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Time Series Machine Learning Methods for Surface PM2.5 Estimations Using Geostationary Satellites and Numerical Weather Models
Document ID
20220000473
Acquisition Source
Marshall Space Flight Center
Document Type
Presentation
Authors
George Priftis
(University of Alabama in Huntsville Huntsville, Alabama, United States)
Aaron Kaulfus
(Marshall Space Flight Center Redstone Arsenal, Alabama, United States)
Muthukumaran Ramasubramanian
(University of Alabama in Huntsville Huntsville, Alabama, United States)
Shubhankar Gahlot
(University of Alabama in Huntsville Huntsville, Alabama, United States)
Iksha Gurung
(University of Alabama in Huntsville Huntsville, Alabama, United States)
Manisha Khatri
(University of Alabama in Huntsville Huntsville, Alabama, United States)
Peiyang Chaeng
(University of Alabama in Huntsville Huntsville, Alabama, United States)
Manil Maskey
(Marshall Space Flight Center Redstone Arsenal, Alabama, United States)
Rahul Ramachandran
(Marshall Space Flight Center Redstone Arsenal, Alabama, United States)
Sundar Christopher
(University of Alabama in Huntsville Huntsville, Alabama, United States)
Haeyong Chung
(University of Alabama in Huntsville Huntsville, Alabama, United States)
Date Acquired
January 24, 2022
Subject Category
Earth Resources And Remote Sensing
Meteorology And Climatology
Meeting Information
Meeting: 102nd American Meteorological Society Annual Meeting/21st Conference on Artificial Intelligence for Environmental Science
Location: Virtual
Country: US
Start Date: January 24, 2022
End Date: January 28, 2022
Sponsors: American Meteorological Society
Funding Number(s)
CONTRACT_GRANT: NNM11AA01A
Distribution Limits
Public
Copyright
Use by or on behalf of the US Gov. Permitted.
Technical Review
Single Expert
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