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Assessing the Prospects of Remote Sensing Maize Leaf Area Index Using UAV-Derived Multi-Spectral Data in Smallholder Farms across the Growing Season.

S. Buthelezi, O. Mutanga, M. Sibanda, J. Odindi, A. Clulow, V. Chimonyo, and T. Mabhaudhi. Remote. Sens., 15 (6): 1597 (March 2023)

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Assessing the Prospects of Remote Sensing Maize Leaf Area Index Using UAV-Derived Multi-Spectral Data in Smallholder Farms across the Growing Season.S. Buthelezi, O. Mutanga, M. Sibanda, J. Odindi, A. Clulow, V. Chimonyo, and T. Mabhaudhi. Remote. Sens., 15 (6): 1597 (March 2023)Estimating Biomass of Native Grass Grown under Complex Management Treatments Using WorldView-3 Spectral Derivatives.M. Sibanda, O. Mutanga, M. Rouget, and L. Kumar. Remote. Sens., 9 (1): 55 (2017)A Hybrid Feature Method for Handling Redundant Features in a Sentinel-2 Multidate Image for Mapping Parthenium Weed.Z. Kiala, O. Mutanga, J. Odindi, S. Viriri, and M. Sibanda. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., (2020)Detection and mapping the spatial distribution of bracken fern weeds using the Landsat 8 OLI new generation sensor.T. Matongera, O. Mutanga, T. Dube, and M. Sibanda. Int. J. Appl. Earth Obs. Geoinformation, (2017)A Comparative Estimation of Maize Leaf Water Content Using Machine Learning Techniques and Unmanned Aerial Vehicle (UAV)-Based Proximal and Remotely Sensed Data.H. Ndlovu, J. Odindi, M. Sibanda, O. Mutanga, A. Clulow, V. Chimonyo, and T. Mabhaudhi. Remote. Sens., 13 (20): 4091 (2021)

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copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Assessing the Prospects of Remote Sensing Maize Leaf Area Index Using UAV-Derived Multi-Spectral Data in Smallholder Farms across the Growing Season.

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