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HELIOS

Heidelberg LiDAR Operations Simulator (HELIOS)

HELIOS is a software package for interactive real-time simulation and visualization of terrestrial, mobile and airborne laser scanning surveys written in Java. Official website: https://www.uni-heidelberg.de/helios

HELIOS

Table of Contents

Install

The pre-built project is available here with a test scene and survey. Note that for faster simulations building the project is recommended.

To build the project, first install the dependencies, then compile the source code, and finally execute it.

Requisites

  • Oracle Java 1.8
  • Maven 3

You can use java -version and mvn -v to check if you already have installed those on your computer.

Linux/Ubuntu:

They can be installed by:

sudo apt-get install oracle-java8-installer maven

Windows:

In Windows installation is less straightforward:

  • Java JDK
    1. Download the Java JDK 8 and install it
    2. Create the environment variable JAVA_HOME to point to the JDK folder
      (e .g: JAVA_HOME=C:\Program Files\Java\jdk1.8.0_151)
    3. Add to the PATH the value %JAVA_HOME%\bin
  • Maven
    1. Download the Maven binary zip
    2. Unzip it and move it to the desired folder (e. g. C:\apache-maven-3.5.2)
    3. Add to the PATH the bin folder inside (e. g. C:\apache-maven-3.5.2\bin)

Compilation

Download the source code from this web site or from git:

git clone https://github.com/GIScience/helios.git

Then inside the root folder simply execute:

mvn package

Eclipse IDE

To add this project to Eclipse go to File > Import > Existing Maven Projects and select helios folder.
You may also want to disable the spell checker: right click in the project > Checkstyle > Deactivate Checkstyle

Usage

HELIOS supports both single-ray and full-waveform simulations. Currently the default mode is the full-waveform. The selection between this two methods is done in the source code when creating the detector object in XmlAssetsLoader.java.

Input

The argument of the program is the survey XML file, also the 3D models of the scene pointed in the survey are needed. See Wiki: Basic input data for further details.

This Blender addon can be used to convert Blender scenes to HELIOS scenes.

Execution

From the root folder run:

java -jar target/helios.jar <survey-file>

To run the example survey:

java -jar target/helios.jar data/surveys/demo/tls_arbaro_demo.xml 

To use the batch mode (no visualization):

java -jar target/helios.jar <survey-file> headless

Output

Output files are generated inside output/Survey Playback folder.

  • Point cloud: File named legxxx_points.xyz separated by spaces where xxx is the leg number.
    Fields:
    X Y Z I ECHO_WIDTH RN NOR FWF_ID OBJ_ID
    Example:
    -4.615 15.979 2.179 4.0393 1.4317 1 1 214275 1
  • Waveform: File named legxxx_points.xyzfullwave.txt separated by spaces where xxx is the leg number.
    See FWF.md for further details.

Documentation

See Wiki.

Research using HELIOS

Backes, D., Smigaj, M., Schimka, M., Zahs, V., Grznárová, A., and Scaioni, M. (2020): River morphology monitoring of a small-scale alpine riverbed using drone photogrammetry and LiDAR, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2020, 1017–1024, DOI: 10.5194/isprs-archives-XLIII-B2-2020-1017-2020.

Li, L., Mu, X., Soma, M., Wan,P., Qi, J., Hu, R., Zhang, W., Tong, Y., Yan, G. (2020): An Iterative-Mode Scan Design of Terrestrial Laser Scanning in Forests for Minimizing Occlusion Effects, IEEE Transactions on Geoscience and Remote Sensing, DOI: 10.1109/TGRS.2020.3018643.

Park, M., Baek, Y., Dinare, M., Lee, D., Park, K.-H., Ahn, J., Kim, D., Medina, J., Choi, W.-J., Kim, S., Zhou, C., Heo, J. & Lee, K. (2020): Hetero-integration enables fast switching time-of-flight sensors for light detection and ranging. In: Sci Rep 10, 2764 (2020), pp. 1-8. DOI: 10.1038/s41598-020-59677-x.

Wang, D. (2020): Unsupervised semantic and instance segmentation of forest point clouds. In: ISPRS Journal of Photogrammetry and Remote Sensing 165 (2020), pp. 86-97. DOI: 10.1016/j.isprsjprs.2020.04.020.

Wang, D., Schraik, D., Hovi, A., Rautiainen, M. (2020): Direct estimation of photon recollision probability using terrestrial laser scanning. In: Remote Sensing of Environment 247 (2020), pp. 1-12. DOI: 10.1016/j.rse.2020.111932.

Zhu, X., Liu, J., Skidmore, A.K., Premier, J., Heurich, M. (2020): A voxel matching method for effective leaf area index estimation in temperate deciduous forests from leaf-on and leaf-off airborne LiDAR data. In: Remote Sensing of Environment, 240. DOI: 10.1016/j.rse.2020.111696.

Lin, C.-H. & Wang, C.-K. (2019): Point Density Simulation for ALS Survey. In: Proceedings of the 11th International Conference on Mobile Mapping Technology (MMT2019), Shenzhen, China. pp. 157-160.

Liu, J., Skidmore, A.K., Wang, T., Zhu, X., Premier, J., Heurich, M., Beudert, B. & Jones, S. (2019): Variation of leaf angle distribution quantified by terrestrial LiDAR in natural European beech forest. In: ISPRS Journal of Photogrammetry and Remote Sensing, 148, pp. 208-220. DOI: 10.1016/j.isprsjprs.2019.01.005.

Liu, J., Wang, T., Skidmore, A.K., Jones, S., Heurich, M., Beudert, B. & Premier, J. (2019): Comparison of terrestrial LiDAR and digital hemispherical photography for estimating leaf angle distribution in European broadleaf beech forests. In: ISPRS Journal of Photogrammetry and Remote Sensing, 158, pp. 76-89. DOI: 10.1016/j.isprsjprs.2019.09.015.

Martínez Sánchez, J., Váquez Álvarez, Á., López Vilariño, D., Fernández Rivera, F., Cabaleiro Domínguez, J.C., Fernández Pena, T. (2019): Fast Ground Filtering of Airborne LiDAR Data Based on Iterative Scan-Line Spline Interpolation. In: Remote Sensing, 11(19), pp. 23 (2256). DOI: 10.3390/rs11192256.

Previtali, M., Díaz-Vilariño, L., Scaioni, M. & Frías Nores, E. (2019): Evaluation of the Expected Data Quality in Laser Scanning Surveying of Archaeological Sites. In: 4th International Conference on Metrology for Archaeology and Cultural Heritage, Florence, Italy, 4-6 December 2019, pp. 19-24.

Xiao, W., Zaforemska, A., Smigaj, M., Wang, Y. & Gaulton, R. (2019): Mean Shift Segmentation Assessment for Individual Forest Tree Delineation from Airborne Lidar Data. In: Remote Sensing, 11(11), pp. 19 (1263). DOI: 10.3390/rs11111263.

Zhang, Z., Li, J., Guo, Y., Yang, C., & Wang, C. (2019): 3D Highway Curve Reconstruction From Mobile Laser Scanning Point Clouds. In: IEEE Transactions on Intelligent Transportation Systems. DOI: 10.1109/TITS.2019.2946259.

Hämmerle, M., Lukač, N., Chen, K.-C., Koma, Zs., Wang, C.-K., Anders, K., & Höfle, B. (2017): Simulating Various Terrestrial and UAV LiDAR Scanning Configurations for Understory Forest Structure Modelling. In: ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2/W4, pp. 59-65. DOI: 10.5194/isprs-annals-IV-2-W4-59-2017.

Rebolj, D., Pučko, Z., Babič, N.Č., Bizjak, M. & Mongus, D. (2017). Point cloud quality requirements for Scan-vs-BIM based automated construction progress monitoring. In: Automation in Construction, 84, pp. 323-334. DOI: 10.1016/j.autcon.2017.09.021.

Bechtold, S., Hämmerle, M. & Höfle, B. (2016): Simulated full-waveform laser scanning of outcrops for development of point cloud analysis algorithms and survey planning: An application for the HELIOS lidar simulation framework. In: Proceedings of the 2nd Virtual Geoscience Conference, Bergen, Norway, 21-23 September 2016, pp 57-58.

Authorship

3DGeo Research Group
Institute of Geography
Heidelberg University

http://www.uni-heidelberg.de/3dgeo

Citation

Bechtold, S. & Höfle, B. (2016): HELIOS: A Multi-Purpose LiDAR Simulation Framework for Research, Planning and Training of Laser Scanning Operations with Airborne, Ground-Based Mobile and Stationary Platforms. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. III-3, pp. 161-168. DOI: 10.5194/isprs-annals-III-3-161-2016

If you use HELIOS in your work, please cite:

@Article{isprs-annals-III-3-161-2016,
AUTHOR = {Bechtold, S. and H\"ofle, B.},
TITLE = {{HELIOS}: A Multi-Purpose LiDAR Simulation Framework for Research, Planning and Training of Laser Scanning Operations with Airborne, Ground-Based Mobile and Stationary Platforms},
JOURNAL = {ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences},
VOLUME = {III-3},
YEAR = {2016},
PAGES = {161--168},
URL = {https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/III-3/161/2016/},
DOI = {10.5194/isprs-annals-III-3-161-2016}
}

We are happy if you are using HELIOS in your work - let us know!

Maintainers

@sebastian-bechtold @nlukac @kathapand @deuxbot @lrg-bhoefle

The first HELIOS version with full-waveform support is available in this repository maintained by @nlukac.

License

See LICENSE.md.

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HELIOS - the Heidelberg LiDAR Operations Simulator - is a software package for interactive real-time simulation and visualisation of terrestrial, mobile and airborne laser scan surveys written in Java.

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