Please read first

  • Denoised versions of the clouds on this page have been processed with software SimpleTree in 2014/2015 for the referenced publication.
  • There is outdated result models as published in 2014/2015 here as well.

    Pinus massoniana - Pine 12 trees

P. massoniana is a coniferous tree species. Tree scans thereby includes leaf noise in form of needles. Larger wind occurrence, high resolution scans. Software allows fully automatic denoising and modeling of all twelve trees.

Published in

Non Destructive Method for Biomass Prediction Combining TLS Derived Tree Volume and Wood Density.

Research Site

Latitude 22°06'02''N
Longditude 106°45'01''E

Biomass results

Please refer to the named publication, tables are included.

Point Clouds

All files are saved in asc file format. Coordinates (x,y,z) and intensity value are white-space separated.
Pinus massoniana raw data, 12 clouds
Within less than thirty minutes raw data clouds have been automatically denoised and modeled. Some noise is left and models show errors.
Pinus massoniana automatically denoised data, 12 clouds
30 more minutes of manual noise deletion and all clouds could be automatically modeled. Pinus massoniana manual denoised data, 12 clouds
All files can also be opened with Cloud Compare.

Calculated Models

These are the PLY models from the computation used for publication result. Saved in PLY format and can be opened with Cloud Compare.
Pinus massoniana 12 - Models published
The models computed with SimpleTree:
Pinus massoniana 12 - Ply Models and Pinus massoniana 12 - csv Models fully automatically calculated with SimpleTree after the release of SimpleTree — An Efficient Open Source Tool to Build Tree Models from TLS Clouds.
The results are supposed to vary slightly from those published, as in a second run deviations have to be expected. The automatic parameter search in SimpleTree is a randomized brute force one.

    License - Creative Commons Non Commercial Share Alike 4.0

If not stated otherwise, all data on this page are published under the Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International license. License holder Jan Hackenberg.

Human readable summary of the license

You are free to:

  • Share — copy and redistribute the material in any medium or format.
  • Adapt — remix, transform, and build upon the material.
The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
  • Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
  • NonCommercial — You may not use the material for commercial purposes.
  • ShareAlike — If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.
  • No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
A link to the full license is given here.