Qlunc: Quantification of lidar uncertainty

Python Jupyter Notebook Submitted 12 March 2021Published 28 October 2021
Review

Editor: @danielskatz (all papers)
Reviewers: @adi3 (all reviews), @antviro (all reviews)

Authors

Francisco Costa (0000-0003-1318-9677), Andrew Clifton (0000-0001-9698-5083), Nikola Vasiljevic (0000-0002-9381-9693), Ines Würth (0000-0002-1365-0243)

Citation

Costa et al., (2021). Qlunc: Quantification of lidar uncertainty. Journal of Open Source Software, 6(66), 3211, https://doi.org/10.21105/joss.03211

@article{Costa2021, doi = {10.21105/joss.03211}, url = {https://doi.org/10.21105/joss.03211}, year = {2021}, publisher = {The Open Journal}, volume = {6}, number = {66}, pages = {3211}, author = {Francisco Costa and Andrew Clifton and Nikola Vasiljevic and Ines Würth}, title = {Qlunc: Quantification of lidar uncertainty}, journal = {Journal of Open Source Software} }
Copy citation string · Copy BibTeX  
Tags

wind lidar lidar hardware uncertainty OpenScience OpenLidar digital twin

Altmetrics
Markdown badge

 

License

Authors of JOSS papers retain copyright.

This work is licensed under a Creative Commons Attribution 4.0 International License.

Creative Commons License

Public user content licensed CC BY 4.0 unless otherwise specified.
ISSN 2475-9066