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FORTLS (version 1.0.1)

Rioja.data: Inventoried Plots Data for a Stand Case Study in La Rioja

Description

This list includes trees detected with TLS for 16 single scans corresponding to plots located in La Rioja, a region of Spain, in the north of the Iberian Peninsula (first element), as well as those inventoried in the field for these 16 plots (second element). Plot attributes related to stand stratum are also included (third element).

The elements of the list are as follows:

  1. tree.list.tls: data frame that includes the list of trees detected with tree.detection for 16 TLS single-scans. The following variables are provided for each tree (see tree.detection ‘Value’ for more details):

    [,1] id character/numeric [,2]
    file character [,3] tree
    numeric [,4] x numeric
    [,5] y numeric [,6:8]
    phi, phi.left, phi.right numeric [,9] horizontal.distance
    numeric [,10] dbh numeric
    [,11:14] num.points, num.points.hom, num.points.est, num.points.hom.est numeric [,15]
    partial.occlusion numeric [,1] id
  2. tree.list.field: data frame that includes the list of trees measured in 16 circular fixed area plots of radius 20 m, whose centres coincide with TLS single-scans points. The following variables are provided for each tree:

    [,1] id numeric plot identification (coincident to TLS scans)
    [,2] tree numeric trees numbering
    [,3] Sp numeric specie code according to NFI ()
    [,4] horizontal.distance numeric horizontal distance (m) from plot center to tree center
    [,5] dbh numeric tree diameter (cm) at breast height (1.3 m)
    [,6] total.height numeric tree total height (m)
    [,7] dead numeric dead (1) or not (NA)
  3. plot.attributes: dataframe that includes the stratum of each plot:

    [,1] id character/numeric plot identification (coincident to TLS scans)
    [,2] stratum numeric stratum (1-2)

Usage

data(Rioja.data)

Arguments

Format

List with 3 data frames containing 598 observations and 15 variables (tree.list.tls), 659 observations and 7 variables (tree.list.field), and 16 observations and 2 variables (plot.attributes).