Improving crop yield estimation by assimilating LAI and inputting satellite-based surface incoming solar radiation into SWAP model

By Alireza Mokhtari, H. Noory, M. Vazifedoust. 2018

92 citations recorded by the source corpus.

Subfields: Ecology, Environmental Engineering, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/23fef6cb84af609fd110c4fc876edd7ca03abed6

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1. O. D. Adeniyi
2. A. Szabo
3. J. Tamás
4. A. Nagy

Citations in the corpus

• Wheat Yield Forecasting for the Tisza River Catchment Using Landsat 8 NDVI and SAVI Time Series and Reported Crop Statistics (2021, methodology): “NDVI and SAVI was chosen in this research, since those vegetation indices (VIs) were ranked as VIs with the highest correlations with wheat yield [34,35].”