Biomass is a critical biophysical parameter used to monitor agricultural and terrestrial ecosystems. Operational difficulties in measuring biomass on the field scale led to use of remote sensing techniques. Numerous vegetation indices (VIs) have been developed for this purpose, most of which utilize bands in the VIS-NIR spectral region. However, a significant number of them exhibit saturation at leaf area index (LAI) higher than 2. We propose an innovative vegetation index red-edge ratio normalized difference vegetation index (RERNDVI), that combines a VI sensitive to moderate to high LAI with VI sensitive to low to moderate LAI. An empirical assessment of the performance of our new index compared with nine existing spectral indices was conducted using hyperspectral and biomass data collected by Center for Advanced Land Management Information Technologies for maize and soybean fields, and Sentinel-2 data for semi-arid shrubland sites for which biomass was estimated based on the allometric model. The coefficient of determination (r²) of RERNDVI with green biomass for maize and soybean is high, but equally important, its noise equivalence is significantly lower than that obtained for all other indices for the full range of biomass levels. Nevertheless, RERNDVI-biomass relationships vary for different crops and shrubs, suggesting that generalizing these relationships will require information regarding canopy structure parameters as well.