Ground Segmentation Algorithm
This function is made to be used in classify_ground. It implements an algorithm for segmentation
of ground points base on a Cloth Simulation Filter. This method is a strict implementation of
the CSF algorithm made by Zhang et al. (2016) (see references) that relies on the authors' original
source code written and exposed to R via the the RCSF
package.
csf( sloop_smooth = FALSE, class_threshold = 0.5, cloth_resolution = 0.5, rigidness = 1L, iterations = 500L, time_step = 0.65 )
sloop_smooth |
logical. When steep slopes exist, set this parameter to TRUE to reduce errors during post-processing. |
class_threshold |
scalar. The distance to the simulated cloth to classify a point cloud into ground and non-ground. The default is 0.5. |
cloth_resolution |
scalar. The distance between particles in the 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 rigidness of the cloth. 1 stands for very soft (to fit rugged terrain), 2 stands for medium, and 3 stands for hard cloth (for flat terrain). The default is 1. |
iterations |
integer. Maximum iterations for simulating cloth. The default value is 500. Usually, there is no need to change this value. |
time_step |
scalar. Time step when simulating the cloth under gravity. The default value is 0.65. Usually, there is no need to change this value. It is suitable for most cases. |
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. (http://www.mdpi.com/2072-4292/8/6/501/htm)
Other ground segmentation algorithms:
pmf()
LASfile <- system.file("extdata", "Topography.laz", package="lidR") las <- readLAS(LASfile, select = "xyzrn") mycsf <- csf(TRUE, 1, 1, time_step = 1) las <- classify_ground(las, mycsf) #plot(las, color = "Classification")
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