Accurate N mapping in cotton with hyperspectral data
FluroSat’s science team has recently published a peer-reviewed academic paper comparing the use of multi- and hyperspectral data for cotton nitrogen use efficiency (NUE) in prestigous IEEE GRSS letters.
Authored by FluroSat’s remote sensing team including Anastasia Volkova, Irah Wajchman and Julian Guinane with John Baird of NSW Department of Primary Industry (DPI), this paper is based on the analysis we conducted over Australian Cotton Research Institute (ACRI) fields during the most recent cotton season.
Our research compared Vegetation Indice (VI) maps and graphs generated from data acquired using both hyperspectral and multispectral sensors mounted on drones, as well as satellite multispectral data. The results of our analysis demonstrated the potential of hyperspectral data to identify greater variability in crops, especially later in the season.
You can read the white paper here.