aRchi (version 2.1.3)

add_non_reconstructed: Detect and add the axes that were not reconstructed by the QSM method

Description

Detect and add the axes that were not reconstructed by the QSM method

Usage

add_non_reconstructed(
  aRchi,
  max_dist = 99999,
  sec_length = 0.2,
  method = "statistical",
  th = 2.5,
  d_clust = 0.02
)
# S4 method for aRchi
add_non_reconstructed(
  aRchi,
  max_dist = 99999,
  sec_length = 0.2,
  method = "statistical",
  th = 2.5,
  d_clust = 0.02
)

Value

the aRchi file with reconstructed axes added to the skeleton with a field "reconstructed".

Arguments

aRchi

a file of class aRchi.

max_dist

numeric. The maximum distance of a point to the skeleton to be considered in the computation.

sec_length

numeric. The length of an axis section to compute the average distance used in the computation of the point relative distance to skeleton.

method

character. Defines the method to use to identify the non reconstructed portions of the point cloud, see details.

th

numeric. The threshold to use to identify the non reconstructed portions of the point cloud. See details.

d_clust

numeric. The distance to use for axes clustering from the identifyed non reconstructed portions of the point cloud.

Details

This function detects the non reconstructed axes by analyzing the point cloud distance to the skeleton. In a first step, the distance of each point to the skeleton is computed. At this step, the points that are too far from the skeleton can be removed with the parameter max_dist. The relative distance of the points is then computed by dividing their respective distance by the average distance of all the points within axes sections of a given length (sec_length). The points that are far from the skeleton (in terms of relative distance) are then considered as being part of a non reconstructed axis (NR). To do so two parameters are available. First, the method parameter defines which method should be used to identify the NR points and th sets the threshold to use. If method = "absolute" then th is a cut-off distance for the relative distance (1 being the average distance). If method = "statistical" then th is a multiplier of the standard deviation so that the points further than th*sd (sd = the standard deviation of the distribution of relative distances) are considered as NR points. NR axes are then segmented by clustering the NR points based on distance. To do so, the d_clust parameter sets the minimal distance between two points to be considered as part of two different axes. The NR axes are then reconstructed as a single segment.

References

Lecigne, B., Delagrange, S., Lauri, P. É., & Messier, C. (2022). Trimming influences tree light interception and space exploration: contrasted responses of two cultivars of Fraxinus pennsylvanica at various scales of their architecture. Trees, 1-17. https://doi.org/10.1007/s00468-022-02273-5

Examples

# \donttest{
# import aRchi file
aRchi=system.file("extdata","Tree_2.aRchi",package = "aRchi")
aRchi = aRchi::read_aRchi(aRchi)

# smooth the skeleton
aRchi = aRchi::smooth_skeleton(aRchi,th = 0.01)

# clean point cloud
aRchi = aRchi::clean_point_cloud(aRchi)

# add missing axes
aRchi = aRchi::add_non_reconstructed(aRchi,th = 3)

# plot the skeleton with reconstructed axes in red
plot(aRchi,color="reconstructed",show_point_cloud = TRUE)
# }