Applying Different Remote Sensing Data to Determine Relative Biomass Estimations of Cereals for Precision Fertilization Task Generation

Abstract

Recently, the area of passive remote sensing of agricultural fields has been developing fast. The prices of RPAS (remotely piloted aircraft system) equipment has gone down and 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 fertilization planning. Our study revealed that while there was a 23 % spatial variation in our test field’s yield, the relative biomass estimations for fertilization planning during the growing season varied 22 % on average although they were visually very alike.