Different Remote Sensing Data in Relative Biomass Determination and in Precision Fertilization Task Generation for Cereal Crops

Abstract

Recently, the area of passive remote sensing in agricultural fields has been developing fast. The prices of RPAS (remotely piloted aircraft system) equipment has gone down, new suitable sensors are coming into markets while simultaneously new and free relevant satellite data has become available. One of the most used applications for these methodologies is to calculate the relative biomass as a basis for additional nitrogen fertilization. In this work, we study the difference of biomass estimations based on Sentinel-2 imagery, tractor implemented commercial measurement system, a low-cost RPAS equipment with commercial software and a hyperspectral imaging system implemented in a professional RPAS system in the fertilization planning. There was a 23% spatial variation in our malt barley yield. Different relative biomass estimations produced similar and sufficient results and the observation time or the used methodology was not very critical. Also none of the methodologies were remarkably better. When we generated the nitrogen fertilization application tasks, different reasonable parameters conducted very different application tasks. This means that in our case, the relative biomass does not provide sufficient information for nitrogen shortage variation. Knowledge of the local conditions is essential.