Classification of 3D Point Clouds Using Color Vegetation Indices for Precision Viticulture and Digitizing Applications
This article belongs to the Special Issue Remote Sensing in Viticulture.
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Multidisciplinary Digital Publishing Institute
2020-01-18
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| Subjects: | UAV imagery, Grapevine height, DSM, RGB sensor, Structure, Vineyard, |
| Online Access: | http://hdl.handle.net/10261/227042 http://dx.doi.org/10.13039/501100011033 http://dx.doi.org/10.13039/501100000780 |
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dig-ias-es-10261-2270422021-06-11T08:49:52Z Classification of 3D Point Clouds Using Color Vegetation Indices for Precision Viticulture and Digitizing Applications Mesas-Carrascosa, Francisco Javier Castro, Ana Isabel de Torres-Sánchez, Jorge Triviño-Tarradas, Paula Jiménez-Brenes, Francisco Manuel García-Ferrer, Alfonso López Granados, Francisca Ministerio de Ciencia, Innovación y Universidades (España) European Commission Agencia Estatal de Investigación (España) UAV imagery Grapevine height DSM RGB sensor Structure Vineyard This article belongs to the Special Issue Remote Sensing in Viticulture. Remote sensing applied in the digital transformation of agriculture and, more particularly, in precision viticulture offers methods to map field spatial variability to support site-specific management strategies; these can be based on crop canopy characteristics such as the row height or vegetation cover fraction, requiring accurate three-dimensional (3D) information. To derive canopy information, a set of dense 3D point clouds was generated using photogrammetric techniques on images acquired by an RGB sensor onboard an unmanned aerial vehicle (UAV) in two testing vineyards on two different dates. In addition to the geometry, each point also stores information from the RGB color model, which was used to discriminate between vegetation and bare soil. To the best of our knowledge, the new methodology herein presented consisting of linking point clouds with their spectral information had not previously been applied to automatically estimate vine height. Therefore, the novelty of this work is based on the application of color vegetation indices in point clouds for the automatic detection and classification of points representing vegetation and the later ability to determine the height of vines using as a reference the heights of the points classified as soil. Results from on-ground measurements of the heights of individual grapevines were compared with the estimated heights from the UAV point cloud, showing high determination coefficients (R² > 0.87) and low root-mean-square error (0.070 m). This methodology offers new capabilities for the use of RGB sensors onboard UAV platforms as a tool for precision viticulture and digitizing applications. This research was funded by the AGL2017-82335-C4-4R project (Spanish Ministry of Science, Innovation and Universities, AEI-EU FEDER funds). 2021-01-19T10:40:22Z 2021-01-19T10:40:22Z 2020-01-18 2021-01-19T10:40:22Z artículo http://purl.org/coar/resource_type/c_6501 doi: 10.3390/rs12020317 e-issn: 2072-4292 Remote Sensing 12(2): 317 (2020) http://hdl.handle.net/10261/227042 10.3390/rs12020317 http://dx.doi.org/10.13039/501100011033 http://dx.doi.org/10.13039/501100000780 #PLACEHOLDER_PARENT_METADATA_VALUE# info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/AGL2017-82335-C4-4-R Publisher's version http://doi.org/10.3390/rs12020317 Sí open Multidisciplinary Digital Publishing Institute |
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UAV imagery Grapevine height DSM RGB sensor Structure Vineyard UAV imagery Grapevine height DSM RGB sensor Structure Vineyard |
| spellingShingle |
UAV imagery Grapevine height DSM RGB sensor Structure Vineyard UAV imagery Grapevine height DSM RGB sensor Structure Vineyard Mesas-Carrascosa, Francisco Javier Castro, Ana Isabel de Torres-Sánchez, Jorge Triviño-Tarradas, Paula Jiménez-Brenes, Francisco Manuel García-Ferrer, Alfonso López Granados, Francisca Classification of 3D Point Clouds Using Color Vegetation Indices for Precision Viticulture and Digitizing Applications |
| description |
This article belongs to the Special Issue Remote Sensing in Viticulture. |
| author2 |
Ministerio de Ciencia, Innovación y Universidades (España) |
| author_facet |
Ministerio de Ciencia, Innovación y Universidades (España) Mesas-Carrascosa, Francisco Javier Castro, Ana Isabel de Torres-Sánchez, Jorge Triviño-Tarradas, Paula Jiménez-Brenes, Francisco Manuel García-Ferrer, Alfonso López Granados, Francisca |
| format |
artículo |
| topic_facet |
UAV imagery Grapevine height DSM RGB sensor Structure Vineyard |
| author |
Mesas-Carrascosa, Francisco Javier Castro, Ana Isabel de Torres-Sánchez, Jorge Triviño-Tarradas, Paula Jiménez-Brenes, Francisco Manuel García-Ferrer, Alfonso López Granados, Francisca |
| author_sort |
Mesas-Carrascosa, Francisco Javier |
| title |
Classification of 3D Point Clouds Using Color Vegetation Indices for Precision Viticulture and Digitizing Applications |
| title_short |
Classification of 3D Point Clouds Using Color Vegetation Indices for Precision Viticulture and Digitizing Applications |
| title_full |
Classification of 3D Point Clouds Using Color Vegetation Indices for Precision Viticulture and Digitizing Applications |
| title_fullStr |
Classification of 3D Point Clouds Using Color Vegetation Indices for Precision Viticulture and Digitizing Applications |
| title_full_unstemmed |
Classification of 3D Point Clouds Using Color Vegetation Indices for Precision Viticulture and Digitizing Applications |
| title_sort |
classification of 3d point clouds using color vegetation indices for precision viticulture and digitizing applications |
| publisher |
Multidisciplinary Digital Publishing Institute |
| publishDate |
2020-01-18 |
| url |
http://hdl.handle.net/10261/227042 http://dx.doi.org/10.13039/501100011033 http://dx.doi.org/10.13039/501100000780 |
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