Please use this identifier to cite or link to this item:
https://hdl.handle.net/1959.11/20291
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/rs8020109 | Handle Link: | https://hdl.handle.net/1959.11/20291 | 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: | MDPI AG | Place of Publication: | Switzerland | ISSN: | 2072-4292 | Fields of Research (FoR) 2008: | 070104 Agricultural Spatial Analysis and Modelling | Fields of Research (FoR) 2020: | 300206 Agricultural spatial analysis and modelling | Socio-Economic Objective (SEO) 2008: | 830406 Sown Pastures (excl. Lucerne) | Socio-Economic Objective (SEO) 2020: | 100505 Sown pastures (excl. lucerne) | Peer Reviewed: | Yes | HERDC Category Description: | C1 Refereed Article in a Scholarly Journal |
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Appears in Collections: | Journal Article School of Science and Technology |
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