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A Deep Learning Approach for Surface PM2.5 Estimations from Geostationary Satellite and Numerical Model Data
Document ID
20205009933
Acquisition Source
Marshall Space Flight Center
Document Type
Poster
Authors
Manisha Khatri (University of Alabama in Huntsville Huntsville, Alabama, United States)
Muthukumaran Ramasubramanian (University of Alabama in Huntsville Huntsville, Alabama, United States)
Iksha Gurung (University of Alabama in Huntsville Huntsville, Alabama, United States)
Aaron S Kaulfus (University of Alabama in Huntsville Huntsville, Alabama, United States)
Georgios Priftis (University of Alabama in Huntsville Huntsville, Alabama, United States)
Peiyang Cheng (University of Alabama in Huntsville Huntsville, Alabama, United States)
Pawan Gupta (Universities Space Research Association Columbia, Maryland, 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
November 10, 2020
Subject Category
Earth Resources And Remote Sensing
Meeting Information
Meeting: AGU Fall 2020
Location: Virtual
Country: US
Start Date: December 1, 2020
End Date: December 17, 2020
Sponsors: American Geophysical Union
Funding Number(s)
CONTRACT_GRANT: NNM11AA01A
Distribution Limits
Public
Copyright
Public Use Permitted.
Technical Review
Single Expert

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