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

Garrido Izard, Miguel; Paraforos, Dimitris S.; Reiser, David; Vázquez Arellano, Manuel; Griepentrog, Hans W. y 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.

Descripción

Título: 3D Maize Plant Reconstruction Based on Georeferenced Overlapping LiDAR Point Clouds
Autor/es:
  • Garrido Izard, Miguel
  • Paraforos, Dimitris S.
  • Reiser, David
  • Vázquez Arellano, Manuel
  • Griepentrog, Hans W.
  • Valero Ubierna, Constantino
Tipo de Documento: Artículo
Título de Revista/Publicación: Remote Sensing
Fecha: 17 Diciembre 2015
Volumen: 7
Materias:
Palabras Clave Informales: LiDAR; total station; crop characterization; scan orientation; point cloud overlapping; ICP; registration; 3D; maize plants; plant phenotyping
Escuela: E.T.S.I. Agrónomos (UPM) [antigua denominación]
Departamento: Ingeniería Agroforestal
Grupo Investigación UPM: Técnicas Avanzadas en Agroalimentación LPF-TAGRALIA
Licencias Creative Commons: Ninguna

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Resumen

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.

Proyectos asociados

TipoCódigoAcrónimoResponsableTítulo
FP7NMP-CP-IP 245986-2RHEAPablo González de Santos, CAR-CSICRobot fleets for highly effective agriculture and forestry.
Comunidad de MadridS2013/ABI-2747TAVS-CMVISAVET, UCMTecnologías Avanzadas en Vigilancia Sanitaria

Más información

ID de Registro: 40018
Identificador DC: http://oa.upm.es/40018/
Identificador OAI: oai:oa.upm.es:40018
Identificador DOI: 10.3390/rs71215870
URL Oficial: http://www.mdpi.com/2072-4292/7/12/15870
Depositado por: Profesor Constantino Valero Ubierna
Depositado el: 21 Abr 2016 12:02
Ultima Modificación: 21 Abr 2016 12:02
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