Research on Sugarcane Sugar Estimation Model based on UAV Hyperspectral Data
In order to explore the ability of UAV hyperspectral remote sensing to directly estimate sugarcane sugar content,two main sugarcane varieties in Guangxi,Guitang 42(GT42)and Guiliu 05136(GL05136),were used in field experiment with many nitrogen fertilizer levels.Then,the canopy hyperspectral reflectance of newly planted cane at elongation stage and process maturity stage was obtained by UAV.Combined with sugar content data measured in the field,sugarcane sugar content estimation models were constructed.The results showed that:①From stem elongation stage to process maturity stage,the sugar content of GT42 and GL05136 under different nitrogen fertilizer treatments increased,while the difference in sugar content between different treatments of the same variety decreased.②The sugar-sensitive hyperspectral bands were different for different varieties of sugarcane at different growth stages.The red-edge band and the blue-red band were more sensitive to the changes of sucrose content at the elongation stage and the technical maturity stage,respectively.491,549,622,718,and 834 nm can be used as the characteristic bands of red,green,blue,red and near-infrared spectra respectively to model the sugar vegetation index.③At stem elongation stage,the estimation accuracy of all hyperspectral vegetation indices for GT42 was significantly higher than that of GL05136,but the opposite was true at process maturity stage.PSRI and MCARI were the optimal sugar fitting index of GT42 at stem elongation stage(R2=0.987)and process maturity stage(R2=0.587).For GL05136 at stem elongation stage(R2=0.850)and process maturity stage(R2=0.231),the preferred index was VARI.
UAV remote sensingHyperspectralSugar content of sugarcaneVegetation indexEstimating models
国家科技期刊平台
NSTL
万方数据
维普
