Deep Neural Networks For Evaluating Future Satellite-Based Hyperspectral Microwave Sensor Designs-Reference-Cited by-同舟云学术

Deep Neural Networks For Evaluating Future Satellite-Based Hyperspectral Microwave Sensor Designs

Published:2023-07-16 Issue: Volume: Page:
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Container-title:IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium
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Author:

MacKinnon James¹,Gambacorta Antonia¹,Piepmeier Jeffrey¹,Stephen Mark¹,Kroodsma Rachael²,Santanello Joseph¹,Blumberg Greg³,Blaisdell John⁴,Moradi Isaac²,Gong Jie⁵,Kotsakis Alexander⁵,Adams Ian¹

Affiliation:

1. NASA Goddard Space Flight Center (GSFC),Greenbelt,MD,20771

2. University of Maryland,College Park,MD,20740

3. Millersville University,Millersville,PA,17551

4. Science Applications International Corporation (SAIC),Reston,VA,20190

5. ERT, Inc.,Laurel,MD,20707

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10281394/10281399/10282220.pdf?arnumber=10282220

Reference8 articles.

1. The Hyperspectral Microwave Photonic Instrument (HYMPI)

2. The Hyperspectral Microwave Photonic Instrument (HYMPI) - Advancing our Understanding of the Earth's Planetary Boundary Layer from Space

3. Advancing Atmospheric Thermodynamic Sounding From Space Using Hyperspectral Microwave Measurements

4. Evaluation of the 7-km GEOS-5 Nature Run;Gelaro;Technical Report Series on Global Modeling and Data Assimilation,2014

5. Community radiative transfer model for radiance assimilation and applications

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