Drone-based sensing for identification of at-risk water and nitrogen stress areas for on-farm management

In this research, various models are developed to estimate the biophysical and biochemical properties of the crop, using only drone-based RGB and hyperspectral data. In conjunction with the input resources supplied on the farm, growth-stage based crop properties analysis is performed. Collection and analysis of field and drone-based leaf-level hyperspectral data and CHNS analysis of leaf samples make this research data novel. New leaf-water and nitrogen content indices that can distinguish water and nitrogen stress are found. The developed models are used to obtain the spatial and temporal distribution of water and nitrogen stress in the farm.