3D Maize Plant Reconstruction Based on Georeferenced Overlapping LiDAR Point Clouds

Garrido Izard, Miguel and Paraforos, Dimitris S. and Reiser, David and Vázquez Arellano, Manuel and Griepentrog, Hans W. and Valero Ubierna, Constantino (2015). 3D Maize Plant Reconstruction Based on Georeferenced Overlapping LiDAR Point Clouds. "Remote Sensing", v. 7 (n. 12); p. 15870. ISSN 2072-4292. https://doi.org/10.3390/rs71215870.

Description

Title: 3D Maize Plant Reconstruction Based on Georeferenced Overlapping LiDAR Point Clouds
Author/s:
  • Garrido Izard, Miguel
  • Paraforos, Dimitris S.
  • Reiser, David
  • Vázquez Arellano, Manuel
  • Griepentrog, Hans W.
  • Valero Ubierna, Constantino
Item Type: Article
Título de Revista/Publicación: Remote Sensing
Date: 17 December 2015
ISSN: 2072-4292
Volume: 7
Subjects:
Freetext Keywords: LiDAR; total station; crop characterization; scan orientation; point cloud overlapping; ICP; registration; 3D; maize plants; plant phenotyping
Faculty: E.T.S.I. Agrónomos (UPM) [antigua denominación]
Department: Ingeniería Agroforestal
UPM's Research Group: Técnicas Avanzadas en Agroalimentación LPF-TAGRALIA
Creative Commons Licenses: None

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Abstract

3D crop reconstruction with a high temporal resolution and by the use of non-destructive measuring technologies can support the automation of plant phenotyping processes. Thereby, the availability of such 3D data can give valuable information about the plant development and the interaction of the plant genotype with the environment. This article presents a new methodology for georeferenced 3D reconstruction of maize plant structure. For this purpose a total station, an IMU, and several 2D LiDARs with different orientations were mounted on an autonomous vehicle. By the multistep methodology presented, based on the application of the ICP algorithm for point cloud fusion, it was possible to perform the georeferenced point clouds overlapping. The overlapping point cloud algorithm showed that the aerial points (corresponding mainly to plant parts) were reduced to 1.5%–9% of the total registered data. The remaining were redundant or ground points. Through the inclusion of different LiDAR point of views of the scene, a more realistic representation of the surrounding is obtained by the incorporation of new useful information but also of noise. The use of georeferenced 3D maize plant reconstruction at different growth stages, combined with the total station accuracy could be highly useful when performing precision agriculture at the crop plant level.

Funding Projects

TypeCodeAcronymLeaderTitle
FP7245986RHEAPablo González de Santos, CAR-CSICRobot fleets for highly effective agriculture and forestry.
Madrid Regional GovernmentS2013/ABI-2747TAVS-CMVISAVET, UCMTecnologías Avanzadas en Vigilancia Sanitaria

More information

Item ID: 40018
DC Identifier: http://oa.upm.es/40018/
OAI Identifier: oai:oa.upm.es:40018
DOI: 10.3390/rs71215870
Official URL: http://www.mdpi.com/2072-4292/7/12/15870
Deposited by: Profesor Constantino Valero Ubierna
Deposited on: 21 Apr 2016 12:02
Last Modified: 04 Jun 2019 14:52
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