The importance of leaf area index in mapping chlorophyll content of corn under different agricultural treatments using UAV images

ABSTRACTThe impact of structural parameters of agricultural crops on the retrieval of chlorophyll content presents a real challenge for the remote-sensing community. Canopy reflectance can differ between crops of different canopy structure even when they have the same canopy chlorophyll content. Thus, structural properties should be incorporated in chlorophyll mapping to reduce modelling errors. The empirical relationships between vegetation indices and chlorophyll content are well established and commonly used in precision agriculture. Recent advances in using unmanned aerial vehicle (UAV/drone) technology offer successful retrieval of crop structural and biochemical parameters. However, transfer of empirical algorithms derived from satellite to UAV-based analyses introduces new challenges mainly due to fine spatial resolution and details such as crop rows and between- and within-canopy gaps that are more pronounced in UAV images. There are two components of the analysis in this study. The first part is ...