Forage Mass Monitoring (FFM) analysis has been traditionally done using biomass sampling to calculate biomass yield per hectare (t ha–1). Current research projects are now looking at reflectance spectroscopy methods using remote sensing systems based on unmanned aerial vehicles (UAVs). Promising results in recent years prove the principal suitability of such systems for airborne monitoring of small- to medium-sized farmland in agricultural applications for precision agriculture, such as biomass for crops and grasslands. An imaging system in the form of a multispectral multicamera system is often used to derive well-established vegetation indices (VIs) efficiently. However, due to the use of silicon-based sensors, the spectral application range of such multi-camera systems is limited to the visible and near infrared (NIR) wavelength range (400–1000 nm). Therefore, more robust indicators linked to biomass in the short-wave infrared (like cellulose or moisture content) cannot be considered as estimators.
In a joint research project, a team from the University of Applied Science Koblenz and the Remote Sensing and GIS group at the University of Cologne developed a UAV-based multi-camera system to collect NIR/SWIR data, to prove more robust and better-performing estimators of biomass monitoring.