gb rivers

data_pipeline.R

library(dplyr)
library(sf)

if (!file.exists("rivers_gb.rds")) {
  download.file(
    "https://beaver-net-app.s3.eu-west-2.amazonaws.com/gb_rivers/rivers_gb.rds",
    "rivers_gb.rds"
  )
}

# raw data
gb_rivers <- readRDS("rivers_gb.rds") |>
  as_tibble() |>
  janitor::clean_names()

# remove attributes and reduce precision of drain_area (round to 0.5)
gb_rivers_compact <- gb_rivers |>
  select(drain_area, geom) |>
  mutate(
    # round to nearest 0.5
    drain_area = round(drain_area / 0.5) * 0.5
  )

# merge adjacent lines with identical features
# less featues = smaller tiles
# note: tippecanoe can also coalesce features (which I have enabled), but this works better
gb_rivers_coords <- st_coordinates(gb_rivers_compact$geom) |>
  as_tibble(.name_repair = ~ c("lon", "lat", "id")) |>
  inner_join(
    transmute(gb_rivers_compact, drain_area, id = row_number()),
    by = "id"
  )

gb_rivers_mls <- gb_rivers_coords |>
  group_by(drain_area) |>
  mutate(group_id = cur_group_id()) |>
  ungroup() |>
  arrange(group_id) |>
  sfheaders::sf_multilinestring(
    x = "lon",
    y = "lat",
    linestring_id = "id",
    multilinestring_id = "group_id",
    keep = TRUE
  ) |>
  st_set_crs(st_crs(gb_rivers$geom)) |>
  st_line_merge() |>
  select(id = group_id, drain_area, geometry)

# ready for tippecanoe
st_write(
  obj = gb_rivers_mls,
  driver = "GeoJSON",
  dsn = "gb-rivers-compact.geojson",
  delete_dsn = TRUE,
  layer_options = c("RFC7946=YES", "ID_FIELD=id")
)

gb_rivers.R

library(rdeck)

rdeck(
  map_style = mapbox_dark(),
  # pre-computed bounds
  initial_bounds = sf::st_bbox(
    c(xmin = -6.975690, ymin = 49.975074, xmax = 1.739668, ymax = 58.686302),
    crs = 4326
  ),
  picking_radius = 2,
  layer_selector = TRUE
) |>
  add_mvt_layer(
    name = "Upstream Catchment Area",
    # source data from https://beaver-net-app.s3.eu-west-2.amazonaws.com/gb_rivers/rivers_gb.rds
    data = tile_json("anthony-north.49q7uoku"),
    get_line_color = scale_color_threshold(
      col = drain_area,
      palette = viridis::magma,
      # pre-computed quantile breaks & limits
      breaks = c(0, 1.11, 3.1, 7.98, 31.79, 10378.65),
      limits = c(0, 10378.65)
    ),
    get_line_width = width_m,
    line_width_min_pixels = 0.75,
    pickable = TRUE,
    auto_highlight = TRUE,
    tooltip = c(drain_area, width_m),
  )

gb_rivers_compact.R

library(rdeck)

rdeck(
  map_style = mapbox_dark(),
  # pre-computed bounds
  initial_bounds = sf::st_bbox(
    c(xmin = -6.975690, ymin = 49.975074, xmax = 1.739668, ymax = 58.686302),
    crs = 4326
  ),
  picking_radius = 2,
  layer_selector = TRUE
) |>
  add_mvt_layer(
    name = "Upstream Catchment Area (compact)",
    # source data from https://beaver-net-app.s3.eu-west-2.amazonaws.com/gb_rivers/rivers_gb.rds
    data = tile_json("anthony-north.2izrjjdl"),
    get_line_color = scale_color_threshold(
      col = drain_area,
      palette = viridis::magma,
      # pre-computed quantile breaks & limits
      breaks = c(0, 1.11, 3.1, 7.98, 31.79, 10378.65),
      limits = c(0, 10378.65)
    ),
    get_line_width = 15,
    line_width_min_pixels = 0.75,
    pickable = TRUE,
    auto_highlight = TRUE,
    tooltip = drain_area,
  )

Tippecanoe command:

tippecanoe gb-rivers.geojson -o gb-rivers.mbtiles --layer=gb-rivers --read-parallel --no-feature-limit --reorder --coalesce --reverse --hilbert --simplification=10 -z12