Bernhard HöfleApr 18, 2023

From forest stand information to laser scanning #pointclouds without a real scanner?

📢 📰 In our new paper by Schäfer et al. (https://doi.org/10.1093/forestry/cpad006) we generate realistic laser scanning data of forests by combining
➡️ forest stand information ℹ️
➡️ the #pytreedb tree point cloud database 🌳(https://pytreedb.geog.uni-heidelberg.de)
➡️ and the laser scanning simulator #HELIOS++ 🖥️(https://github.com/3dgeo-heidelberg/helios)

Such simulated data may be used in sensitivity analyses, for algorithm development, and for #machinelearning.

Generating synthetic laser scanning data of forests by combining forest inventory information, a tree point cloud database and an open-source laser scanning simulator

Abstract. Airborne laser scanning (ALS) data are routinely used to estimate and map structure-related forest inventory variables. The further development, refin

OUP Academic
Bernhard HöfleJan 19, 2023

📢 1st release (v1.0.0) of #pytreedb, our #python #package providing an object-based database to store trees that were captured as 3D point clouds. 🌳

Test it: pip install pytreedb

DOI: https://doi.org/10.5281/zenodo.7551309

GitHub: https://github.com/3dgeo-heidelberg/pytreedb
#syssifoss #opensource

pytreedb - library for point clouds of tree vegetation objects.

First public release of pytreedb and pytreedb_server. Documentation can be found at https://pytreedb.readthedocs.io/.

Zenodo