------------------------------------------------------------------------------------------------------------- This file was generated on 2026-05-26 by Felix Esser ------------------------------------------------------------------------------------------------------------- A GENERAL INFORMATION ------------------------------------------------------------------------------------------------------------- 1. Title of the dataset: FieldPheno4D 2. Brief description of the research project and its aims: 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. 3. Author Information A. Investigator Contact Information Name: Felix Esser Institution: Institute of Geodesy and Geoinformation Address: Nussallee 17 Email: esser@igg.uni-bonn.de B. Project Supervisor (Principal Investigator 1) Contact Information Name: Lasse Klingbeil Institution: Institute of Geodesy and Geoinformation Address: Nussallee 17 Email: klingbeil@igg.uni-bonn.de C. Project Supervisor (Principal Investigator 2) Contact Information Name: Heiner Kuhlmann Institution: Institute of Geodesy and Geoinformation Address: Nussallee 17 Email: klingbeil@igg.uni-bonn.de D. In case of questions related to this dataset, please contact: Name: Felix Esser Institution: Institute of Geodesy and Geoinformation Address: Nussallee 17 Email: esser@igg.uni-bonn.de 4. Date of data collection: 2023-05-16 - 23-08-21 5. Information about funding sources that supported the collection of the data: This work has been funded by been funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy, EXC-2070 - 390732324 (PhenoRob).This work has been partially supported by the German Federal Ministry of Research, Technology and Space (BMFTR) under the Robotics Institute Germany (RIG). 6. Language of the dataset: English 7. Geographic location of data collection: Campus Klein Altendorf, Meckenheimer Straße 42C, 53359 Rheinbach ------------------------------------------------------------------------------------------------------------- B DATA & FILE OVERVIEW ------------------------------------------------------------------------------------------------------------- 1. File List: FieldPheno4D_timetable.pdf: Timetable containing dates the point cloud were captured Plot01.zip: 18 point clouds of bean plants Plot02.zip: 17 point clouds of bean plants Plot03.zip: 9 point clouds of bean plants Plot04.zip: 5 point clouds of bean plants Plot05.zip: 13 point clouds of bean plants Plot06.zip: 15 point clouds of bean plants Plot07.zip: 18 point clouds of bean plants The unzipped folders have the following structure: PlotXX.zip/ ├── PlotXX/ ├──YYMMDD.las ├──YYMMDD.las ├──YYMMDD.las ├──YYMMDD.las ├──YYMMDD.las ├── ... ├──PXX_orthophoto.png ├──dem/: Digital Elevation Model (DEM) visualizatio of the point clouds ├──png/ ├──bboxes/: visualization of the multi-temporal bounding boxes of the point clouds YYMMDD.las ├──combined/: combined images (.png) showing the nadir, xz-axis and yz-axis perspective on the point cloud ├──nadir/: nadir images (.png) on the point cloud ├──side_xz/: xz-axis images (.png) on the point cloud ├──side_yz/: yz-axis images (.png) on the point cloud 2. Are there multiple versions of the dataset? no ------------------------------------------------------------------------------------------------------------- C SHARING/ACCESS INFORMATION ------------------------------------------------------------------------------------------------------------- 1. Was data derived from another source? no 2. Licenses/restrictions placed on the data: CC BY 4.0 3. Links to publications that cite or use the data: - 4. Link to dataset website: https://felixesser.github.io/FieldPheno4D/ ------------------------------------------------------------------------------------------------------------- D METHODOLOGICAL INFORMATION ------------------------------------------------------------------------------------------------------------- 1. Description of methods used for collection/generation of data: The dataset was generated using a specialized field phenotyping robot as described by our paper: https://doi.org/10.1109/MRA.2023.3321402. The robot compromises a centimeter-precise georeferencing system fusing GNSS (Global Navigation Satellite System) and IMU (Inertial Measurement Unit) data, and a high-precision dual laser scanning system featuring two industrial-grade laser triangulation scanner. The processing of the ras laser measurements also needs a kinematic calibration procedure. Its implementation can be found here: https://github.com/Engineering-Geodesy-Bonn/KinScanCal 2. Methods for processing the data: To open/edit the .las point clouds we recommend to use the open source software CloudCompare: https://www.cloudcompare.org/. The point clouds contain the additional scalar field of the height, which was computed using a DEM pipeline. This pipeline can be found here: https://github.com/felixesser/FieldPheno4D 3. Instrument- and/or software-specific information needed to interpret the data: CloudCompare 4. People involved in sample collection, processing, analysis and/or submission: Andre Cornelißen 5. Describe any quality-assurance procedures performed on the data: - 6. Standards and calibration information: - 7. Environmental/experimental conditions: - ------------------------------------------------------------------------------------------------------------- E DATA-SPECIFIC INFORMATION FOR: .las point clouds in the unzipped .zip files ------------------------------------------------------------------------------------------------------------- 1. Variable list including full names and definitions (please spell out abbreviated words) of column headings for tabular data: - 2. Units of measurement used: Coordinates of the point clouds are in meter in the UTM, 32N Zone, EPSG:25832, WGS84 3. Missing data codes/symbols: - 4. Specialized formats or other abbreviations used: -