A Combination of Plant NDVI and LiDAR Measurements Improve the Estimation of Pasture Biomass in Tall Fescue (Festuca arundinacea var. Fletcher)

Abstract

The total biomass of a tall fescue (Festuca arundinacea var. Fletcher) pasture was assessed by using a vehicle mounted light detection and ranging (LiDAR) unit to derive canopy height and an active optical reflectance sensor to determine the spectro-optical reflectance index, normalized difference vegetation index (NDVI). In a random plot design, measurements of NDVI and pasture height were combined to estimate biomass with a root mean square error of prediction (RMSEP) equal to ±455.28 kg green dry matter (GDM)/ha, over a range of 286 kg to 3933 kg GDM/ha. The combination of NDVI and height measurements were observed to be more accurate in assessing total biomass than just the NDVI (RMSEP ± 846.51 kg/ha) and height (RMSEP ± 708.13 kg/ha). Based on the results of the study it was concluded the use of combined LiDAR and active optical reflectance sensors can help unlock the complex interrelationship between green fraction and biomass in swards containing both green and senescent material.

Plant phenotyping relevance

LiDARとNDVIセンサーを組み合わせ、牧草キャノピー高・反射情報からバイオマスを推定し、単独測定との精度比較で技術性能を検証しているため、植物表現型取得法が中心である。

Code and data availability

The article describes NDVI/LiDAR pasture biomass measurements and regression analysis in MS Excel, but contains no data availability statement, no public dataset deposit, and no author code or model release. The only URL present is the CC-BY license notice, which is not a paper-specific asset.

No evidence-backed public reproduction asset is currently recorded.