To cite PDAL in publications use:

PDAL Contributors, 2022. PDAL Point Data Abstraction Library.

A BibTeX entry for LaTeX users is

author = {PDAL Contributors},
title = {PDAL Point Data Abstraction Library},
month = aug,
year = 2022,
doi = {10.5281/zenodo.2616780},

A paper about PDAL by the team, “PDAL: An open source library for the processing and analysis of point clouds”, is available at [Butler2021].



Bartels, Marc, and Hong Wei. “Threshold-free object and ground point separation in LIDAR data.” Pattern recognition letters 31.10 (2010): 1089-1099.


Breunig, M.M., Kriegel, H.-P., Ng, R.T., Sander, J., 2000. LOF: Identifying Density-Based Local Outliers. Proc. 2000 Acm Sigmod Int. Conf. Manag. Data 1–12.


Butler, H. Chambers, B. Hartzell, P. Glennie, C. PDAL: An open source library for the processing and analysis of point clouds. Computers & Geosciences, Volume 148, 2021, 104680, ISSN 0098-3004,


Chen, Ziyue et al. “Upward-Fusion Urban DTM Generating Method Using Airborne Lidar Data.” ISPRS Journal of Photogrammetry and Remote Sensing 72 (2012): 121–130.


Cook, Robert L. “Stochastic sampling in computer graphics.” ACM Transactions on Graphics (TOG) 5.1 (1986): 51-72.


Demantké J., Mallet C., David N., Vallet, B. “Dimensionality Based Scale Selection in 3d LIDAR Point Clouds.” Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci, XXXVIII-5/W12, 97-102, 2011


Dippé, Mark AZ, and Erling Henry Wold. “Antialiasing through stochastic sampling.” ACM Siggraph Computer Graphics 19.3 (1985): 69-78.


Ester, Martin, et al. “A density-based algorithm for discovering clusters in large spatial databases with noise.” Kdd. Vol. 96. No. 34. 1996.


Fischer, Kaspar, Bernd Gärtner, and Martin Kutz. “Fast Smallest-Enclosing-Ball Computation in High Dimensions.” 26473 (2010): 630–641. Web.


Guinard S., Landrieu L. “Weakly Supervised Segmented-Aided Classification of Urban Scenes From 3D LIDAR Point Clouds.” Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1/W1, 151-157, 2017


Kazhdan, Michael, Matthew Bolitho, and Hugues Hoppe. “Poisson surface reconstruction.” Proceedings of the fourth Eurographics symposium on Geometry processing. Vol. 7. 2006.


Li, Wenkai, et al. “A new method for segmenting individual trees from the lidar point cloud.” Photogrammetric Engineering & Remote Sensing 78.1 (2012): 75-84.


Limberger, Frederico A., and Manuel M. Oliveira. “Real-Time Detection of Planar Regions in Unorganized Point Clouds.” Pattern Recognition 48.6 (2015): 2043–2053. Web.


Lloyd, Stuart. “Least squares quantization in PCM.” IEEE transactions on information theory 28.2 (1982): 129-137.


McCool, Michael, and Eugene Fiume. “Hierarchical Poisson disk sampling distributions.” Proceedings of the conference on Graphics interface. Vol. 92. 1992.


ALoopingIcon. “Meshing Point Clouds.” MESHLAB STUFF. n.p., 7 Sept. 2009. Web. 13 Nov. 2015.


Pingel, Thomas J., Keith C. Clarke, and William A. McBride. “An Improved Simple Morphological Filter for the Terrain Classification of Airborne LIDAR Data.” ISPRS Journal of Photogrammetry and Remote Sensing 77 (2013): 21–30.


Rusu, Radu Bogdan, et al. “Towards 3D point cloud based object maps for household environments.” Robotics and Autonomous Systems 56.11 (2008): 927-941.


Weyrich, T et al. “Post-Processing of Scanned 3D Surface Data.” Proceedings of Eurographics Symposium on Point-Based Graphics 2004 (2004): 85–94. Print.


Yang, Heng, Jingnan Shi, and Luca Carlone, “TEASER: Fast and Certifiable Point Cloud Registraton,” arXiv preprint, arXiv:2001.07715, 2020.


Zhang, Keqi, et al. “A progressive morphological filter for removing nonground measurements from airborne LIDAR data.” Geoscience and Remote Sensing, IEEE Transactions on 41.4 (2003): 872-882.


Zhang, Wuming, et al. “An easy-to-use airborne LiDAR data filtering method based on cloth simulation.” Remote Sensing 8.6 (2016): 501.