Unmanned aerial vehicle remote sensing inversion of relative chlorophyll content of maize leaves and identification of their indicator leaf at different flight altitudes
The detection accuracy of chlorophyll content in maize leaves is affected by spatial heterogeneity.The pur-pose of this study was to investigate the relationship between relative chlorophyll content(SPAD value)and vegetation indi-ces of maize leaves based on unmanned aerial vehicle(UAV)remote sensing technology,so as to clarify the indicator leaf and the best UAV flying altitude.The remote sensing estimation model of relative chlorophyll content based on vegetation in-dices was constructed by random forest method,and the model was evaluated.The results showed that relative chlorophyll content in maize leaves at grain filling stage was higher than that at milking stage,and relative chlorophyll content of middle leaves was higher than that of upper and lower leaves.During the grain filling stage and milking stage,the SPAD value of maize leaves was indicated by the fifth leaf,and the best precision for the regression model(R2=0.94)was obtained when the flying altitude of UAV was 20 m.The results can provide technical support for improving the accuracy of remote sensing monitoring of relative chloro-phyll content,and provide theoretical basis for crop smart management in the fields.
万方数据
维普
