CSF (Cloth Simulation Filter)

LiDAR point cloud ground filtering / segmentation (bare earth extraction) method based on cloth simulation.
1.9K Downloads
Updated 17 Mar 2024
Separating point clouds into ground and non-ground measurements is an essential step to generate digital terrain models (DTMs) from LiDAR (light detection and ranging) data. Many filtering algorithms have been developed. However, even state-of-the-art filtering algorithms need to set up a number of complicated parameters carefully to achieve high accuracy.
For the purpose of reducing the parameters users to set, and promoting the filtering algorithms, we present a new filtering method which only needs a few easy-to-set integer and Boolean parameters. This method is based on cloth simulation which is a 3D computer graphics algorithm and is used for simulating cloth within a computer program. So our filtering algorithm is called cloth simulation filtering, CSF.
More information of CSF and its parameters can be found at http://www.cloudcompare.org/doc/wiki/index.php?title=CSF_(plugin).
CSF implemented the algorithm proposed by the paper "Zhang W, Qi J, Wan P, Wang H, Xie D, Wang X, Yan G. An Easy-to-Use Airborne LiDAR Data Filtering Method Based on Cloth Simulation. Remote Sensing. 2016; 8(6):501.",which can be downloaded from https://www.researchgate.net/profile/Wuming_Zhang2. Please cite this paper, if you use this software in your work.
The usage is very simple. [groundIndex,nonGroundIndex] = csf_filtering(pointcloud,typeofscene,postprocessing,gridsize); Sometime, only the type of the scene is needed to be set by the user. More details can be found in demos.
CSF has been integrated into two free softwares for point cloud processing. If you want to use it with a graphical user interface (GUI), you can download CloudCompare from http://www.cloudcompare.org/ or Point Cloud Magic from http://lidar.radi.ac.cn (In Chinese).
An enhanced CSF algorithm is available for download from http://easypoint.xyz, that operates 10 times faster than most other software options.It also enables automatic processing of forest plot point cloud.
Recently, we published a paper which extends CSF to deal with the photon point cloud of ICESat-2 (LiDAR mounted on a Satellite). The result is more accurate than NASA ALT08 product. We have integrated this algorithm into the EasyPoint software and have granted it for free use.

Cite As

wpqjbzwm wpqjbzwm (2024). CSF (Cloth Simulation Filter) (https://github.com/jianboqi/CSF), GitHub. Retrieved .

Zhang W, Qi J, Wan P, Wang H, Xie D, Wang X, Yan G. An Easy-to-Use Airborne LiDAR Data Filtering Method Based on Cloth Simulation. Remote Sensing. 2016; 8(6):501.

Chang B, Xiong H, Li Y, et al. ALCSF: An adaptive and anti-noise filtering method for extracting ground and top of canopy from ICESat-2 LiDAR data along single tracks[J]. ISPRS Journal of Photogrammetry and Remote Sensing. 2024, 215: 80-98.

MATLAB Release Compatibility
Created with R2012a
Compatible with any release
Platform Compatibility
Windows macOS Linux

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Version Published Release Notes
1.2.3

update description

1.2.2.3

update description and cite

1.2.2.2

Minor changes to title and summary.

1.2.2.0

Fix some small bugs when using CSF with Matlab

1.2.1.0

we get a lot of feedbacks from different users around the world, the new version has been enhanced by:
1. improving accuracy for highly rugged terains
2. fixing some small bugs.

1.2.0.0

We get a lot of feedbacks from different users around the world, the new version has been enhanced by:
1. improving accuracy for highly rugged terrains.
2. Fixing some small bugs.

1.1.0.0

Three more options are added to input parameters.
[groundIndex,nonGroundIndex]=csf_filtering(PointCloudMatrix,rigidness,isSmooth,clothResolution,class_threshold,iterations,time_step)

1.0.0.0

To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.