Remote sensing based evapotranspiration modeling for sugarcane in Brazil using a hybrid approach
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DOI: 10.1016/j.agwat.2022.107763
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Cited by:
- Gonçalves, I.Z. & Ruhoff, A. & Laipelt, L. & Bispo, R.C. & Hernandez, F.B.T. & Neale, C.M.U. & Teixeira, A.H.C. & Marin, F.R., 2022. "Remote sensing-based evapotranspiration modeling using geeSEBAL for sugarcane irrigation management in Brazil," Agricultural Water Management, Elsevier, vol. 274(C).
- Zhou, Hanmi & Ma, Linshuang & Niu, Xiaoli & Xiang, Youzhen & Chen, Jiageng & Su, Yumin & Li, Jichen & Lu, Sibo & Chen, Cheng & Wu, Qi, 2024. "A novel hybrid model combined with ensemble embedded feature selection method for estimating reference evapotranspiration in the North China Plain," Agricultural Water Management, Elsevier, vol. 296(C).
- M. Babaei & H. Ketabchi, 2022. "Determining Groundwater Recharge Rate with a Distributed Model and Remote Sensing Techniques," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(14), pages 5401-5423, November.
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Keywords
Satellite image; SETMI; Irrigation management; Saccharum officinarum;All these keywords.
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