Wheat Height Estimation Using LiDAR in Comparison to Ultrasonic Sensor and UAS

Authors

Wenan Yuan, University of Nebraska-LincolnFollow
Jiating Li, University of Nebraska-LincolnFollow
Madhav Bhatta, University of Nebraska-LincolnFollow
Yeyin Shi, University of Nebraska-LincolnFollow
P. Stephen Baenziger, University of Nebraska-LincolnFollow
Yufeng Ge, University of Nebraska-LincolnFollow

ORCID IDs

0000-0002-6300-2973

0000-0002-4959-0481

0000-0002-9109-6954

Document Type

Article

Date of this Version

2018

Citation

Sensors 2018, 18, 3731

Comments

Copyright 2018 by the authors.

Open access

doi:10.3390/s18113731

Abstract

As one of the key crop traits, plant height is traditionally evaluated manually, which can be slow, laborious and prone to error. Rapid development of remote and proximal sensing technologies in recent years allows plant height to be estimated in more objective and efficient fashions, while research regarding direct comparisons between different height measurement methods seems to be lagging. In this study, a ground-based multi-sensor phenotyping system equipped with ultrasonic sensors and light detection and ranging (LiDAR) was developed. Canopy heights of 100 wheat plots were estimated five times during a season by the ground phenotyping system and an unmanned aircraft system (UAS), and the results were compared to manual measurements. Overall, LiDAR provided the best results, with a root-mean-square error (RMSE) of 0.05 m and an R² of 0.97. UAS obtained reasonable results with an RMSE of 0.09 m and an R² of 0.91. Ultrasonic sensors did not perform well due to our static measurement style. In conclusion, we suggest LiDAR and UAS are reliable alternative methods for wheat height evaluation.