 This paper proposes a method for mapping the nitrogen and status of a maze field using hyperspectral remote sensing imagery. The method involves collecting field data such as leaf and canopy nitrogen concentrations and dry matter weight, as well as remotely sensed vegetation indices. These indices are then used to estimate the nitrogen nutrition index, NNI, which is defined as the ratio between the leaf nitrogen concentration and the critical nitrogen concentration needed for maximum biomass production. The NNI is then mapped across the field, and a variable rate N-fertilizer map is derived by comparing the actual nitrogen concentration to the optimal nitrogen concentration. This article is authored by Chiara Silia, Cynthia Panagata, Mikhail Rossini, and others.