Change Detection in 4D Point Cloud Data
The 3DGeo research group develops methods for the automatic geographic analysis of dense timeseries of 3D point clouds captured with LiDAR or photogrammetry. These methods are used to understand, quantify and predict the dynamics of the natural and anthropogenic environment. In this project, the SSC provides a unified implementation of the developed methods in form of a Python package. Performance-critical parts of the library are written in performance-oriented, thread-parallel C++.
The development process can be followed here: https://github.com/ssciwr/py4dgeo
This project is funded through the 2021 SSC Open Call with a total of 5 months of developer time.
Applicant: Prof. Dr. Bernhard Höfle, Institute of Geography