3D Point Clouds of Trees and Apple Fruit Annotated with Thermal Data
Authors/Creators
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
Identifiers
Related works
- Is cited by
- Journal article: 10.34133/plantphenomics.0252 (DOI)
- Journal article: 10.1080/10942912.2024.2330494 (DOI)
Funding
Software
- Repository URL
- https://gitlab-extern.atb-potsdam.de/cracksense/3d_thermal_annotation
- Programming language
- Python
- Development Status
- Active