An improved NDVI-based method to predict actual evapotranspiration of irrigated grasses and crops
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DOI: 10.1016/j.agwat.2020.106077
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- Mahmoud, Shereif H. & Gan, Thian Yew, 2019. "Irrigation water management in arid regions of Middle East: Assessing spatio-temporal variation of actual evapotranspiration through remote sensing techniques and meteorological data," Agricultural Water Management, Elsevier, vol. 212(C), pages 35-47.
- Maselli, Fabio & Chiesi, Marta & Brilli, Lorenzo & Moriondo, Marco, 2012. "Simulation of olive fruit yield in Tuscany through the integration of remote sensing and ground data," Ecological Modelling, Elsevier, vol. 244(C), pages 1-12.
- Escarabajal-Henarejos, D. & Molina-Martínez, J.M. & Fernández-Pacheco, D.G. & Cavas-Martínez, F. & García-Mateos, G., 2015. "Digital photography applied to irrigation management of Little Gem lettuce," Agricultural Water Management, Elsevier, vol. 151(C), pages 148-157.
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- Elbeltagi, Ahmed & Deng, Jinsong & Wang, Ke & Malik, Anurag & Maroufpoor, Saman, 2020. "Modeling long-term dynamics of crop evapotranspiration using deep learning in a semi-arid environment," Agricultural Water Management, Elsevier, vol. 241(C).
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Keywords
Sentinel-2; Fractional Vegetation Cover (FVC); Water stress; Irrigation;All these keywords.
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