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FieldPheno4D

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Important usage condition: Use and redistribution are governed by CC BY 4.0. Review and comply with the license before using the data.
Persistent identifier
doi:10.60507/FK2/HYI2DS
Published version
1.0
Publication date
2026-05-27
License
CC BY 4.0

Description

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.

Creators

Keywords

3D Point Clouds, Plant Phenotyping, 3D Reconstruction

Files

Before downloading: Use and redistribution are governed by CC BY 4.0. Review and comply with the license before using the data.
FileTypeBytesChecksum
FIeldPheno4D_timetable.pdfapplication/pdf119174MD5 85f090bf03a97bdd21f37ace18043523
Plot01.zipapplication/zip8406722571MD5 e6f91ad1f88bcdda35632e9333ba281c
Plot03.zipapplication/zip4136520344MD5 657d3e672e985e01d5545f9a11507489
Plot02.zipapplication/zip8938712972MD5 385a94dc1b13d6c0a50a06cb9fd8e9c6
Plot04.zipapplication/zip1869666274MD5 1c926af3bd7d5705f83fb27460134864
Plot05.zipapplication/zip5013379033MD5 eb9731f60bbe2e1487e61b288fa2ea03
Plot06.zipapplication/zip5366742798MD5 21ccc5641695ef57522a1de1a59c445e
Plot07.zipapplication/zip7701209853MD5 810efe1f3a1bf9f86cd700393dbe4743
Esser_FieldPheno4D_Readme.txttext/plain7437MD5 6ae190ec0e434c37741bb14acb6521df

Citation

Esser, Felix; Klingbeil, Lasse; Kuhlmann, Heiner, 2026-05-27, FieldPheno4D, doi:10.60507/FK2/HYI2DS, V1.0

Additional Dataverse fields

Id665
Dataset Typedataset
Internal Version Number43
Latest Version Publishing StateRELEASED
Release Time2026-05-27T08:19:45Z
Create Time2026-03-19T15:31:23Z
Citation Date2026-05-27
File Access RequestTrue

Export metadata

Static metadata exports available for this published dataset version:

Complete Dataverse metadata

Citation Metadata

Title title
FieldPheno4D
Subtitle subtitle
The Multi-temporal, Multi-Crop dataset of High-Resolution 3D Point Clouds captured in the Field
Alternative URL alternativeURL
https://felixesser.github.io/FieldPheno4D/
Author author
  1. Author Name
    Esser, Felix
    Author Affiliation
    University of Bonn
    Author Identifier Scheme
    ORCID
    Author Identifier
    Type Name
    authorIdentifier
    Multiple
    False
    Type Class
    primitive
    Value
    https://orcid.org/0000-0003-3119-8585
    Expandedvalue
    Person Name
    Esser, Felix
    @id
    https://orcid.org/0000-0003-3119-8585
    Scheme
    ORCID
    @type
    https://schema.org/Person
  2. Author Name
    Klingbeil, Lasse
    Author Affiliation
    University of Bonn
    Author Identifier Scheme
    ORCID
    Author Identifier
    Type Name
    authorIdentifier
    Multiple
    False
    Type Class
    primitive
    Value
    https://orcid.org/0000-0002-1941-150X
    Expandedvalue
    Person Name
    Klingbeil, Lasse
    @id
    https://orcid.org/0000-0002-1941-150X
    Scheme
    ORCID
    @type
    https://schema.org/Person
  3. Author Name
    Kuhlmann, Heiner
    Author Affiliation
    University of Bonn
    Author Identifier Scheme
    ORCID
    Author Identifier
    Type Name
    authorIdentifier
    Multiple
    False
    Type Class
    primitive
    Value
    https://orcid.org/0009-0004-9758-7721
    Expandedvalue
    Person Name
    Kuhlmann, Heiner
    @id
    https://orcid.org/0009-0004-9758-7721
    Scheme
    ORCID
    @type
    https://schema.org/Person
Dataset Contact datasetContact
  1. Dataset Contact Name
    Esser, Felix
    Dataset Contact Affiliation
    University of Bonn
    Dataset Contact Email
    esserfe@uni-bonn.de
Ds Description dsDescription
  1. Ds Description Value
    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.
Subject subject
  1. Agricultural Sciences
  2. Engineering
Subject Refinement subjectRefinement
  1. Subject Refinement Value
    3D Plant Phenotyping
Free Keyword freeKeyword
  1. Free Keyword Value
    3D Point Clouds
  2. Free Keyword Value
    Plant Phenotyping
  3. Free Keyword Value
    3D Reconstruction
Language language
  1. English
Production Place productionPlace
Phenorob Central Field Experiment, Campus Kleinaltendorf
Contributor contributor
  1. Contributor Type
    Data Collector
    Contributor Name
    André Cornelißen
Grant Number grantNumber
  1. Grant Number Agency
    DFG, German Research Foundation
    Grant Number Value
    EXC-2070 - 390732324
  2. Grant Number Agency
    German Federal Ministry of Research, Technology and Space (BMFTR)
    Grant Number Value
    Robotics Institute Germany (RIG)
Depositor depositor
Esser, Felix
Date Of Deposit dateOfDeposit
2026-03-19
Time Period Covered timePeriodCovered
  1. Time Period Covered Start
    2023-05-16
    Time Period Covered End
    2023-08-21
Date Of Collection dateOfCollection
  1. Date Of Collection Start
    2023-05-16
    Date Of Collection End
    2023-08-21
Kind Of Data kindOfData
  1. 3D Point Clouds

Computational Workflow Metadata

Workflow Code Repository workflowCodeRepository
  1. https://github.com/Engineering-Geodesy-Bonn/SlidingCalibration

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