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.if (require(RCSF, quietly = TRUE)) { 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") }
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: gnd_mcc, gnd_pmf