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Active-Optical Sensors Using Red NDVI Compared to Red Edge NDVI for Prediction of Corn Grain Yield in North Dakota, U.S.A.

, , , and . Sensors, 15 (11): 27832-27853 (2015)

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Large-Window Curvature Computations for High-Resolution Digital Elevation Models., , , and . IEEE Trans. Geosci. Remote. Sens., (2022)Active-Optical Sensors Using Red NDVI Compared to Red Edge NDVI for Prediction of Corn Grain Yield in North Dakota, U.S.A., , , and . Sensors, 15 (11): 27832-27853 (2015)Multi-scalar analysis of geospatial agricultural data for sustainability., , , and . IEEE BigData, page 2139-2146. IEEE Computer Society, (2016)Scaling up Window-Based Slope Computations for Geographic Information System., , and . EIT, page 554-559. IEEE, (2018)Corn Nitrogen Nutrition Index Prediction Improved by Integrating Genetic, Environmental, and Management Factors with Active Canopy Sensing Using Machine Learning., , , , , , , , , and 4 other author(s). Remote. Sens., 14 (2): 394 (2022)Use of corn height measured with an acoustic sensor improves yield estimation with ground based active optical sensors., , , and . Comput. Electron. Agric., (2016)Quantifying Efficiency of Sliding-Window Based Aggregation Technique by Using Predictive Modeling on Landform Attributes Derived from DEM and NDVI., , and . ISPRS Int. J. Geo Inf., 8 (4): 196 (2019)Statistical and machine learning methods evaluated for incorporating soil and weather into corn nitrogen recommendations., , , , , , , , , and 2 other author(s). Comput. Electron. Agric., (2019)Comparing classification accuracy of NDVI with DEM derived attributes using multi-scalar approach in Geographic Information Systems., , and . EIT, page 249-254. IEEE, (2019)