The research presented here examines the potential of multipolarization RADARSAT-2 (C-band) and Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) (L-band) for Leaf Area Index estimation over soybeans (low biomass crop) and corn (high biomass crop) canopies.
A new Leaf Area Index estimation approach is developed based on coupling of two existing models, the Water Cloud Model and the Ulabymodel.Previous research on SAR sensitivity to Leaf Area Index has been primarily empirically based, with simple statistical models developed and inverted to estimate Leaf Area Index. This study proposes a semiempirical approach, which when well calibrated is likely to be more robust when applied within its range of validity. The models developed in this study are applicable to a range of Leaf Area Index from 0.04–4.79 for cornfields and from 0.07–3.57 for soybeanfields