% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/fitbit_utils.R
\name{rayshader_3d_DEM}
\alias{rayshader_3d_DEM}
\title{Rayshader 3-dimensional using the Copernicus DEM elevation data}
\usage{
rayshader_3d_DEM(
  rst_buf,
  rst_ext,
  linestring_ASC_DESC = NULL,
  elevation_sample_points = NULL,
  zoom = 0.5,
  windowsize = c(1600, 1000),
  add_shadow_rescale_original = FALSE,
  verbose = FALSE
)
}
\arguments{
\item{rst_buf}{this parameter corresponds to the 'sfc_obj' object of the 'extend_AOI_buffer()' function}

\item{rst_ext}{this parameter corresponds to the 'raster_obj_extent' object of the 'extend_AOI_buffer()' function}

\item{linestring_ASC_DESC}{If NULL then this parameter will be ignored. Otherwise, it can be an 'sf' object or a named list of length 2 (that corresponds to the output of the 'gps_lat_lon_to_LINESTRING()' function)}

\item{elevation_sample_points}{if NULL then this parameter will be ignored. Otherwise, it corresponds to a data.table with column names 'latitude', 'longitude' and 'AltitudeMeters'. For instance, it can consist of 3 or 4 rows that will be displayed as vertical lines in the 3-dimensionsal map to visualize sample locations of the route (the latitudes and longitudes must exist in the output data.table of the 'GPS_TCX_data()' function)}

\item{zoom}{a float number. Lower values increase the 3-dimensional DEM output. The default value is 0.5}

\item{windowsize}{a numeric vector specifying the window dimensions (x,y) of the output 3-dimensional map. The default vector is c(1600, 1000)}

\item{add_shadow_rescale_original}{a boolean. If TRUE, then 'hillshade' will be scaled to match the dimensions of 'shadowmap'. See also the 'rayshader::add_shadow()' function for more information.}

\item{verbose}{a boolean. If TRUE then information will be printed out in the console}
}
\value{
it doesn't return an object but it displays a 3-dimensional 'rayshader' object
}
\description{
Rayshader 3-dimensional using the Copernicus DEM elevation data
}
\examples{
\dontrun{

require(fitbitViz)

# export the TCX file from the Fitbit website or app for the desired activity

res_tcx <- GPS_TCX_data(
  tcx_file = "/path/to/activity.tcx",
  time_zone = "Europe/Athens",
  verbose = TRUE
)
str(res_tcx)

# ....................................................
# then compute the sf-object buffer and raster-extend
# ....................................................

sf_rst_ext <- extend_AOI_buffer(
  dat_gps_tcx = res_tcx,
  buffer_in_meters = 1000,
  CRS = 4326,
  verbose = TRUE
)
sf_rst_ext

# ...............................................................
# Download the Copernicus DEM 30m elevation data because it has
# a better resolution, it takes a bit longer to download because
# the .tif file size is bigger
# ...............................................................

dem_dir <- tempdir()
# dem_dir

dem30 <- CopernicusDEM::aoi_geom_save_tif_matches(
  sf_or_file = sf_rst_ext$sfc_obj,
  dir_save_tifs = dem_dir,
  resolution = 30,
  crs_value = 4326,
  threads = parallel::detectCores(),
  verbose = TRUE
)

TIF <- list.files(dem_dir, pattern = ".tif", full.names = T)
# TIF

if (length(TIF) > 1) {
  # ....................................................
  # create a .VRT file if I have more than 1 .tif files
  # ....................................................

  file_out <- file.path(dem_dir, "VRT_mosaic_FILE.vrt")

  vrt_dem30 <- create_VRT_from_dir(
    dir_tifs = dem_dir,
    output_path_VRT = file_out,
    verbose = TRUE
  )
}

if (length(TIF) == 1) {
  # ..................................................
  # if I have a single .tif file keep the first index
  # ..................................................

  file_out <- TIF[1]
}

raysh_rst <- crop_DEM(
  tif_or_vrt_dem_file = file_out,
  sf_buffer_obj = sf_rst_ext$sfc_obj,
  verbose = TRUE
)

# terra::plot(raysh_rst)


# ................................................................
# create the 'elevation_sample_points' data.table parameter based
# on the min., middle  and max. altitude of the 'res_tcx' data
# ................................................................

idx_3m <- c(
  which.min(res_tcx$AltitudeMeters),
  as.integer(length(res_tcx$AltitudeMeters) / 2),
  which.max(res_tcx$AltitudeMeters)
)

cols_3m <- c("latitude", "longitude", "AltitudeMeters")
dat_3m <- res_tcx[idx_3m, ..cols_3m]
# dat_3m

# ...............................................................
# Split the route in 2 parts based on the maximum altitude value
# ...............................................................

linestring_dat <- gps_lat_lon_to_LINESTRING(
  dat_gps_tcx = res_tcx,
  CRS = 4326,
  time_split_asc_desc = NULL,
  verbose = TRUE
)

# .....................................................
# Conversion of the 'SpatRaster' to a raster object
# because the 'rayshader' package accepts only rasters
# .....................................................

rst_obj <- raster::raster(raysh_rst)
raster::projection(rst_obj) <- terra::crs(raysh_rst, proj = TRUE)


# .....................................
# open the 3-dimensional rayshader map
# .....................................

ray_out <- rayshader_3d_DEM(
  rst_buf = rst_obj,
  rst_ext = sf_rst_ext$raster_obj_extent,
  linestring_ASC_DESC = linestring_dat,
  elevation_sample_points = dat_3m,
  zoom = 0.5,
  windowsize = c(1600, 1000),
  add_shadow_rescale_original = FALSE,
  verbose = TRUE
)
}
}
\references{
https://www.tylermw.com/a-step-by-step-guide-to-making-3d-maps-with-satellite-imagery-in-r/
}
