10.60507/FK2/HYI2DS
Esser, Felix
Felix
Esser
https://orcid.org/0000-0003-3119-8585
University of Bonn
Klingbeil, Lasse
Lasse
Klingbeil
https://orcid.org/0000-0002-1941-150X
University of Bonn
Kuhlmann, Heiner
Heiner
Kuhlmann
https://orcid.org/0009-0004-9758-7721
University of Bonn
FieldPheno4D
The Multi-temporal, Multi-Crop dataset of High-Resolution 3D Point Clouds captured in the Field
bonndata
2026
Agricultural Sciences
Engineering
Esser, Felix
Felix
Esser
University of Bonn
André Cornelißen
André
Cornelißen
2026-03-19
2026-05-27
2023-05-16/2023-08-21
2023-05-16/2023-08-21
3D Point Clouds
10.60507/FK2/HYI2DS/6MVDDB
10.60507/FK2/HYI2DS/TTWZNL
10.60507/FK2/HYI2DS/P1IBUD
10.60507/FK2/HYI2DS/TFDGWV
10.60507/FK2/HYI2DS/XIRWOM
10.60507/FK2/HYI2DS/GG7AOE
10.60507/FK2/HYI2DS/NBEUHV
10.60507/FK2/HYI2DS/YUALBT
10.60507/FK2/HYI2DS/CFG2WT
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application/pdf
application/zip
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1.0
Creative Commons Attribution 4.0 International License.
This dataset contains high-quality 4D point clouds of multiple crop species (bean, wheat, corn, sugar beet, potato, and brassica) acquired using a specialized field phenotyping robot. The platform is equipped with two industrial-grade laser triangulation scanners (micrometer precision) and a centimeter-accurate georeferencing system comprising RTK GNSS and an inertial navigation system (INS), enabling precise multi-temporal registration of 3D point clouds. High quality is defined by sub-millimeter point precision, sub-millimeter spatial resolution, centimeter-level georeferencing accuracy, and high consistency between the two scanners. The dataset is organized into individual crop plots containing single crop rows of each species, scanned with by the field robot. This dataset enables multi-temporal phenotypic trait determination at the single plant-organ scale under field conditions. The key novelty lies in the combination of field-based acquisition with high-quality reconstruction, addressing the quality limitations of existing datasets created in the field.
Phenorob Central Field Experiment, Campus Kleinaltendorf
DFG, German Research Foundation
EXC-2070 - 390732324
German Federal Ministry of Research, Technology and Space (BMFTR)
Robotics Institute Germany (RIG)