Wheat height estimation using LiDAR in comparison to ultrasonic sensor and UAS

Wenan Yuan, Jiating Li, Madhav Bhatta, Yeyin Shi, P. Stephen Baenziger, Yufeng Ge

Research output: Contribution to journalArticlepeer-review

61 Scopus citations


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.

Original languageEnglish (US)
Article number3731
JournalSensors (Switzerland)
Issue number11
StatePublished - Nov 2 2018


  • Crop
  • Phenotyping
  • Plant breeding
  • Proximal sensing
  • Remote sensing

ASJC Scopus subject areas

  • Analytical Chemistry
  • Information Systems
  • Atomic and Molecular Physics, and Optics
  • Biochemistry
  • Instrumentation
  • Electrical and Electronic Engineering


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