Universitätssiegel
 
Funding
LOKI project, funded by the Federal Ministry for Education and Research (BMBF)

BMBF

Funding code: 03G0890A

Duration
2020 - 2023


SYSSIFOSS project, funded by the Deutsche Forschungsgemeinschaft(DFG, German Research Foundation)

BMBF

Project number: 411263134

Duration
2019 - 2022


VirtuaLearn3D project, funded by the Deutsche Forschungsgemeinschaft(DFG, German Research Foundation)

BMBF

Project number: 496418931

Duration
2022 - 2025

 

Contact
Bernhard Höfle
Institute of Geography, Heidelberg University

 

HELIOS++ - Heidelberg LiDAR Operations Simulator

HELIOS++ is hosted on GitHub with an extensive wiki.

News

Stay up-to-date by following HELIOS via our GIScience News Blog and on Twitter: #HELIOS #3DGeo.

New paper: Check out our latest paper where we make use of the pytreedb tree point cloud database and the HELIOS++ laser scanning simulator to generate realistic laser scanning data of forests.

HELIOS++

General Information

In 2020, HELIOS++ replaced the former version of HELIOS with a modern implementation in C++11, including Python bindings to allow easy use in existing workflows. The code and ready-for-use precompiled versions are hosted on GitHub. We invite interested researchers and developers to contribute to further development of this project by submitting pull requests. We also host an extensive wiki, where the complete functionality of HELIOS++ is documented.

Literature & How to cite HELIOS++

More information on HELIOS++ is available in our publication. If you use HELIOS++ in your work, please cite:

Secondary paper on virtual laser scanning simulation with HELIOS++ as a high performance computing challenge:

Citation as BibTex:

@article{heliosPlusPlus,
title = {Virtual laser scanning with HELIOS++: 
A novel take on ray tracing-based simulation 
of topographic full-waveform 3D laser scanning},
journal = {Remote Sensing of Environment},
volume = {269},
year = {2022},
issn = {0034-4257},
doi = {https://doi.org/10.1016/j.rse.2021.112772},
author = {Lukas Winiwarter and Alberto Manuel {Esmorís Pena}
and Hannah Weiser and Katharina Anders 
and Jorge {Martínez Sánchez} and Mark Searle and Bernhard Höfle}
}

Research

HELIOS++ and its predecessor have been used extensively in different research:

3DGeo Publications

Publications from Other Research Groups

Winiwarter et al. (2022) conducted a systematic literature review based on these publications (see above).

Background

Virtual laser scanning is a tool to create simulated point cloud data, as would be acquired by a LiDAR sensor. Such data may be used to complement real data, where data acquisition is not feasible due to economical or logistic constraints or where it is impossible, e.g. when simulating a sensor that does not exist. HELIOS++ allows the simulation of laser scanning on different platforms (airborne, UAV-based, terrestrial mobile and static) and using different data types to represent the 3D scene, including triangular meshes, digital elevation rasters, voxel grids and point clouds. The implementation in C++ allows for low runtimes and efficient memory usage, while the Python bindings pyhelios enable direct use of HELIOS++ from within Python scripts.

als_demo

HELIOS++ software modules (platform, scanner, scene, survey) and LiDAR simulation sequence.

Outreach

At the 2022 FOSSGISS conference on free open source software for geographic information systems, we presented AEOS, the QGIS Plugin that enables the usage of HELIOS++ in one of the most widely used GIS applications. Check out the demo session here and learn how to simulate your own point clouds!

Projects using HELIOS++

VirtuaLearn3D - Virtual Laser Scanning for Machine Learning Algorithms in Geographic 3D Point Cloud Analysis

We investigate the close coupling of learning algorithms with virtual laser scanning and real point cloud data to use benefits of both 1) the realism of real − but sparse − training data and 2) the multitude of options of object-sensor interactions that can be generated with VLS.

SYSSIFOSS - Synthetic structural remote sensing data for improved forest inventory models

LOKI - Airborne Observation of Critical Infrastructure

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