Prediction of Soil Moisture From Near-Global Cygnss Gnss-Reflectometry Using a Random Forest Machine Learning Model. Wilson, M., Datta, R., Savarimuthu, S., Moller, D., & Ruf, C. In IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, pages 4465–4471, Athens, Greece, July, 2024. IEEE.
Prediction of Soil Moisture From Near-Global Cygnss Gnss-Reflectometry Using a Random Forest Machine Learning Model [link]Paper  doi  bibtex   
@inproceedings{wilson_prediction_2024,
	address = {Athens, Greece},
	title = {Prediction of {Soil} {Moisture} {From} {Near}-{Global} {Cygnss} {Gnss}-{Reflectometry} {Using} a {Random} {Forest} {Machine} {Learning} {Model}},
	copyright = {https://doi.org/10.15223/policy-029},
	isbn = {979-8-3503-6032-5},
	url = {https://ieeexplore.ieee.org/document/10642723/},
	doi = {10.1109/IGARSS53475.2024.10642723},
	urldate = {2025-02-13},
	booktitle = {{IGARSS} 2024 - 2024 {IEEE} {International} {Geoscience} and {Remote} {Sensing} {Symposium}},
	publisher = {IEEE},
	author = {Wilson, M.D. and Datta, R. and Savarimuthu, S. and Moller, D. and Ruf, C.},
	month = jul,
	year = {2024},
	pages = {4465--4471},
}

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