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Imaging Spectrometry and Fluorometry in Support of Flex: What Can We Learn from Multi-Scale Experiments?, , , , , , , , , and 5 other author(s). IGARSS, page 3931-3934. IEEE, (2018)SMAP Vegetation Optical Depth is Directly Proportional to Crop Water in the US Corn Belt., , , , , and . IGARSS, page 5445-5448. IEEE, (2019)Latent heat and sensible heat flux simulation in maize using artificial neural networks., , , , and . Comput. Electron. Agric., (2018)Gross primary production and ecosystem respiration of irrigated maize and irrigated soybean during a growing season, , , and . Agricultural and Forest Meteorology, 131 (3-4): 180--190 (August 2005)Annual carbon dioxide exchange in irrigated and rainfed maize-based agroecosystems, , , , , , , , , and 4 other author(s). Agricultural and Forest Meteorology, 131 (1-2): 77--96 (July 2005)Modeling Gross Primary Production of Midwestern US Maize and Soybean Croplands with Satellite and Gridded Weather Data., , , , and . Remote. Sens., 12 (23): 3956 (2020)Toward Generic Models for Green LAI Estimation in Maize and Soybean: Satellite Observations., , , , and . Remote Sensing, 9 (4): 318 (2017)Relationship between gross primary production and chlorophyll content in crops: Implications for the synoptic monitoring of vegetation productivity, , , , , , , , , and . J. Geophys. Res., 111 (D8): D08S11+ (Apr 27, 2006)Net Ecosystem Exchange (NEE) simulation in maize using artificial neural networks., , , , and . IFAC J. Syst. Control., (2019)Assessment of Canopy Chlorophyll Content Retrieval in Maize and Soybean: Implications of Hysteresis on the Development of Generic Algorithms., , , and . Remote. Sens., 9 (3): 226 (2017)