In forestgeo/fgeo.tool: Import and Manipulate 'ForestGEO' Data

knitr::opts_chunk$set(echo = TRUE, collapse = TRUE)

library(dplyr)
library(tibble)

Example data

elevation_ls <- fgeo.data::luquillo_elevation
str(elevation_ls)

Paramenters

gridsize <- 20
plotdim <- c(320, 500)
edgecorrect <- TRUE
n_clusters <- 4

Slope and convexity

meanelev_convex_slope <- ctfs::allquadratslopes(
  elevation_ls,
  gridsize = gridsize,
  plotdim = plotdim,
  edgecorrect = edgecorrect
)
as_tibble(meanelev_convex_slope)

We can create "habitats" by clustering meanelev, convex and slope.

meanelev_convex_slope <- mutate(
  meanelev_convex_slope, 
  habitats =  kmeans(meanelev_convex_slope, n_clusters)$cluster
)

habitat <- rowid_to_column(meanelev_convex_slope, "index")
as_tibble(habitat)

ctfs::allquadratslopes() didn't output the gx and gy coordinates of each row of the output, but the row indices correspond to quadrat index.

# The names of the columns isn't quite right. I plan to make `add_index()` a bit
# more flexible: https://github.com/forestgeo/fgeo.tool/issues/52
elevation_df <- dplyr::rename(elevation_ls$col, gx = x, gy = y)

elevation_df <- fgeo.tool::add_index(elevation_df)
elevation_df

Now we can use index to link gx, gy to hatibats created with ctfs::allquadratslopes().

round_gxgy_to_gridsize <- function(x, gridsize) {
  fgeo.base::check_crucial_names(x, c("gx", "gy"))

  x$gx <- fgeo.base::round_any(x$gx, gridsize)
  x$gy <- fgeo.base::round_any(x$gy, gridsize)
  x
}

gxgy <- ctfs::index.to.gxgy(habitat$index, gridsize = gridsize, plotdim = plotdim)
gxgy_hab <- cbind(habitat, gxgy)
gxgy_hab <- dplyr::select(gxgy_hab, index, gx, gy, habitats, everything())
tibble::as.tibble(gxgy_hab)