Monitoring of sugar beet growth indicators using wide-dynamic-range vegetation index (WDRVI) derived from UAV multispectral images

Abstract

The normalized vegetation index (NDVI) is widely used to monitor the spatial, temporal, physiological, and biophysical characteristics of vegetation. However, if the ground biomass is high, the NDVI becomes rapidly saturated. In the leaf area index (LAI) range of 2 to 6, reflectance in the near-infrared band is significantly higher than that in the red band. When reflectance in the near-infrared band exceeds 40%, the contribution of that reflectance to the NDVI is low. Here, we applied a weight coefficient, α (range 0.05 to 0.5), to the near-infrared band, thus developing a wide-dynamic-range vegetation index (WDRVI). We calculated (α * NIR-RED)/(α * NIR + RED) values; these emphasized the Fresh Weight of Beet LAI, the Fresh Weight of Leaves (FWL), and the Fresh Weight of Roots (FWR). We sought a vegetation index that optimally monitored early-stage sugar beet growth. The WDRVI sensitivities using various α coefficients were higher than those of the NDVI in the LAI range of 2 to 6. The determination coefficients (r2 values) of the sugar beet LAI, FWL, and FWT models established using the WDRVI1 were 0.957, 0.950, and 0.963, respectively. Using the WDRVI1 index model to estimate the accuracy of beet growth indicators can improve 1.05% to 5.07%. Use of the WDRVI reduces beet growth indicator saturation when the ground biomass is high, enhancing the accuracy of growth monitoring. This is useful as the sugar beet has huge ground biomass.