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Using Deep Learning to Predict Yearly Wildfire Potential from Antecedent Land Surface and Meteorological DataNo abstract available
Document ID
20190033953
Acquisition Source
Marshall Space Flight Center
Document Type
Presentation
Authors
White, Andrew T. (Alabama Univ. Huntsville, AL, United States)
Hain, Christopher R. (NASA Marshall Space Flight Center Huntsville, AL, United States)
Schultz, Christopher J. (NASA Marshall Space Flight Center Huntsville, AL, United States)
Case, Jonathan L. (ENSCO, Inc. Vandenberg AFB, CA, United States)
White, Kris (NWS Prototyping Aviation Collaborative Effort (PACE) Fort Worth, TX, United States)
Date Acquired
December 13, 2019
Publication Date
December 9, 2019
Subject Category
Earth Resources And Remote Sensing
Meteorology And Climatology
Report/Patent Number
MSFC-E-DAA-TN75915
Report Number: MSFC-E-DAA-TN75915
Meeting Information
Meeting: AGU Fall Meeting 2019
Location: San Francisco, CA
Country: United States
Start Date: December 9, 2019
End Date: December 13, 2019
Sponsors: American Geophysical Union (AGU)
Funding Number(s)
CONTRACT_GRANT: NNM17AA29T
CONTRACT_GRANT: NNM11AA01A
Distribution Limits
Public
Copyright
Public Use Permitted.

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