Georeferenced LiDAR 3D Vine Plantation Map Generation

The use of electronic devices for canopy characterization has recently been widely discussed. Among such devices, LiDAR sensors appear to be the most accurate and precise. Information obtained with LiDAR sensors during reading while driving a tractor along a crop row can be managed and transformed i...

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Main Authors: Meritxell Queraltó, Jordi Llop, Emilio Gil, Jordi Llorens
Format: Article
Language:English
Published: MDPI AG 2011-06-01
Series:Sensors
Subjects:
GPS
Online Access:http://www.mdpi.com/1424-8220/11/6/6237/
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spelling doaj-6e92a783811c4d97bc8e0dd7fe68e53c2020-11-24T21:40:23ZengMDPI AGSensors1424-82202011-06-011166237625610.3390/s110606237Georeferenced LiDAR 3D Vine Plantation Map GenerationMeritxell QueraltóJordi LlopEmilio GilJordi LlorensThe use of electronic devices for canopy characterization has recently been widely discussed. Among such devices, LiDAR sensors appear to be the most accurate and precise. Information obtained with LiDAR sensors during reading while driving a tractor along a crop row can be managed and transformed into canopy density maps by evaluating the frequency of LiDAR returns. This paper describes a proposed methodology to obtain a georeferenced canopy map by combining the information obtained with LiDAR with that generated using a GPS receiver installed on top of a tractor. Data regarding the velocity of LiDAR measurements and UTM coordinates of each measured point on the canopy were obtained by applying the proposed transformation process. The process allows overlap of the canopy density map generated with the image of the intended measured area using Google Earth®, providing accurate information about the canopy distribution and/or location of damage along the rows. This methodology was applied and tested on different vine varieties and crop stages in two important vine production areas in Spain. The results indicate that the georeferenced information obtained with LiDAR sensors appears to be an interesting tool with the potential to improve crop management processes.http://www.mdpi.com/1424-8220/11/6/6237/LiDARcanopy densityvineyardGPSUTM coordinates
collection DOAJ
language English
format Article
sources DOAJ
author Meritxell Queraltó
Jordi Llop
Emilio Gil
Jordi Llorens
spellingShingle Meritxell Queraltó
Jordi Llop
Emilio Gil
Jordi Llorens
Georeferenced LiDAR 3D Vine Plantation Map Generation
Sensors
LiDAR
canopy density
vineyard
GPS
UTM coordinates
author_facet Meritxell Queraltó
Jordi Llop
Emilio Gil
Jordi Llorens
author_sort Meritxell Queraltó
title Georeferenced LiDAR 3D Vine Plantation Map Generation
title_short Georeferenced LiDAR 3D Vine Plantation Map Generation
title_full Georeferenced LiDAR 3D Vine Plantation Map Generation
title_fullStr Georeferenced LiDAR 3D Vine Plantation Map Generation
title_full_unstemmed Georeferenced LiDAR 3D Vine Plantation Map Generation
title_sort georeferenced lidar 3d vine plantation map generation
publisher MDPI AG
series Sensors
issn 1424-8220
publishDate 2011-06-01
description The use of electronic devices for canopy characterization has recently been widely discussed. Among such devices, LiDAR sensors appear to be the most accurate and precise. Information obtained with LiDAR sensors during reading while driving a tractor along a crop row can be managed and transformed into canopy density maps by evaluating the frequency of LiDAR returns. This paper describes a proposed methodology to obtain a georeferenced canopy map by combining the information obtained with LiDAR with that generated using a GPS receiver installed on top of a tractor. Data regarding the velocity of LiDAR measurements and UTM coordinates of each measured point on the canopy were obtained by applying the proposed transformation process. The process allows overlap of the canopy density map generated with the image of the intended measured area using Google Earth®, providing accurate information about the canopy distribution and/or location of damage along the rows. This methodology was applied and tested on different vine varieties and crop stages in two important vine production areas in Spain. The results indicate that the georeferenced information obtained with LiDAR sensors appears to be an interesting tool with the potential to improve crop management processes.
topic LiDAR
canopy density
vineyard
GPS
UTM coordinates
url http://www.mdpi.com/1424-8220/11/6/6237/
work_keys_str_mv AT meritxellqueralto georeferencedlidar3dvineplantationmapgeneration
AT jordillop georeferencedlidar3dvineplantationmapgeneration
AT emiliogil georeferencedlidar3dvineplantationmapgeneration
AT jordillorens georeferencedlidar3dvineplantationmapgeneration
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