3DFin
A free software for automatic computation of tree parameters in terrestrial point clouds.
https://github.com/3dfin/3dfin
Category: Biosphere
Sub Category: Forest Remote Sensing
Keywords from Contributors
forestry lidar-point-cloud
Last synced: about 21 hours ago
JSON representation
Repository metadata
3D Forest INventory
- Host: GitHub
- URL: https://github.com/3dfin/3dfin
- Owner: 3DFin
- License: gpl-3.0
- Created: 2023-02-24T11:35:56.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2025-02-17T20:35:34.000Z (2 months ago)
- Last Synced: 2025-04-06T02:02:40.024Z (22 days ago)
- Language: Python
- Homepage:
- Size: 10.4 MB
- Stars: 64
- Watchers: 3
- Forks: 7
- Open Issues: 14
- Releases: 26
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
README.md
Welcome to 3DFin: 3D Forest inventory's official repository!
3DFin is a free software for automatic computation of tree parameters in terrestrial point clouds. It offers the users a quick, ease-of-use interface to load their forest plots and generate tree metrics with just a few clicks.
Getting Started
Be sure to check the Documentation, which features detailed explanations on how the program works and an User Manual.
Also, the Tutorial covers the basics of 3DFin and is a great tool to get started.
Download
3DFin is freely available in 4 ways:
- As a CloudCompare plugin (Windows and Linux)
- As a QGIS plugin
- As a standalone program (Only in Windows)
- As a Python package (In Windows, Linux and macOS)
1. CloudCompare plugin
3DFin is available in Windows as a plugin in CloudCompare (2.13) thanks to CloudCompare PythonRuntime (see References). You can download the latest version CloudCompare (Windows installer version) including the 3DFin plugin here:
Simply install the latest version of CloudCompare and tick Python and 3DFin's checkbox during the installation:
To install 3DFin plugin, tick the 'Python plugin support' checkbox during CloudCompare installation.
For Linux, the plugin is embedded into the CloudCompare flatpak.
3DFin plugin in CloudCompare.
Running the plugin will open 3DFin's graphical user interface (GUI).
3DFin GUI. It is common to any version of 3DFin.
2. QGIS plugin
3DFin is also available as a plugin in QGIS. Please follow the instructions available here in order to test it.
Note that for now this does not provide much added value in comparison with CloudCompare and Standalone version of 3DFin.
3. Standalone program
3DFin is also available in Windows and macOS as a standalone program, which can be downloaded from here:
3DFin.exe
file is the Windows version while 3DFin
is the macOS version.
These binaries are built into Github servers and are thus unsigned and unverified. As consequences, while executing theses binaries your system may warn from security issues and should ask you to grant some permissions.
If you have a complete Python environment on your system, please consider installing 3DFin standalone via pip
package manager.
Older versions of 3DFin standalone may also be downloaded from Releases. From there, simply navigate to the desired version and click on 3DFin[.exe].
4. Python package (3DFin)
3DFin and its dependencies may be installed and launched in any OS (Windows, Linux and macOS) as a Python package:
pip install 3DFin
python -m three_d_fin
If you are a macOS or Linux user and you may want to try 3DFin, this is the way you should proceed.
pip
will also install a script entry point in your Python installation's bin|script directory, so alternatively you can launch 3DFin from the command line with:
3DFin[.exe]
Usage
CloudCompare plugin is the reccomended way of using 3DFin, as it provides enhanced features for visualisation of the results and exporting of the outputs (it allows to export the results as a CloudCompare native BIN file).
By default, running 3DFin (either the CloudCompare plugin or any version of 3DFin) will open a GUI window.
For batch processing you can use the CLI capabilities of 3DFin and running the following command:
3DFin[.exe] cli --help
will give you an overview of the available parameters.
Citing 3DFin
If you use 3DFin in your research, please cite the following paper:
Laino, D., Cabo, C., Prendes, C., Janvier, R., Ordonez, C., Nikonovas, T., Doerr, S., & Santin, C. (2024). 3DFin: a software for automated 3D forest inventories from terrestrial point clouds. Forestry: An International Journal of Forest Research. https://doi.org/10.1093/forestry/cpae020
Thank you for citing 3DFin in your work! Your citations help to support the continued development and maintenance of this software.
References
CloudCompare-PythonRuntime, by Thomas Montaigu: CloudCompare-PythonRuntime
Acknowledgement
3DFin has been developed at the Centre of Wildfire Research of Swansea University (UK) in collaboration with the Research Institute of Biodiversity (CSIC, Spain) and the Department of Mining Exploitation of the University of Oviedo (Spain).
Funding provided by the UK NERC project (NE/T001194/1):
'Advancing 3D Fuel Mapping for Wildfire Behaviour and Risk Mitigation Modelling'
and by the Spanish Knowledge Generation project (PID2021-126790NB-I00):
‘Advancing carbon emission estimations from wildfires applying artificial intelligence to 3D terrestrial point clouds’.
Owner metadata
- Name: 3DFin
- Login: 3DFin
- Email:
- Kind: organization
- Description:
- Website:
- Location:
- Twitter:
- Company:
- Icon url: https://avatars.githubusercontent.com/u/125979752?v=4
- Repositories: 1
- Last ynced at: 2023-04-27T12:38:43.231Z
- Profile URL: https://github.com/3DFin
GitHub Events
Total
- Create event: 1
- Release event: 1
- Issues event: 4
- Watch event: 11
- Issue comment event: 9
- Push event: 3
- Fork event: 2
Last Year
- Create event: 1
- Release event: 1
- Issues event: 4
- Watch event: 11
- Issue comment event: 9
- Push event: 3
- Fork event: 2
Committers metadata
Last synced: 7 days ago
Total Commits: 356
Total Committers: 4
Avg Commits per committer: 89.0
Development Distribution Score (DDS): 0.233
Commits in past year: 70
Committers in past year: 2
Avg Commits per committer in past year: 35.0
Development Distribution Score (DDS) in past year: 0.157
Name | Commits | |
---|---|---|
romain janvier | r****r@h****r | 273 |
3DFIN | 3****e@g****m | 55 |
Diego Laíño Rebollido | 6****r | 15 |
3DFIN | 1****N | 13 |
Committer domains:
Issue and Pull Request metadata
Last synced: 2 days ago
Total issues: 19
Total pull requests: 65
Average time to close issues: 14 days
Average time to close pull requests: 1 day
Total issue authors: 17
Total pull request authors: 2
Average comments per issue: 3.0
Average comments per pull request: 0.11
Merged pull request: 61
Bot issues: 0
Bot pull requests: 0
Past year issues: 14
Past year pull requests: 6
Past year average time to close issues: 17 days
Past year average time to close pull requests: 6 days
Past year issue authors: 12
Past year pull request authors: 2
Past year average comments per issue: 1.93
Past year average comments per pull request: 0.0
Past year merged pull request: 5
Past year bot issues: 0
Past year bot pull requests: 0
Top Issue Authors
- mRossi97 (2)
- Camiladom1234 (2)
- leonard-leo (1)
- Loris-L (1)
- VasilisAle (1)
- leestamm (1)
- julesmorel (1)
- fguerra06 (1)
- ander541 (1)
- nadeemali476 (1)
- ser1993 (1)
- KrisFRS (1)
- ashlynolah (1)
- yduguay-CGQ (1)
- AIMSURVEYS (1)
Top Pull Request Authors
- rjanvier (49)
- Diegolainor (16)
Top Issue Labels
- question (7)
- not_confirmed (4)
- documentation (1)
- wontfix (1)
- duplicate (1)
Top Pull Request Labels
Package metadata
- Total packages: 1
-
Total downloads:
- pypi: 1,362 last-month
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 19
- Total maintainers: 1
pypi.org: 3dfin
Automatic dendrometry and forest inventory for terrestrial point clouds, application package
- Homepage:
- Documentation: https://github.com/3DFin/3DFin#README.md
- Licenses: gpl-3.0
- Latest release: 0.4.1 (published 10 months ago)
- Last Synced: 2025-04-27T12:36:55.613Z (about 21 hours ago)
- Versions: 19
- Dependent Packages: 0
- Dependent Repositories: 0
- Downloads: 1,362 Last month
-
Rankings:
- Dependent packages count: 7.242%
- Downloads: 10.15%
- Average: 24.257%
- Forks count: 30.337%
- Stargazers count: 32.315%
- Dependent repos count: 41.24%
- Maintainers (1)
Score: 12.960446619506016