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Marin County Wildland Fires: Examining Fuel Load and Land Cover Change to Inform Fire Prevention and Suppression Decisions in Marin County, CAHeightened occurrence of severe wildfires in the Western United States is increasing the need to better understand regions of high potential wildfire severity and develop methodologies for identifying the best locations for fuels reduction and active wildfire suppression, especially in populated regions such as Marin County, California. Marin County, located in the San Francisco Bay Area, has had significant development in the wildland-urban interface and periods of highly wildfire-prone conditions. The NASA DEVELOP team collaborated with Fire Foundry (a Marin-based fire service workforce development program) and the Marin County Fire Department to develop models to assist with fire management. Using data from Sentinel-2A, PlanetScope, ECOSTRESS, a county-wide LiDAR mapping effort, Landsat 7 Enhanced Thematic Mapper (ETM+), and Landsat 8 Operational Land Imager (OLI), our team developed a number of input data layers for three different models to evaluate wildfire severity. One model performed a suitability analysis with weights based on scientific literature; another model utilized a U-Net Convolutional Neural Network trained on previous fires in Marin and neighboring Sonoma County to predict the difference normalized burn severity; and the third inputted data layers into the FlamMap tool that outputs risk categories. We compared model outputs and performed a weighted overlay analysis to identify specific locations where a fireline could be constructed to interrupt the progress of an active fire. These tools will assist partners in preparing for and managing active wildfire situations.
Document ID
20230006640
Acquisition Source
Langley Research Center
Document Type
Other - DEVELOP Technical Report
Authors
Suhani Dalal
(Science Systems and Applications (United States) Lanham, Maryland, United States)
Katera Lee
(Science Systems and Applications (United States) Lanham, Maryland, United States)
Gabriel Rosenstein
(Science Systems and Applications (United States) Lanham, Maryland, United States)
Chandler Ross
(Science Systems and Applications (United States) Lanham, Maryland, United States)
Date Acquired
May 1, 2023
Publication Date
March 30, 2023
Subject Category
Earth Resources and Remote Sensing
Meeting Information
Meeting: DEVELOP Spring Term Meeting
Location: Virtual
Country: US
Start Date: March 30, 2023
Sponsors: National Aeronautics and Space Administration
Funding Number(s)
CONTRACT_GRANT: NNL16AA05C
WBS: 970315.02.02.01.08
Distribution Limits
Public
Copyright
Use by or on behalf of the US Gov. Permitted.
Technical Review
Professional Review
Keywords
Remote sensing
Sentinel-2
machine learning
fireline
fire severity
Landsat
FlamMap
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