Inferring Carbon Dioxide Emissions From Power Plants Using Satellite Imagery and Machine Learning-Reference-Cited by-同舟云学术

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Inferring Carbon Dioxide Emissions From Power Plants Using Satellite Imagery and Machine Learning

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:

Hobbs Madison¹,Kargar Ali Rouzbeh¹,Couture Heather¹,Freeman Jeremy¹,Söldner-Rembold Isabella²,Ferreira André²,Jeyaratnam Jeyavinoth¹,O’Connor Joseph²,Lewis Jordan¹,Koenig Hannes¹,McCormick Colin¹,Nakano Tiffany³,Dalisay Charmaine³,Davitt Aaron¹,Gans Lee¹,Lewis Christy¹,Volpato Gabriela¹,Gray Matthew²,McCormick Gavin¹

Affiliation:

1. WattTime

2. TransitionZero

3. Global Energy Monitor

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10281394/10281399/10283046.pdf?arnumber=10283046

Reference11 articles.

1. Power sector: electricity generation;freeman;Climate TRACE,2022

2. Quantifying CO 2 Emissions From Individual Power Plants From Space

3. Towards tracking the emissions of every power plant on the planet;couture;NeurIPS Workshop Tackling Climate Change with Machine Learning,2020

4. Quantifying Global Power Plant Carbon Dioxide Emissions With Imaging Spectroscopy

5. A methodology to constrain carbon dioxide emissions from coal-fired power plants using satellite observations of co-emitted nitrogen dioxide

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