CSF: Airborne LiDAR filtering method based on Cloth Simulation

In RCSF: Airborne LiDAR Filtering Method Based on Cloth Simulation

Description

Airborne LiDAR filtering method of ground points based on Cloth Simulation (Zhang et al. 2016, see references). This function is an R wrapper around the library written by the orignal authors of the algorithm. The ALS point cloud is inverted, and then a rigid cloth is used to cover the inverted surface. By analyzing the interactions between the cloth nodes and the corresponding LiDAR points, the locations of the cloth nodes can be determined to generate an approximation of the ground surface.

Usage

CSF(
  cloud,
  sloop_smooth = FALSE,
  class_threshold = 0.5,
  cloth_resolution = 0.5,
  rigidness = 1L,
  iterations = 500L,
  time_step = 0.65
)

Arguments

cloud	data.frame with 3 columns named X Y, Z containing the coordinates of the point cloud.
sloop_smooth	logical. When sharp slopes exist, set this parameter to TRUE to perform a post-processing which will reduced errors.
class_threshold	scalar. The distance to the simulated cloth to classify point cloud into ground and non-ground. The default is 0.5.
cloth_resolution	scalar. The distance between paticles in cloth. This is usually set to the average distance of the points in the point cloud. The default value is 0.5.
rigidness	integer. The rididness of the cloth. 1 stands for very soft cloth (to fit rugged terrain), 2 stands for medium cloth and 3 stands for hard cloth (for flat terrain). The default is 1.
iterations	integer. Maximum iteration for simulating cloth. The default value is 500. Usually, users do not need to change this.
time_step	scalar. Time step when simulating the cloth under the gravity. The default value is 0.65. Usually, Do not change this value. It is suitable for most cases.

Value

An integer vector containing the ids of the points that belong on the ground.

References

W. Zhang, J. Qi*, P. Wan, H. Wang, D. Xie, X. Wang, and G. Yan, “An Easy-to-Use Airborne LiDAR Data Filtering Method Based on Cloth Simulation”, Remote Sens., vol. 8, no. 6, p. 501, 2016

Examples

data(rcsf_cloud)
head(rcsf_cloud)

id_ground = CSF(rcsf_cloud)

Example output

        X    Y      Z
1 68.3750 89.0 308.85
2 68.3438 87.5 308.88
3 68.2812 86.0 308.89
4 68.2188 84.5 308.94
5 68.1562 83.0 308.89
6 68.1250 81.5 308.86

RCSF documentation built on Feb. 5, 2020, 1:07 a.m.