Rice Yield Estimation with Vegetation Index Using Multispectral Imagery from Unmanned Aerial Vehicle
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Abstract
Multispectral high - resolution imagery from unmanned aerial vehicle (UAV) of rice (Chai Nat 1 varieties) in the research plots at Mae Hia Agricultural Research, Demonstration and Training Center, Faculty of Agriculture, Chiang Mai University was analyzed spatially to crop spectral parameters with a program of geographic information system (GIS) in terms of three vegetation index (VI) including two physical collaborating parameters. These parameters were developed collaborating with the rice yield data from crop cutting as the models in terms of simple and multiple linear regression equations to estimate rice yield in experimental plots. As a result, found that, the most reliable model was developed with all crop spectral parameters from unmanned aerial vehicle (UAV) in terms of multiple linear regression equation that is Y = - 430.86 - 5108.88X1 - 447.9X2 + 2751.09X3 + 282.36X4 - 254.2X5 with the most determination coefficient of 0.879. In conclusion, the model can provided closely rice yield estimation with observed yields. It can be usefully implemented to predict rice yield at the plot level.
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References
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