Sensitivity of Remote Sensing Estimates of Wheat Chlorophyll Content. to Varying Soil Reflectance.

Ground-based remote sensing estimates of wheat (Triticum aestivum L.) nitrogen (N) status helps growers decide whether in-season N fertilizer applications are needed. These estimates are based on spectral indices that are sensitive to chlorophyll content (C_ab ), but also leaf area index (LAI) and soil background variation. To isolate C_ab from LAI spectral signals, the combined use of chlorophyll and structural indices has been proposed since the latter helps minimize LAI effects. However, relatively little is known about the sensitivity of these combined indices to variations in soil background effects. The objectives of this study were to evaluate the sensitivity of selected combined indices and their single index counterparts to varying soil reflectance and to test how strongly soil reflectance affects the overall index performance for ground-based sensing of C_ab. A total of 121 soil surface reflectance spectra acquired throughout major wheat growing areas in the United States were used as input to the PROSPECT+SAIL radiative transfer model, which in turn was used to simulate the effect of soil spectra on canopy reflectance and computed spectral indices. Variation in soil background reflectance appeared to influence spectral indices only for low LAI values (LAI<1.5). Overall index performance showed that effect of soil background on spectral indices is minimal compared to LAI. Across all studied indices, the ratio of Modified Chlorophyll Absorption Ratio Index to second Modified Triangular Vegetation Index (MCARI/MTVI2) showed the greatest sensitivity to variations in C_ab; explaining almost 90% of the observed variability. The strong performance of MCARI/MTVI2 was attributed to its relatively low sensitivity to both variations in soil background effects and LAI. Further research is needed to evaluate the effects of soil moisture, surface roughness, residue, growth stage and shadow on the studied indices.