R/fitbit_utils.R
rayshader_3d_DEM.RdRayshader 3-dimensional using the Copernicus DEM elevation data
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
)this parameter corresponds to the 'sfc_obj' object of the 'extend_AOI_buffer()' function
this parameter corresponds to the 'raster_obj_extent' object of the 'extend_AOI_buffer()' function
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)
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)
a float number. Lower values increase the 3-dimensional DEM output. The default value is 0.5
a numeric vector specifying the window dimensions (x,y) of the output 3-dimensional map. The default vector is c(1600, 1000)
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.
a boolean. If TRUE then information will be printed out in the console
it doesn't return an object but it displays a 3-dimensional 'rayshader' object
https://www.tylermw.com/a-step-by-step-guide-to-making-3d-maps-with-satellite-imagery-in-r/
if (FALSE) {
require(fitbitViz)
#............................
# first extract the log-id(s)
#............................
USER_ID = '99xxxx'
token = 'my_long_web_api_token'
log_id = extract_LOG_ID(user_id = USER_ID,
token = token,
after_Date = '2021-03-13',
limit = 10,
sort = 'asc',
verbose = TRUE)
str(log_id)
#...................................
# then return the gps-ctx data.table
#...................................
res_tcx = GPS_TCX_data(log_id = log_id,
user_id = USER_ID,
token = token,
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)
}