publication . Article . 2017

In-Field High-Throughput Phenotyping of Cotton Plant Height Using LiDAR

Shangpeng Sun; Changying Li; Andrew H. Paterson;
Open Access
  • Published: 18 Apr 2017 Journal: Remote Sensing, volume 9, page 377 (eissn: 2072-4292, Copyright policy)
  • Publisher: MDPI AG
Abstract
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 scann...
Subjects
free text keywords: Mean squared error, Lidar, Remote sensing, Geology, Angular resolution, Precision agriculture, Throughput, Point cloud, Plant phenotyping, Spatial reference system, field robotics, high-throughput phenotyping, crop surface model, plant height, Science, Q
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publication . Article . 2017

In-Field High-Throughput Phenotyping of Cotton Plant Height Using LiDAR

Shangpeng Sun; Changying Li; Andrew H. Paterson;