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Title: A Combination of Plant NDVI and LiDAR Measurements Improve the Estimation of Pasture Biomass in Tall Fescue (Festuca arundinacea var. Fletcher)
Contributor(s): Schaefer, Michael T  (author); Lamb, David  (author)
Publication Date: 2016
Open Access: Yes
DOI: 10.3390/rs8020109Open Access Link
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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.
Publication Type: Journal Article
Source of Publication: Remote Sensing, 8(2), p. 1-10
Publisher: MDPIAG
Place of Publication: Switzerland
ISSN: 2072-4292
Field of Research (FOR): 070104 Agricultural Spatial Analysis and Modelling
Socio-Economic Objective (SEO): 830406 Sown Pastures (excl. Lucerne)
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
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