Abstract

Non-destructive methods to derive spatial information on the development of forage mass are of key importance in managed grasslands. Established methods are rising plate meter (RPM) and rapid pasture meter, which both require in-field work, are rather time consuming, and do not provide spatially continuous data. Therefore, the overall objective of this study is to investigate low-cost unmanned aerial vehicle (UAV)-based RGB image acquisition for grassland monitoring. The idea of this paper is to transfer the successfully introduced approach of crop surface models (CSMs) for ultrahigh resolution analysis of plant height to managed grasslands. The study area is the Rengen Long-term Grassland Experiment, Germany, which is a two-cut experiment and was established in 1941. We conducted RPM and UAV-based data acquisition over six growth periods in 2014, 2015, and 2016. In 3 years, 26 RPM and 46 UAV campaigns were conducted under varying weather conditions (cloudy/sunny). The UAV-based RGB imagery was photogrammetrically processed with Structure from Motion and Multi-view Stereopsis techniques, producing multi-temporal CSMs for grassland sward height analysis. The regression analysis of UAV-derived sward height (CSM-SH) against RPM-measured sward height (RPM-SH) resulted in R2 of 0.91, 0.87, and 0.83 for 2014, 2015, and 2016, respectively. The pooling of the data for all 3 years resulted in an R2 of 0.86. These findings prove the successful transfer of the CSM approach for grassland monitoring and the potential of UAV-based monitoring to replace manual or in-field measurements with RPM or rapid pasture meter.

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