Multimodal remote sensing for enhancing detection of spatial variability in agricultural fields

Detection of variability in agricultural fields depends on the spatial scale of the observed variable. Plant water status can be evaluated using thermal IR images that can provide valuable information on the water status, whereas visible RGB images can provide detailed information on the plants' color, which is not a good indicator of the water status. The informative mode (thermal IR images) has coarse resolution, as opposed to the excessive resolution of the less informative mode (visible RGB). In the present study, we present a method to enhance the information obtained from the thermal IR mode, by combining information from the visible RGB mode. We propose to un-mix the temperature of objects in the thermal images based on the information extracted from the high resolution RGB image