Abstract
Abstract. Monitoring biomass yield in grassland is of key importance to support sustainable management decisions. Especially the high spatio-temporal variety in grasslands requires rapid and cost-efficient data acquisition with a high spatial and temporal resolution. Therefore, this study aims to evaluate the comparability of UAV-based simultaneously acquired vegetation indices from a consumer-grade RGB-camera (Sony Alpha 6000) and a well-calibrated narrow-band multispectral camera (MicaSense RedEdge-M) to estimate dry matter biomass yield. The study site is an experimental grassland field in Germany with four nitrogen fertilizer levels. Biomass yield and UAV-based data for the first cut in May 2018 was analysed in this study. From the RGB-data the Plant Pigment Ratio Index (PPR) and the Normalized Green Red Difference Index (NGRDI) and from the multispectral data the Normalized Difference Vegetation Index (NDVI) are calculated as predictors for dry biomass yield. The NGRDI and NDVI perform moderately well with cross-validation R2 of 0.57 and 0.63 respectively, while the PPR performs better with an R2 of 0.70. These results indicate the potential of low-cost UAV-based methods for rapid assessment of grasslands.
Highlights
Grasslands cover 40 % of the earths terrestrial surface and are of ecological and economic importance (FAO, 2010)
Besides providing ecosystem functions such as carbon sequestration, grasslands are the basis of milk and meat production, and play a role in biofuel production (O’Mara, 2012) Monitoring biomass yield throughout the growing season is of key importance to support management decisions on grasslands
The results indicate a promising approach to map grassland biomass in high spatial and temporal resolution with consumer-grade RGB cameras
Summary
Grasslands cover 40 % of the earths terrestrial surface and are of ecological and economic importance (FAO, 2010). On intensely managed grasslands, where nitrogen fertilizer and manure are applied regularly, precision agriculture applications are beneficial to support sustainable, site-specific management decisions on fertilizer treatment, grazing management and yield forecasting to mitigate potential negative impacts. To support these management decisions, timely and accurate information is needed on plant parameters with a high spatial and temporal resolution. The rapid development in platform and sensor technology, e.g. miniaturization and cost-efficiency of multispectral cameras and more user-friendly platforms (UAVs), open up a new spatial scale for environmental and agricultural studies and offer a cost efficient and near-real time assessment of biomass yield with high temporal and spatial resolution (Aasen et al, 2018)
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
