Mapping and Monitoring of Biomass and Grazing in Pasture with an Unmanned Aerial System
The tools available to farmers to manage grazed pastures and adjust forage demand to grass growth are generally rather static. Unmanned aerial systems (UASs) are interesting versatile tools that can provide relevant 3D information, such as sward height (3D structure), or even describe the physical c...
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| Vydané v: | Remote sensing (Basel, Switzerland) Ročník 11; číslo 5; s. 473 - 486 |
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| Hlavní autori: | , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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MDPI AG
01.03.2019
MDPI Multidisciplinary Digital Publishing Institute (MDPI) |
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| ISSN: | 2072-4292, 2072-4292 |
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| Abstract | The tools available to farmers to manage grazed pastures and adjust forage demand to grass growth are generally rather static. Unmanned aerial systems (UASs) are interesting versatile tools that can provide relevant 3D information, such as sward height (3D structure), or even describe the physical condition of pastures through the use of spectral information. This study aimed to evaluate the potential of UAS to characterize a pasture’s sward height and above-ground biomass at a very fine spatial scale. The pasture height provided by UAS products showed good agreement (R2 = 0.62) with a reference terrestrial light detection and ranging (LiDAR) dataset. We tested the ability of UAS imagery to model pasture biomass based on three different combinations: UAS sward height, UAS sward multispectral reflectance/vegetation indices, and a combination of both UAS data types. The mixed approach combining the UAS sward height and spectral data performed the best (adj. R2 = 0.49). This approach reached a quality comparable to that of more conventional non-destructive on-field pasture biomass monitoring tools. As all of the UAS variables used in the model fitting process were extracted from spatial information (raster data), a high spatial resolution map of pasture biomass was derived based on the best fitted model. A sward height differences map was also derived from UAS-based sward height maps before and after grazing. Our results demonstrate the potential of UAS imagery as a tool for precision grazing study applications. The UAS approach to height and biomass monitoring was revealed to be a potential alternative to the widely used but time-consuming field approaches. While reaching a similar level of accuracy to the conventional field sampling approach, the UAS approach provides wall-to-wall pasture characterization through very high spatial resolution maps, opening up a new area of research for precision grazing. |
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| AbstractList | The tools available to farmers to manage grazed pastures and adjust forage demand to grass growth are generally rather static. Unmanned aerial systems (UASs) are interesting versatile tools that can provide relevant 3D information, such as sward height (3D structure), or even describe the physical condition of pastures through the use of spectral information. This study aimed to evaluate the potential of UAS to characterize a pasture’s sward height and above-ground biomass at a very fine spatial scale. The pasture height provided by UAS products showed good agreement (R2 = 0.62) with a reference terrestrial light detection and ranging (LiDAR) dataset. We tested the ability of UAS imagery to model pasture biomass based on three different combinations: UAS sward height, UAS sward multispectral reflectance/vegetation indices, and a combination of both UAS data types. The mixed approach combining the UAS sward height and spectral data performed the best (adj. R2 = 0.49). This approach reached a quality comparable to that of more conventional non-destructive on-field pasture biomass monitoring tools. As all of the UAS variables used in the model fitting process were extracted from spatial information (raster data), a high spatial resolution map of pasture biomass was derived based on the best fitted model. A sward height differences map was also derived from UAS-based sward height maps before and after grazing. Our results demonstrate the potential of UAS imagery as a tool for precision grazing study applications. The UAS approach to height and biomass monitoring was revealed to be a potential alternative to the widely used but time-consuming field approaches. While reaching a similar level of accuracy to the conventional field sampling approach, the UAS approach provides wall-to-wall pasture characterization through very high spatial resolution maps, opening up a new area of research for precision grazing. The tools available to farmers to manage grazed pastures and adjust forage demand to grass growth are generally rather static. Unmanned aerial systems (UASs) are interesting versatile tools that can provide relevant 3D information, such as sward height (3D structure), or even describe the physical condition of pastures through the use of spectral information. This study aimed to evaluate the potential of UAS to characterize a pasture's sward height and above-ground biomass at a very fine spatial scale. The pasture height provided by UAS products showed good agreement (R2 = 0.62) with a reference terrestrial light detection and ranging (LiDAR) dataset. We tested the ability of UAS imagery to model pasture biomass based on three different combinations: UAS sward height, UAS sward multispectral reflectance/vegetation indices, and a combination of both UAS data types. The mixed approach combining the UAS sward height and spectral data performed the best (adj. R2 = 0.49). This approach reached a quality comparable to that of more conventional non-destructive on-field pasture biomass monitoring tools. As all of the UAS variables used in the model fitting processwereextractedfromspatialinformation(rasterdata),ahighspatialresolutionmapofpasture biomass was derived based on the best fitted model. A sward height differences map was also derived from UAS-based sward height maps before and after grazing. Our results demonstrate the potential of UAS imagery as a tool for precision grazing study applications. The UAS approach to height and biomass monitoring was revealed to be a potential alternative to the widely used but time-consumingfield approaches. While reachinga similarlevel ofaccuracy to theconventional field sampling approach, the UAS approach provides wall-to-wall pasture characterization through very high spatial resolution maps, opening up a new area of research for precision grazing. |
| Author | Bauwens, Sébastien Herinaina, Andriamandroso Blaise, Yannick Castro Muñoz, Eloy Bindelle, Jérôme Lebeau, Frédéric Lejeune, Philippe Michez, Adrien |
| Author_xml | – sequence: 1 givenname: Adrien orcidid: 0000-0003-4329-6422 surname: Michez fullname: Michez, Adrien – sequence: 2 givenname: Philippe surname: Lejeune fullname: Lejeune, Philippe – sequence: 3 givenname: Sébastien surname: Bauwens fullname: Bauwens, Sébastien – sequence: 4 givenname: Andriamandroso surname: Herinaina fullname: Herinaina, Andriamandroso – sequence: 5 givenname: Yannick surname: Blaise fullname: Blaise, Yannick – sequence: 6 givenname: Eloy surname: Castro Muñoz fullname: Castro Muñoz, Eloy – sequence: 7 givenname: Frédéric surname: Lebeau fullname: Lebeau, Frédéric – sequence: 8 givenname: Jérôme surname: Bindelle fullname: Bindelle, Jérôme |
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| Keywords | HAUTEUR DE PÂTURAGE HAUTEUR D'HERBE AÉRONEF SANS PILOTE PÂTURAGE DE PRÉCISION MODÉLISATION DE LA BIOMASSE PRAIRIALE |
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| SubjectTerms | Agriculture Agriculture & agronomie Agriculture & agronomy Biomass drone Environmental Sciences Farmers Geomorphology Grasslands Grazing Image detection Lidar Life sciences Mapping Monitoring Nitrogen Pasture pasture biomass modeling pasture height Plant growth precision grazing Reflectance Remote sensing Sciences du vivant Spatial data Spatial resolution Sward sward height Topography unmanned aerial systems Unmanned aerial vehicles Vegetation |
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| Title | Mapping and Monitoring of Biomass and Grazing in Pasture with an Unmanned Aerial System |
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