{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,29]],"date-time":"2026-06-29T10:04:58Z","timestamp":1782727498492,"version":"3.54.5"},"reference-count":44,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2017,4,18]],"date-time":"2017-04-18T00:00:00Z","timestamp":1492473600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100005825","name":"NIFA","doi-asserted-by":"publisher","award":["2017-67021-25928"],"award-info":[{"award-number":["2017-67021-25928"]}],"id":[{"id":"10.13039\/100005825","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>A LiDAR-based high-throughput phenotyping (HTP) system was developed for cotton plant phenotyping in the field. The HTP system consists of a 2D LiDAR and an RTK-GPS mounted on a high clearance tractor. The LiDAR scanned three rows of cotton plots simultaneously from the top and the RTK-GPS was used to provide the spatial coordinates of the point cloud during data collection. Configuration parameters of the system were optimized to ensure the best data quality. A height profile for each plot was extracted from the dense three dimensional point clouds; then the maximum height and height distribution of each plot were derived. In lab tests, single plants were scanned by LiDAR using 0.5\u00b0 angular resolution and results showed an R2 value of 1.00 (RMSE = 3.46 mm) in comparison to manual measurements. In field tests using the same angular resolution; the LiDAR-based HTP system achieved average R2 values of 0.98 (RMSE = 65 mm) for cotton plot height estimation; compared to manual measurements. This HTP system is particularly useful for large field application because it provides highly accurate measurements; and the efficiency is greatly improved compared to similar studies using the side view scan.<\/jats:p>","DOI":"10.3390\/rs9040377","type":"journal-article","created":{"date-parts":[[2017,4,18]],"date-time":"2017-04-18T11:22:04Z","timestamp":1492514524000},"page":"377","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":68,"title":["In-Field High-Throughput Phenotyping of Cotton Plant Height Using LiDAR"],"prefix":"10.3390","volume":"9","author":[{"given":"Shangpeng","family":"Sun","sequence":"first","affiliation":[{"name":"College of Engineering, University of Georgia, Athens, GA 30602, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2590-4797","authenticated-orcid":false,"given":"Changying","family":"Li","sequence":"additional","affiliation":[{"name":"College of Engineering, University of Georgia, Athens, GA 30602, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrew","family":"Paterson","sequence":"additional","affiliation":[{"name":"College of Agricultural and Environmental Sciences and Franklin College of Arts and Science, University of Georgia, Athens, GA 30602, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2017,4,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"17077","DOI":"10.3390\/rs71215870","article-title":"3D maize plant reconstruction based on georeferenced overlapping lidar point clouds","volume":"7","author":"Garrido","year":"2015","journal-title":"Remote Sens."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1505","DOI":"10.1016\/j.agrformet.2009.04.008","article-title":"Obtaining the three-dimensional structure of tree orchards from remote 2D terrestrial lidar scanning","volume":"149","author":"Llorens","year":"2009","journal-title":"Agric. 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