experimental_metrics: compute experimental lidar metrics

In jstrunk001/lasR: Simple lidar reading, processing, viewing

Description

take advantage of xy and 3d information

Usage

experimental_metrics(x = NA, y = NA, z = NA, i = NA, rn = NA,
  cl = NA, r = NA, g = NA, b = NA, resxy = 20, resxyz = 20,
  ressurf = 5, htcover = 6, zthresh = c(3, 6, 12, 20),
  adjustz = c("none", "positive", "min0", "zq01"), outlier = c(min =
  NA, max = NA))

Arguments

x	lidR object X vector : las1$X
y	lidR object Y vector : las1$Y
z	lidR object Z vector : las1$Z
i	lidR object intensity vector : las1$Intensity
rn	lidR object return vector : las1$ReturnNumber
cl	lidR object return vector : las1$Classification
r	lidR object red vector : las1$R
g	lidR object green vector : las1$G
b	lidR object blue vector : las1$B
resxy	resolution to use when computing xy statistic - grid resolution
resxyz	resolution to use when computing xyz statistic - voxel resolution
ressurf	resolution to use when computing raster areas - grid resolution
htcover	height to use when computing cover and threshold for eliminating ground returns
zthresh	height thresholds to use for height ratios round(100*length(z[ z > zthresh[i]]) / length(z[ z > htcover]),2)
adjustz	(optional) method used to shift z values up/down. When there is no DTM or the DTM is poor (e.g. when used with DAP) this can help
outlier	a two value vector with minimum and maximum values used to restrict the range of z values considered

Details

<Delete and Replace>

Revision History

1.0	4/4/2019

Value

list of statistics, currently only computed on x,y,z

Author(s)

Jacob Strunk <[e-mail]>

See Also

another_function
yet_another_function

Examples

   if(!"las1" %in% ls()) las1 = readLAS("D:\\Box\\sync\\R\\analyses\\wa_dsm_env_fia\\data\\plot_clips_ht\\plot_44.laz")
   test2 = lasmetrics(las1,experimental_metrics(X,Y,Z))
   test2

jstrunk001/lasR documentation built on April 20, 2020, 7:24 a.m.