A Data Fusion Framework to Gap Fill and Improve Satellite-based Evapotranspiration: Integrating Eddy Covariance and CubeSat Observations with Machine Learning
- DOI
- 10.5281/zenodo.20836508
- Published
- 2026
- Container
- Not recorded
- Publisher
- Zenodo
- Open access
- yes
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BibTeX
@article{allodium:10.5281/zenodo.20836508,
title = {A Data Fusion Framework to Gap Fill and Improve Satellite-based Evapotranspiration: Integrating Eddy Covariance and CubeSat Observations with Machine Learning},
author = {Akbar, Muhammad Umar and Mirchi, Ali and Wagle, Pradeep and Mansaray, Abubakarr and Pandey, Mamata and Saasan, Navdeep Kaur},
year = {2026},
doi = {10.5281/zenodo.20836508},
url = {https://doi.org/10.5281/zenodo.20836508}
}RIS
TY - JOUR TI - A Data Fusion Framework to Gap Fill and Improve Satellite-based Evapotranspiration: Integrating Eddy Covariance and CubeSat Observations with Machine Learning AU - Akbar, Muhammad Umar AU - Mirchi, Ali AU - Wagle, Pradeep AU - Mansaray, Abubakarr AU - Pandey, Mamata AU - Saasan, Navdeep Kaur PY - 2026 DO - 10.5281/zenodo.20836508 UR - https://doi.org/10.5281/zenodo.20836508 ER -
APA
Umar, A. M., Ali, M., Pradeep, W., Abubakarr, M., Mamata, P., & Kaur, S. N. (2026). A Data Fusion Framework to Gap Fill and Improve Satellite-based Evapotranspiration: Integrating Eddy Covariance and CubeSat Observations with Machine Learning. https://doi.org/10.5281/zenodo.20836508