Name
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 scanned by LiDAR using 0.5 degrees angular resolution and results showed an R-2 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 R-2 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. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.3390/rs9040377 | REMOTE SENSING |
Keywords | Field | DocType |
precision agriculture,field robotics,LiDAR,high-throughput phenotyping,crop surface model,plant height | Plant phenotyping,Spatial reference system,Remote sensing,Mean squared error,Precision agriculture,Angular resolution,Lidar,Throughput,Geology,Point cloud | Journal |
Volume | Issue | Citations |
9 | 4 | 6 |
PageRank | References | Authors |
0.55 | 12 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shangpeng Sun | 1 | 6 | 0.88 |
| Changying Li | 2 | 56 | 10.72 |
| Andrew H Paterson | 3 | 27 | 4.04 |