A coupled multitemporal UAV-based LiDAR and multispectral data approach to model dry biomass of maize

Abstract

The presented approach attempts to highlight the capabilities of a data fusion approach that combines UAV LiDAR (RIEGL – miniVUX-1UAV) and multispectral data (Micasense – Altum) to assess the dry above ground biomass (AGB) for maize. The combined acquisition of both LiDAR and multispectral data not only supports estimates of AGB when fusing them, but also helps to evaluate phenological stage-specific modelling differences on the individual sensor data. A multiple linear regression was applied on the multisensorial UAV data from two appointments in 2021. The resulting R² of 0.87 and RMSE of 14.35 g/plant for AGB was then transferred to AGB in dt/ha.