The California Fire Science Seminar Series will return on February 6, 2024, at 2 pm. Join us for the biweekly, virtual presentation and discussion on emerging fire science topics from a diverse range of topics and speakers. Sign up for the California Fire Science Seminar Series newsletter below to receive updates.
2024 Seminar Series Schedule
Seminars will be held every other Tuesday from 2pm to 3pm.
View flyer here!
February 6th, 2024: Physics-Based Modeling of Fire Spread in Densely-Built Urban Areas - Some Implications to the Modeling of Fire Spread in WUI Fires
February 20th, 2024: AI-Enabled Wildfire Detection Using Satellite Imagery
March 5th, 2024: The Role of Economics in Wildfire Risk Management
March 19th, 2024: Reforestation for Resilience: Creating Fire-Adapted Forests for the Future
April 2nd, 2024: California’s Prescribed Fire (R)evolution: Changing Hearts, Minds, and Landscapes
April 16th, 2024: Victims or Survivors? The Cost of Culture in Fire Recovery
April 30th, 2024: Towards Advancing the Prediction of Wildland Fuels Combustion through Detailed Kinetics
BONUS WEBINAR:
May 15th, 2024: Developing a Practical Physical Wildfire Behavior Model
Bonus Webinar
Developing a Practical Physical Wildfire Behavior Model
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Date: Wednesday, May 15th, 2024
Abstract: Wildland fire behavior prediction relies upon empirical modeling that has been operationalized for many decades. Although research has yielded many possible physical models, none have yet been seriously considered as replacements for operational uses. The reasons include incomplete physical understanding, overly complicated or intensive solutions given the practical client needs, and lack of input data. Long-standing research at the Missoula Fire Sciences Laboratory has sought to develop the basic understanding of physical processes in wildland fire using laboratory and field research and match the knowledge generated to a model formulation that would advance predictive capability but not burden users with undue complexity or computational requirements. This talk will overview the experimental work and modeling results.
Presenter: Mark A. Finney is a Senior Scientist and Research Forester with the US Forest Service, Rocky Mountain Research Station, Missoula Fire Sciences Laboratory. He has devoted his career to understanding fire as an ecological and physical process and has conducted research on prescribed burning and fuel treatment effects across the western United States. His wildfire modeling forms basis for operational wildfire predictions throughout the US. He holds a Ph.D. in wildland fire science from Univ. California at Berkeley (1991), an M.S. in Fire Ecology from University of Washington (1986), and a B.S. in Forestry from Colorado State University (1984).
Past Seminars
Physics-Based Modeling of Fire Spread in Densely-Built Urban Areas - Some Implications to the Modeling of Fire Spread in WUI Fires
View the recording here!
Date: February 6, 2024
Abstract: Urban fires pose a persistent hazard in Japanese urban areas. To address this, various fire spread models have been developed, with many relying on empirical formulations. However, to enhance model generality, a shift towards physics-based formulations is explored. Yet, computational methods like CFD, grounded in fundamental physics equations, are computationally demanding and face limitations in large-scale applications like urban fires. This necessitates the development of models effectively incorporating less computationally demanding procedures, such as engineering correlations based on experiments. In this seminar, a fire spread model developed under such constraints will be presented. While urban fires are rare outside Japan, the fire spread mechanisms in urban areas share commonalities with WUI fires. Therefore, the framework of the fire spread model for urban fires is applicable to WUI fires.
Presenter: Keisuke Himoto, Dr.Eng., is a senior researcher at the National Institute for Land and Infrastructure Management in Tsukuba, Japan. His research interests cover a broad range of fire safety issues in the built environment but with a special focus on large outdoor fires. He is the developer of various fire-related computational models, including one of the first physics-based computational models for fire spread in densely built urban areas.
AI-Enabled Wildfire Detection Using Satellite Imagery
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Date: February 20, 2024
Abstract: Wildfires in California have grown in size and intensity since the 1980s, causing significant damage to the environment and human communities. Our study is focused on developing a deep-learning framework for detecting and monitoring wildfires using satellite imagery. Utilizing the Sentinel-2 satellite, we harnessed multispectral data across various bands with resolutions ranging from 10m to 60m. Specifically, bands 12 (SWIR, 2190 nm), 11 (SWIR, 1610 nm), and 4 (Red, 665 nm) were critical in our analysis due to their sensitivity to high temperatures and their ability to penetrate smoke, providing spectral information even through dense smoke that could obscure traditional RGB imaging. Our methodology involved the creation of a large-scale dataset downloaded through Google Earth Engine, comprising over 50 high-resolution images (1792x1792 pixels), which were further divided into 2450 smaller images for enhanced model training efficiency. Label Studio was employed for fire segmentation to produce accurate masks for our U-Net-based segmentation model. Data augmentation techniques were applied to triple our dataset, yielding 7350 images. About 65% of images were allocated for training, 15% for validation, and 20% for model testing. We trained a U-Net deep learning model, known for its effectiveness in image segmentation with multiple convolutional layers, dropout layers, and max pooling layers, totaling 1,941,105 trainable parameters. Training over 100 epochs demonstrated consistent model accuracy and minimal loss. Key performance metrics include an accuracy of 98.47%, precision of 90.76%, recall of 80.47%, and an F-score of 85.31%. The success of this approach demonstrates the compelling capabilities of combining advanced deep learning techniques with multispectral satellite imagery for effective wildfire monitoring, offering an invaluable tool for disaster management and environmental conservation.
Keywords: Wildfire Detection, Satellite Imagery, Sentinel-2 Satellite, Deep Learning, U-Net, Image Segmentation
Presenter: Dr. Ali Moghimi is an Assistant Professor of Teaching in the Department of Biological and Agricultural Engineering, where he is the lead faculty advisor for the Agricultural and Environmental Technology major. Ali teaches a wide range of courses, including, TAE 10 (introduction to Technology), TAE 30 (communications and Computing Technology), ABT 60 (introduction to drone technology), ABT/LDA 150 (introduction to geographical information systems – GIS), and ABT/HYD 182 (Environmental Analysis using GIS). Ali’s research interests include remote sensing, GIS, and applied machine learning and deep learning.
The Role of Economics in Wildfire Risk Management
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Date: March 5, 2023
Abstract: Despite the growing impacts, interest and investment in wildfire traditional economic tools such as cost modeling, cost benefit analysis, and cost effectiveness have played a relatively limited role in informing wildfire management. High levels of uncertainty associated with a dynamic fire environment, variation in fire weather across space and time, disagreement around priorities and values that are impacted by wildfire, and the design and culture of organizations charged with implementing wildfire management make risk management a more appropriate framework for implementing and understanding wildfire management decision making. This is not to suggest that economics is not important, it plays a critical role in informing many aspects of the risk management cycle. In this presentation, I will discuss some of the challenges applying economics and highlight some of the key concepts that are helping us better understand the challenges and opportunities of wildfire management.
Presenter: Dave Calkin is a supervisory research forester at the Human Dimensions Program of the US Forest Service Rocky Mountain Research Station in Missoula, Montana. He co-leads the Wildfire Risk Management Science team (https://www.fs.fed.us/rmrs/groups/wildfire-risk-management-team) working to improve risk based fire management decision making through improved science development, application, and delivery. His research incorporates economics with risk and decision sciences to explore ways to evaluate and improve the efficiency and effectiveness of wildfire management programs.
In 2023 Dave received the Ember Award from the International Association of Wildland Fire for sustained achievement in wildfire research. He received a BS in applied math from the University of Virginia, an MS in natural resources conservation from the University of Montana, and a PhD in Economics from Oregon State University.
His Google Scholar profile is available at: http://scholar.google.com/citationsuser=pswd8h4AAAAJ&hl=en
Reforestation for Resilience: Creating Fire-Adapted Forests for the Future
View the recording here!
Date: March 19, 2024
Abstract: Wildfires are becoming an increasing issue, raising concern about direct infrastructure and property damage as well as indirect effects related to their emissions. In this context, a fundamental understanding of the burning processes of wildland fuels is crucial for the modeling and prediction of both fire behavior as well as related emissions. Current fuel consumption parameterizations used in wildfire models usually oversimplify fuel consumption processes, such as flaming and smoldering combustion regimes, and fuel properties, like fuel elements' size and moisture content. In this seminar, a physics-based modeling framework developed to describe biomass combustion and emissions will be presented. Biomass is represented through its fundamental constituents, such as lignin, cellulose, hemicellulose, water, and extractives. A detailed reaction kinetic model is coupled with a multi-region single-particle model and is adopted to investigate the process of biomass degradation, including char oxidation. The validation of the modeling framework with experimental data from literature is performed at various scales, including thermogravimetric experiments and particle-scale experiments of pyrolysis and combustion. Additionally, preliminary results of its applicability for the construction of detailed parameterizations for large-scale wildfire applications, such as WRF-SFIRE coupled atmosphere-fire model, will be discussed.
Presenters: Malcolm North is a Research Forest Ecologist with the U.S. Forest Service Pacific Southwest Research Station, and an Affiliate Professor of Forest Ecology, Department of Plant Sciences at the University of California, Davis. He received his Master of Forest Science at Yale University and his PhD in Forest Ecology from the University of Washington. His research includes work on examining forest restoration and ecosystem response, wildlife, wildfire and forest carbon dynamics published in more than 200 articles. His lab (students and postdocs) primarily focus on forest and fire ecology of Sierra Nevada mixed-conifer forests.
Marc Meyer is the Southern Sierra Province Ecologist with the USDA Forest Service Pacific Southwest Regional Ecology Program and serves the Inyo, Sierra, and Sequoia National Forests. His work focuses on integrating science information into land management and project planning in the southern Sierra Nevada. Marc has a Ph.D. in ecology from the University of California Davis and has many years of experience studying the effects of fire and other restoration treatments on California’s ecosystems. He has published many peer-reviewed science articles in ecology, including the GTR-270 postfire restoration framework for national forests in California.
California’s Prescribed Fire (R)evolution: Changing Hearts, Minds, and Landscapes
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Date: April 2, 2024
Abstract: Prescribed fire has undergone major transformation in California over the last decade or two, evolving from a mostly agency-led practice with limited visibility to a statewide grassroots movement, engaging and being led by a diversity of partners, including NGOs, ranchers, Indigenous practitioners, and other community leaders. This movement has been simultaneously organic, bubbling up at the local level, and impressively strategic, pairing local community organizing with state-level liability changes, new qualifications pathways for practitioners, and major investments in cutting-edge concepts, like the state’s $20 million Prescribed Fire Claims Fund. The change during this period has been monumental, representing an evolution in the way we think about and implement prescribed fire in California, but it also represents a revolution—the result of a groundswell of passion, purpose, and pressure from the most affected communities. This presentation will share insights on California’s prescribed fire evolution/revolution, and reflect on where it might go from here.
Presenter: Lenya Quinn-Davidson is the Fire Network Director for the University of California Agriculture and Natural Resources. Lenya’s focus is on the human connection with fire, and increasing resiliency of California’s landscapes and communities. Lenya works at various scales, including locally with private landowners and communities members; at the state level, where she leads UCANR’s Fire Network and collaborates on policy, research, and community-based burning; and nationally/internationally, through her leadership on Women-in-Fire Training Exchanges (WTREX). Lenya is passionate about using fire to inspire and empower people, from ranchers and scientists to agency leaders and young women, and everyone in between.
Victims or Survivors? The Cost of Culture in Fire Recovery
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Date: April 16, 2024
Abstract: As fire disasters in California increase in severity and frequency, the costs accumulate for federal, state, and local governments, insurers, residents, and communities. While the costs of wildfires are difficult to quantify, the 2018 Carr fire in Shasta County, CA resulted in costly evacuations of approximately 38,000 people, the ecosystem loss of 229,651 acres, destruction of 1,077 homes and the generational equity represented therein, $162 million in firefighting costs, and an estimated $1.6 billion in damages. At the time, this was the sixth largest fire in California history and necessitated a coordinated recovery response by government agencies and nongovernmental groups. This seminar presentation draws on extensive qualitative data – 134 in-depth interviews and six months of ethnographic observation with Carr fire recovery organizations – to document mechanisms by which the costs of this disaster are borne unequally by residents. I demonstrate how local and visiting aid workers’ normative assumptions about legitimate victimhood structure survivors’ access to resources and produce inequalities in disaster recovery. I conclude with a discussion of how gender, race, and age intersect with socioeconomic class in the production of disaster recovery inequalities. As climate disasters become increasingly prevalent worldwide, it is imperative that ecologists, fire management agencies, social service providers, health professionals, and social scientists study the processes that produce unequal disaster recovery outcomes and propose interventions that can mitigate these disparities.
Presenter: Rebecca Ewert is an Assistant Professor of Instruction in Sociology at Northwestern University. Her research interests include mental health, disasters, culture, inequality, and qualitative methods. Her work explores how people of different social groups (classes, genders, ages, and races) recover economically, socially, and emotionally from disasters. More about her work can be found on her website: www.rebeccaewert.com.
Towards Advancing the Prediction of Wildland Fuels Combustion through Detailed Kinetics
View the recording here!
Date: April 30, 2024
Abstract: Wildfires are becoming an increasing issue, raising concern about direct infrastructure and property damage as well as indirect effects related to their emissions. In this context, a fundamental understanding of the burning processes of wildland fuels is crucial for the modeling and prediction of both fire behavior as well as related emissions. Current fuel consumption parameterizations used in wildfire models usually oversimplify fuel consumption processes, such as flaming and smoldering combustion regimes, and fuel properties, like fuel elements' size and moisture content. In this seminar, a physics-based modeling framework developed to describe biomass combustion and emissions will be presented. Biomass is represented through its fundamental constituents, such as lignin, cellulose, hemicellulose, water, and extractives. A detailed reaction kinetic model is coupled with a multi-region single-particle model and is adopted to investigate the process of biomass degradation, including char oxidation. The validation of the modeling framework with experimental data from literature is performed at various scales, including thermogravimetric experiments and particle-scale experiments of pyrolysis and combustion. Additionally, preliminary results of its applicability for the construction of detailed parameterizations for large-scale wildfire applications, such as WRF-SFIRE coupled atmosphere-fire model, will be discussed.
Presenter: Chiara Saggese received her PhD in Industrial Chemistry and Chemical Engineering from Politecnico of Milan in 2015. After working as a postdoctoral fellow on experiments and kinetic modeling of real fuel combustion chemistry and emissions at Stanford University, she joined the Reaction Dynamics Group in Lawrence Livermore National Laboratory in 2019. Her research activity spans from the development of kinetic models of conventional and sustainable fuels to the kinetic modeling of pollutants formation in combustion processes. Within the current transition to a decarbonized transportation system, she is focusing on modeling soot formation from sustainable aviation fuels. Lately, her research focus has expanded to the investigation of wildland fuels combustion and emissions to inform sub-models present in large-scale wildfire applications.
Recordings of presentations are available here: 2024 California Fire Science Seminar Series - YouTube
Recordings of past presentations are available here: CA Fire Science Seminar Series - YouTube
The California Fire Science Seminar Series is organized and supported by the Berkeley Fire Research Group, College of Engineering, University of California, Berkeley; the University of California, Merced and the California Fire Science Consortium. The planning committee includes Michael Gollner (UC Berkeley), Crystal Kolden (UC Merced), Jeanette Cobain (UC Merced), Scott Stephens (UC Berkeley), Autym Shafer (UC Berkeley), and Katanja Waldner (UC Berkeley). The student committee who assisted with planning includes Ajinkya Desai (UC Irvine), Andrew Johnson (UC Berkeley), Ankit Sharma (Case Western Reserve), Ashkan Teymouri (UC Davis), Ashley Cale (UN Reno), Ashley Duran (UC Berkeley), Caden Chamberlain (UW), Dylan Moore (UC Davis), Elena Kaminskaia (UC Riverside), Joyce Ho (UMich), Katrina Sharonin (UC Berkeley), Monica Antonio (UC Berkeley), Nathaniel Brockway (UAF), Nick Graver (UC Riverside), Nitin Kumar (UC Davis), Shaorun Lin (UC Berkeley), Shu Li (UC Irvine), Trevor Haltermann (Cal Poly Humboldt), Yiren Qin (UMD).
