Published March 12, 2024 | Version v3

3D Point Clouds of Trees and Apple Fruit Annotated with Thermal Data

  • 1. ROR icon Leibniz Institute for Agricultural Engineering and Bioeconomy
  • 2. Julian-Maximilian University Würzburg

Description

The data set captures four measurements during fruit growth:  06/28/2022 (15:00), 07/12/2022 (15:00), 09/01/2022 (15:00), 09/06/2022 (13:00)

Additionally, diurnal courses are provided for three days:  

Date

Time

09/21

07:00, 08:00, 10:00, 12:00, 13:00, 18:00

09/22

07:00, 08:00, 10:00, 12:00, 13:00, 18:00

10/05

06:30, 07:00, 09:00, 10:00, 11:00, 16:00

 

The data set was measured in Blocks (A-D) of trees (T) on apple (A) fruit and is stored as compressed zip files, capturing raw, preprocessed, and manually recorded reference (ground truth) data.

1. zip files entitled Raw_YYYY_MM_DD_Block[A-C]-[R, L] for seasonal data and Raw_YYYY_MM_DD_BlockD-[R, L]_Hour__:__ for diel data

- raw data of LiDAR 3D point clouds - txt files

- raw image data by thermal camera - txt files

2. zip files entitled YYYY_MM_DD or DailyAcquisitions:

- preprocessed (merged) sensor data of temperature-annotated 3D point clouds of canopies - csv files

- preprocessed data, capturing manually segmented point clouds of temperature-annotated fruit - txt files

3. Microsoft Excel files entitled References and Weather data:

- raw data, representing reference data of fruit - xlsx file

- raw data of weather conditions - xlsx file

Files

2022_06_28.zip

Files (112.1 GB)

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Additional details

Additional titles

Subtitle
Seasonal and Diel Data

Related works

Is cited by
Journal article: 10.34133/plantphenomics.0252 (DOI)
Journal article: 10.1080/10942912.2024.2330494 (DOI)

Funding

European Union
ERA-NET Cofund on ICT-enabled agri-food systems - Project "Sunburn and HEat prediction in canopies for Evolving a warning Tech solution - SHEET" 86265

Software

Repository URL
https://gitlab-extern.atb-potsdam.de/cracksense/3d_thermal_annotation
Programming language
Python
Development Status
Active