Monitoring the southern corn rust based on hyperspectral remote sensing

Abstract

In this study, the canopy hyperspectral reflectance of Southern Corn Rust (SCR) was collected by ground spectrometer, and the canopy spectral characteristics of SCR, the correlation between canopy spectral reflectance or vegetation index and disease index (DI) were analyzed, then a hyperspectral remote sensing monitoring model of SCR was constructed. The results showed that: (1) There was a reflection peak at 550 nm after maize was infected by SCR, and an absorption valley near 970 nm. (2) The DI of SCR was significantly negatively correlated with canopy spectral reflectance at 350~720 nm (P<0.05), and the maximum negative correlation was near 680 nm (P<0.05), | r | was 0.47~0.76. (3) The hyperspectral monitoring model of SCR was established based on different vegetation indexes. The results showed that the model constructed by NDVI705 had better monitoring accuracy and verification accuracy. The R2 of the monitoring model was 0.651, RMSE was 0.276, and the relative error between the predicted value and the measured value was 12.13%, R2 was 0.679, RMSE was 0.288.