Prediction of High-Resolution Atmospheric CO2 Concentration from OCO-2 using Machine Learning

Author:

Pais Spurthy Maria1ORCID,Bhattacharjee Shrutilipi1ORCID,Madasamy Anand Kumar1ORCID

Affiliation:

1. Department of Information Technology, National Institute of Technology Karnataka, India

Publisher

ACM

Reference29 articles.

1. [Online]. OCO-2 Lite Level-2 Version 9r Data. Retrieved November 22, 2022 from https://urs.earthdata.nasa.gov/ [Online]. OCO-2 Lite Level-2 Version 9r Data. Retrieved November 22, 2022 from https://urs.earthdata.nasa.gov/

2. Interpretation of nonlinear relationships between process variables by use of random forests

3. Prediction of Satellite-Based Column CO2 Concentration by Combining Emission Inventory and LULC Information

4. David Crisp . 2015. Measuring atmospheric carbon dioxide from space with the Orbiting Carbon Observatory-2 (OCO-2) . In Earth observing systems xx, Vol. 9607 . SPIE , 960702. David Crisp. 2015. Measuring atmospheric carbon dioxide from space with the Orbiting Carbon Observatory-2 (OCO-2). In Earth observing systems xx, Vol. 9607. SPIE, 960702.

5. Michele Fratello and Roberto Tagliaferri . 2019. Decision Trees and Random Forests . In Encyclopedia of Bioinformatics and Computational Biology - Volume 1 , Shoba Ranganathan, Michael Gribskov , Kenta Nakai, and Christian Schönbach (Eds.). Elsevier , 374–383. https://doi.org/10.1016/b978-0-12-809633-8. 2033 7-3 10.1016/b978-0-12-809633-8.20337-3 Michele Fratello and Roberto Tagliaferri. 2019. Decision Trees and Random Forests. In Encyclopedia of Bioinformatics and Computational Biology - Volume 1, Shoba Ranganathan, Michael Gribskov, Kenta Nakai, and Christian Schönbach (Eds.). Elsevier, 374–383. https://doi.org/10.1016/b978-0-12-809633-8.20337-3

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