However, presently, aerial firefighting operations rely on relatively unsophisticated technologies for communications, such as over-the-air radios, which limit the ability of pilots and management to relay fire data and coordinate operations. Aerial operations in and around fires are additionally high-risk activities due to the variable, dangerous conditions and complex, technically difficult maneuvers which must be performed to, for example, conduct a retardant drop. Thus, between 2000 and 2013, of the 298 wildland firefighter fatalities, 26% were related to aerial operations. As a result, there is significant potential to both improve the performance and resiliency of wildfire response while reducing risk to human operators.

Daniel E Hulse↗
NASA NTRS2023

Marin County Wildfires Ii: Improving Fire Suppression Modeling to Inform Fire Prevention and Suppression Decisions in Marin County, Ca

A future of increased wildfires requires greater integration of spatial analysis and local knowledge of emergency responders. We examine the application of a Potential Operational Delineations (PODs) framework for strategic pre-fire planning in Marin County. PODs are spatial units for wildfire management that combine predictive modeling and local firefighter expertise to identify potential control locations as unit boundaries and assess the difficulty of suppression within units. Additionally, this project explores the integration of road networks and social vulnerability to assess environmental justice in evacuation safety. This project constitutes a novel application of the PODs framework as it integrates expertise from Marin County senior firefighters with a Fireline Location Model (FLM) to achieve POD definition and uses a Suppression Difficulty Score (SDS) to rank each POD. The FLM uses network analysis and hydrologic modeling to identify key roads and ridgelines as boundaries and combines them with expert knowledge, in the form of workshops, to construct PODs. Once identified, PODs are classified using SDS, which includes processed inputs such as LiDAR-derived aboveground biomass, ECOSTRESS Evaporative Stress Index, land use cover type from Sentinel-2 Imagery, and a digital elevation model. Environmental justice for evacuation safety incorporated three key road metrics such as connectivity, travel area, and exit capacity, the Social Vulnerability Index from the Center for Disease Control, and cell coverage to determine a final Evacuation Difficulty Score. Results indicate a strong link between road networks as primary POD boundaries, with ridgelines and waterways as secondary and tertiary locations. Specifically, we find 78.5% of expertise-identified POD boundaries align with FLM-determined boundaries. More validation is needed to support this process; however, initial results signal a feasible framework to integrate expertise and spatial analysis in local level strategic fire planning

Wildfire modeling↗
NASA NTRS2022

Idaho Wildfires II: Assessing the Relationship Between Drought Indicators and Wildfire Risk to Enhance Hazard Modeling and Inform Mitigation Planning

The western United States has experienced twenty years of increased and prolonged drought which have exacerbated wildfire hazards. These jeopardize population centers through increased risks to ecosystem services, local economies, and livelihoods. The Idaho Office of Emergency Management, Water Resources, and Department of Lands are seeking methods to dynamically monitor these conditions and update models that inform hazard mitigation planning and resource allocation. Towards this, these agencies partnered with NASA DEVELOP to produce drought-enhanced wildfire hazard models. Part of a two-term project, the two teams revised the state’s static wildfire hazard model with refined data layers and remotely-sensed data to reflect dynamic ecosystem responses to drought conditions and wildfire potential. Our team distinguished between rangeland and forestland ecosystems, and investigated relationships between drought metrics and vegetation condition using TerrSet Earth Trends Modeler. This analysis determined that total precipitation at a 5-month lag interval (r 2 = 0.72) along with the Evaporative Stress Index (r 2 = 0.69); and precipitation at a 5-month interval (r 2 = 0.42) were important drivers in rangeland and forestland, respectively. These driver variables were incorporated into a temporally dynamic wildfire hazard map. Our team used linear regression to correlate hazard ratings with wildfire frequency. For the year 2020, neither the enhanced hazard model (p < 0.10, r 2 = 0.01) nor the state’s static model (p < 0.05, r 2 = 0.03) were strongly correlated with actual wildfire frequency as they expressed an inverse relationship between wildfire hazard and frequency. This suggests wildfire occurrence is complex and not necessarily driven by the variables used.

Wildfire↗
NASA NTRS2021

Evaluation and Intercomparison of Wildfire Smoke Forecasts from Multiple Modeling Systems for the 2019 Williams Flats Fire

Wildfire smoke is one of the most significant concerns of human and environmental health, associated with its substantial impacts on air quality, weather, and climate. However, biomass burning emissions and smoke remain among the largest sources of uncertainties in air quality forecasts. In this study, we evaluate the smoke emissions and plume forecasts from 12 state-of-the-art air quality forecasting systems during the Williams Flats fire in Washington State, US, August 2019, which was intensively observed during the Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) field campaign. Model forecasts with lead times within 1 d are intercompared under the same framework based on observations from multiple platforms to reveal their performance regarding fire emissions, aerosol optical depth (AOD), surface PM2.5, plume injection, and surface PM2.5 to AOD ratio. The comparison of smoke organic carbon (OC) emissions suggests a large range of daily totals among the models, with a factor of 20 to 50. Limited representations of the diurnal patterns and day-to-day variations of emissions highlight the need to incorporate new methodologies to predict the temporal evolution and reduce uncertainty of smoke emission estimates. The evaluation of smoke AOD (sAOD) forecasts suggests overall underpredictions in both the magnitude and smoke plume area for nearly all models, although the high-resolution models have a better representation of the fine-scale structures of smoke plumes. The models driven by fire radiative power (FRP)-based fire emissions or assimilating satellite AOD data generally outperform the others. Additionally, limitations of the persistence assumption used when predicting smoke emissions are revealed by substantial underpredictions of sAOD on 8 August 2019, mainly over the transported smoke plumes, owing to the underestimated emissions on 7 August. In contrast, the surface smoke PM2.5 (sPM2.5) forecasts show both positive and negative overall biases for these models, with most members presenting more considerable diurnal variations of sPM2.5. Overpredictions of sPM2.5 are found for the models driven by FRP-based emissions during nighttime, suggesting the necessity to improve vertical emission allocation within and above the planetary boundary layer (PBL). Smoke injection heights are further evaluated using the NASA Langley Research Center's Differential Absorption High Spectral Resolution Lidar (DIAL-HSRL) data collected during the flight observations. As the fire became stronger over 3–8 August, the plume height became deeper, with a day-to-day range of about 2–9 km a.g.l. However, narrower ranges are found for all models, with a tendency of overpredicting the plume heights for the shallower injection transects and underpredicting for the days showing deeper injections. The misrepresented plume injection heights lead to inaccurate vertical plume allocations along the transects corresponding to transported smoke that is 1 d old. Discrepancies in model performance for surface PM2.5 and AOD are further suggested by the evaluation of their ratio, which cannot be compensated for by solely adjusting the smoke emissions but are more attributable to model representations of plume injections, besides other possible factors including the evolution of PBL depths and aerosol optical property assumptions. By consolidating multiple forecast systems, these results provide strategic insight on pathways to improve smoke forecasts.

AOD↗
NASA NTRS1974

An analysis of wildfire prevention

A model of the production of wildfire ignitions and damages is developed and used to determine wildland activity-regulation decisions, which minimize total expected cost-plus-loss due to wildfires. In this context, the implications of various policy decisions are considered. The resulting decision rules take a form that makes it possible for existing wildfire management agencies to readily adopt them upon collection of the required data.

Heineke, J. M.↗
NASA NTRS2022

Chile Disasters: Automating Wildfire Risk and Occurrence Mapping in Google Earth Engine to Improve Wildfire Detection and Response Time Efforts

Wildfires in Chile in the last decade were the worst on record, destroying homes and livelihoods, polluting the air, and displacing whole towns. To predict locations where wildfires were likely to start, the Corporación Nacional Forestal (CONAF) created a wildfire risk model within ArcGIS Pro and Google Earth Engine (GEE) that utilized the NOAA Global Forecast System (GFS) and the NASA Shuttle Radar Topography Mission (STRM) 90-meter datasets. The previous CONAF model was very resource-heavy and time-intensive to run. NASA DEVELOP, in partnership with CONAF, automated the previous model and transferred it fully into GEE where all Earth observation datasets could be used without downloading. The new model substantially reduced the runtime. The final model was used to create a near real-time wildfire monitoring application as well as fire severity maps. The end products will be used by CONAF for wildfire prediction and management to prevent more destruction in the future.

Maria De Los Santos↗