fix all conflicts

R/corenet_build_OS.R

@@ -239,19 +239,23 @@ corenet_build_OS = function(os_scotland, osm_scotland, la_names) {
   )
 
   # Define the file path for the combined GeoJSON
-  combined_CN_file = glue::glue("{output_folder}/combined_CN_{date_folder}_OS.geojson")
+  combined_CN_geojson_file = glue::glue("{output_folder}/combined_CN_{date_folder}_OS.geojson")
+  combined_CN_gpkg_file = glue::glue("{output_folder}/combined_CN_{date_folder}_OS.gpkg")
+  # Write the combined data to GeoJSON and GeoPackage files
+  sf::st_write(final_la_coherent, combined_CN_geojson_file, delete_dsn = TRUE)
+  sf::st_write(final_la_coherent, combined_CN_gpkg_file, delete_dsn = TRUE)
 
-  # Write the combined GeoJSON to a file
-  sf::st_write(combined_CN_geojson, combined_CN_file, delete_dsn = TRUE)
-  cat("Combined cohesive networks GeoJSON file for group has been saved to:", combined_CN_file, "\n")
+  # Print messages indicating where the files have been saved
+  cat("Combined cohesive networks GeoJSON file for group has been saved to:", combined_CN_geojson_file, "\n")
+  cat("Combined cohesive networks GeoPackage file for group has been saved to:", combined_CN_gpkg_file, "\n")
 
   # Define the path for the PMtiles
-  combined_CN_pmtiles = glue::glue("{output_folder}/combined_CN_{number}_{date_folder}_OS.pmtiles")
+  combined_CN_pmtiles = glue::glue("{output_folder}/combined_CN_{date_folder}_OS.pmtiles")
 
   # Construct the Tippecanoe command for the current group
   command_tippecanoe = paste0(
     'tippecanoe -o ', combined_CN_pmtiles,
-    ' --name="', 'Scottish_Coherent_Networks_', number, '"',
+    ' --name="', 'Scottish_Coherent_Networks', 
     ' --layer=coherent_networks',
     ' --attribution="University of Leeds"',
     ' --minimum-zoom=6',
@@ -261,11 +265,11 @@ corenet_build_OS = function(os_scotland, osm_scotland, la_names) {
     ' --buffer=5',
     ' -rg',
     ' --force ',
-    combined_CN_file
+    combined_CN_geojson_file
   )
 
   # Execute the command and capture output
   system_output = system(command_tippecanoe, intern = TRUE)
-  cat("Tippecanoe output for group", number, ":\n", system_output, "\n")
+  cat("Tippecanoe output for group :\n", system_output, "\n")
 
-}
+}

R/pkgs.R

@@ -21,6 +21,7 @@ get_pkgs = function() {
   "tidyverse", # Includes dplyr, ggplot2, tidyr, stringr etc.
   "zonebuilder", # For creating zones for spatial analysis
   "iterators", # For creating iterators
-  "doParallel" # For parallel processing
+  "doParallel", # For parallel processing
+  "httr"
   )
 }

R/simplify_network.R

@@ -8,12 +8,9 @@ simplify_network = function(rnet_y, region_name, region_boundary) {
   region_snake_case = snakecase::to_snake_case(region_name)
   base_name = paste0("OS_Scotland_Network_", region_snake_case, ".geojson")
   rnet_x_f = file.path("inputdata", base_name)
-  rnet_x = sf::read_sf(rnet_x_f)
-  # rnet_x = geojsonsf::geojson_sf(rnet_x_f) # bit faster
+  rnet_x = sf::read_sf(rnet_x_f) |> sf::st_transform(crs = "EPSG:27700")
 
-  # Transform the spatial data to a different coordinate reference system (EPSG:27700)
-  # TODO: uncomment:
-  rnet_x = rnet_x[region_boundary, ] # TODO: is this needed? Can remove if not
+  rnet_x = rnet_x[region_boundary |> sf::st_transform(crs = "EPSG:27700") , ] # TODO: is this needed? Can remove if not
   rnet_xp = sf::st_transform(rnet_x, "EPSG:27700")
   rnet_yp = sf::st_transform(rnet_y, "EPSG:27700")
 
@@ -69,36 +66,29 @@ simplify_network = function(rnet_y, region_name, region_boundary) {
   rnet_merged_all = rnet_merged_all |>
     dplyr::filter_at(columns_to_check, any_vars(!is.na(.)))
 
-  # Selecting only the geometry column from the 'rnet_merged_all' dataset.
-  rnet_merged_all_only_geometry = rnet_merged_all |> dplyr::select(geometry)
-
-  # Merging all geometries into a single geometry using st_union from the sf package.
-  rnet_merged_all_union = sf::st_union(rnet_merged_all_only_geometry)
-
-  # Transforming the merged geometry to a specific coordinate reference system (CRS), EPSG:27700.
-  rnet_merged_all_projected = sf::st_transform(rnet_merged_all_union, "EPSG:27700")
-
   # Converting the projected geometry into a GEOS geometry. GEOS is a library used for spatial operations.
-  rnet_merged_all_geos = geos::as_geos_geometry(rnet_merged_all_projected)
+  rnet_merged_all_geos = geos::as_geos_geometry(rnet_merged_all)
 
   # Creating a buffer around the GEOS geometry. This expands the geometry by a specified distance (in meters).
   rnet_merged_all_geos_buffer = geos::geos_buffer(rnet_merged_all_geos, distance = 30, params = geos::geos_buffer_params(quad_segs = 4))
 
   # Converting the buffered GEOS geometry back to an sf object.
   rnet_merged_all_projected_buffer = sf::st_as_sf(rnet_merged_all_geos_buffer)
 
-  # Transform the coordinate reference system of 'rnet_merged_all' to WGS 84 (EPSG:4326).
-  rnet_merged_all_buffer = sf::st_transform(rnet_merged_all_projected_buffer, "EPSG:4326")
-
   # Subsetting another dataset 'rnet_y' based on the spatial relation with 'rnet_merged_all_buffer'.
   # It selects features from 'rnet_y' that are within the boundaries of 'rnet_merged_all_buffer'.
-  rnet_y_subset = rnet_y[rnet_merged_all_buffer, , op = sf::st_within]
+  # rnet_y_subset = sf::st_intersection(rnet_yp, rnet_merged_all_projected_buffer)
+  # browser()
+  rnet_yp_points = sf::st_point_on_surface(rnet_yp)
+  rnet_yp_points_subset = rnet_yp_points[rnet_merged_all_projected_buffer, ]
+  rnet_y_subset = rnet_yp[rnet_yp_points_subset, ]
 
   # Filter 'rnet_y' to exclude geometries within 'within_join'
-  rnet_y_rest = rnet_y[!rnet_y$geometry %in% rnet_y_subset$geometry, ]
+  rnet_y_rest = rnet_yp[!rnet_yp$geometry %in% rnet_y_subset$geometry, ]
 
   # Transform the CRS of the 'rnet_merged_all' object to WGS 84 (EPSG:4326)
   rnet_merged_all = sf::st_transform(rnet_merged_all, "EPSG:4326")
+  rnet_y_rest = sf::st_transform(rnet_y_rest, "EPSG:4326")
 
   # Combine 'rnet_y_rest' and 'rnet_merged_all' into a single dataset
   simplified_network = dplyr::bind_rows(rnet_y_rest, rnet_merged_all)

_targets.R

@@ -20,6 +20,7 @@ library(targets) # Needed to make targets work
 library(magrittr) # Light load of |>
 library(sf) # Needed for sf support
 set.seed(2023)
+httr::set_config(httr::timeout(seconds = 6000))
 tar_source()
 pkgs = get_pkgs()
 
@@ -626,7 +627,6 @@ tar_target(rs_school, {
     os_pois_subset[region_boundary_buffered, ] |>
       sf::st_transform("EPSG:27700")
   }),
-
   tar_target(grid, {
     grid = readRDS("./inputdata/grid_scot.Rds")
     grid = sf::st_transform(grid, "EPSG:4326")
@@ -676,14 +676,13 @@ tar_target(rs_school, {
   # Combined utility trip purposes --------------------------------------------
 
   tar_target(od_utility_combined, {
-
     od_utility_combined = rbind(od_shopping, od_visiting, od_leisure) |>
       dplyr::slice_max(n = parameters$max_to_route, order_by = all, with_ties = FALSE)
     sum(od_utility_combined$bicycle) / sum(od_utility_combined$all)
 
     # Get % cycling for commuting per zone
     # pcycle_regional = sum(commute_stats$comm_orig_bicycle, na.rm = TRUE) /
-      # sum(commute_stats$comm_orig_all, na.rm = TRUE)
+    # sum(commute_stats$comm_orig_all, na.rm = TRUE)
     pcycle_national = 0.016
 
     commute_stats_minimal = commute_stats |>
@@ -692,7 +691,7 @@ tar_target(rs_school, {
       dplyr::transmute(
         DataZone,
         multiplier = (comm_orig_bicycle / comm_orig_all) /
-         pcycle_national
+          pcycle_national
       ) |>
       # 0 to 0.1:
       dplyr::mutate(multiplier = case_when(
@@ -829,7 +828,7 @@ tar_target(rs_school, {
 
   tar_target(utility_stats_baseline, {
     stats = sf::st_drop_geometry(od_utility_combined)
-     stats = stats[, c(
+    stats = stats[, c(
       "startDZ", "endDZ", "purpose", "all", "car",
       "foot", "bicycle", "public_transport", "taxi"
     )]
@@ -1130,7 +1129,6 @@ tar_target(rs_school, {
     responce = system(command_all, intern = TRUE)
     responce
   }),
-
   tar_target(pmtiles_buildings, {
     check = length(zones_dasymetric_tile)
 
@@ -1229,7 +1227,7 @@ tar_target(rs_school, {
 
     message("Saving outputs for ", parameters$date_routing)
 
-    saveRDS(od_commute_subset, file.path(region_folder, "od_commute_subset.Rds"))  
+    saveRDS(od_commute_subset, file.path(region_folder, "od_commute_subset.Rds"))
     saveRDS(zones_stats, file.path(region_folder, "zones_stats.Rds"))
     saveRDS(school_stats, file.path(region_folder, "school_stats.Rds"))
 
@@ -1241,7 +1239,6 @@ tar_target(rs_school, {
     sf::write_sf(combined_network, file.path(region_folder, "combined_network.gpkg"), delete_dsn = TRUE)
     as.character(Sys.Date())
   }),
-
   tar_target(metadata, {
     # TODO: generate build summary
     # metadata_all = tar_meta()

code/build.R

@@ -11,11 +11,7 @@ library(doParallel)
 tar_source()
 
 parameters = jsonlite::read_json("parameters.json", simplifyVector = T)
-lads = sf::read_sf("inputdata/boundaries/la_regions_2023.geojson")
-mapview::mapview(lads)
-# To test for a single local authority:
-lads = lads |>
-  filter(LAD23NM %in% c("Clackmannanshire"))
+lads = sf::read_sf("inputdata/boundaries/la_regions_scotland_bfe_simplified_2023.geojson")
 date_folder = parameters$date_routing
 la_names = lads$LAD23NM
 output_folder = file.path("outputdata", date_folder)
@@ -44,21 +40,20 @@ if (GENERATE_CDB) {
 
   library(osmactive)
   # See https://github.com/nptscot/osmactive/blob/main/code/classify-roads.R and traffic-volumes.R
-  # TODO: Change to V6:
-  "final_estimates_Scotland.gpkg"
-  # https://github.com/nptscot/scottraffic/releases
-  f_traffic = "scottraffic/final_estimates_Scotland_higherror_discarded.gpkg"
+  f_traffic = "scottraffic/final_estimates_Scotland.gpkg"
   if (!file.exists(f_traffic)) {
     system("gh repo clone nptscot/scottraffic")
+    file.remove(f_traffic)
     setwd("scottraffic")
     system("gh release list")
-    system("gh release download v5 --clobber")
+    system("gh release download v6")
     setwd("..")
   }
   traffic_volumes_scotland = sf::read_sf(f_traffic)
 
-  # Generate cycle_net - this is slow, we should save the file
-  osm_national = get_travel_network("Scotland", force_download = T)
+  # Generate cycle_net: forcing update:
+  # osm_national = get_travel_network("Scotland", force_download = TRUE)
+  osm_national = get_travel_network("Scotland")
   # saveRDS(osm_national, "inputdata/osm_national_2024_05_23")
 
   # Generate road segment midpoints
@@ -180,15 +175,20 @@ if (GENERATE_CDB) {
 
       #     
       cycle_net_traffic = level_of_service(cycle_net_traffic)
-
+            
       cbd_layer = cycle_net_traffic |>
         transmute(
           osm_id,
           highway,
-          `Traffic volume` = final_traffic,
           `Speed limit` = final_speed,
           `Infrastructure type` = cycle_segregation,
-          `Level of Service`
+          `Level of Service`,
+          `Traffic volume category` = case_when(
+           final_traffic >= 0 & final_traffic < 1999.5 ~ "0 to 1999",
+            final_traffic >= 1999.5 & final_traffic < 3999.5 ~ "2000 to 3999",
+            final_traffic >= 3999.5 ~ "4000+",
+            TRUE ~ NA_character_
+          )
         )
       # save file for individual district
       district_name = district_geom$LAD23NM |> 
@@ -202,16 +202,26 @@ if (GENERATE_CDB) {
   }
 
   # Combine all CBD files into a single file
+  # Remove combined file if it already exists:
+  if (file.exists(cbd_filename)) {
+    file.remove(cbd_filename)
+  }
   cbd_files = list.files(output_folder, pattern = "cbd_layer_.*\\.geojson$", full.names = TRUE)
   # Create an empty cbd_layers and cbd_layer
   cbd_layers = sf::st_sf(geometry = st_sfc())
   cbd_layer = sf::st_sf(geometry = st_sfc())
   cbd_layers = lapply(cbd_files, sf::read_sf)
   cbd_layer = do.call(rbind, cbd_layers)
   cbd_filename = paste0(output_folder, "/cbd_layer_", date_folder, ".geojson")
-  if (file.exists(cbd_filename)) {
-    file.remove(cbd_filename)
-  }
+  # Update traffic volumes for off road cycleways
+  cbd_layer = cbd_layer |>
+    mutate(
+      `Traffic volume category` = case_when(
+        `Infrastructure type` == "Off Road Cycleway" ~ NA_character_,
+        highway %in% c("footway", "path", "pedestrian", "steps") ~ NA_character_,
+        TRUE ~ `Traffic volume category`
+      )
+    )
   sf::write_sf(cbd_layer, cbd_filename)
   fs::file_size(cbd_filename)
 
@@ -286,7 +296,7 @@ if (parameters$generate_CN_start) {
 # mapview::mapview(cn_test, zcol = "road_function")
 
 # Combine regional outputs 
----------------------------------------------------
+
 GENERATE_PMTILES = TRUE
 
 if (GENERATE_PMTILES) {
@@ -666,9 +676,6 @@ if (PUSH_TO_GITHUB) {
       parameters$max_to_route > 20e3
   is_linux = Sys.info()[["sysname"]] == "Linux"
   if (full_build) {
-    v = paste0("v", Sys.Date(), "_commit_", commit$commit)
-    v = gsub(pattern = " |:", replacement = "-", x = v)
-    # Or latest release:
     setwd(glue::glue(getwd(),"/", output_folder))
     system("gh release list")
     v = glue::glue("v{date_folder}")

code/prep_admin_bounds.R

@@ -18,7 +18,31 @@ library(sf)
 # la = sf::read_sf("la.gpkg")
 # plot(la)
 
-la = sf::read_sf("https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/Local_Authority_Districts_December_2023_Boundaries_UK_BSC/FeatureServer/0/query?outFields=*&where=1%3D1&f=geojson")
+
+# Boundary options: 
+# https://www.ons.gov.uk/methodology/geography/geographicalproducts/digitalboundaries
+    # (BFC) Full resolution - clipped to the coastline (Mean High Water mark)
+    # (BFE) Full resolution - extent of the realm (usually this is the Mean Low Water mark but, in some cases, boundaries extend beyond this to include offshore islands)
+    # (BGC) Generalised (20m) - clipped to the coastline (Mean High Water mark)
+    # (BUC) Ultra Generalised (500m) - clipped to the coastline (Mean High Water mark)
+
+
+la_bsc = sf::read_sf("https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/Local_Authority_Districts_December_2023_Boundaries_UK_BSC/FeatureServer/0/query?outFields=*&where=1%3D1&f=geojson")
+la_bfe = sf::read_sf("https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/Local_Authority_Districts_December_2023_Boundaries_UK_BFE/FeatureServer/0/query?outFields=*&where=1%3D1&f=geojson")
+
+# BFE version is 50x larger than BSC
+object.size(la_bfe) |> as.numeric() /
+  object.size(la_bsc) |> as.numeric() 
+
+la_bfe_simplified = rmapshaper::ms_simplify(la_bfe, keep = 0.02)
+
+# BFE version is now 1.4x larger than BSC
+object.size(la_bfe_simplified) |> as.numeric() /
+  object.size(la_bsc) |> as.numeric()
+
+mapview::mapview(la_bsc) + mapview::mapview(la_bfe_simplified)
+
+la = la_bfe_simplified
 
 la = la[, c("LAD23CD", "LAD23NM")]
 # LAs in Scotland, CD starts with "S":
@@ -75,10 +99,11 @@ la_regions |>
 # check for NAs: 
 la_regions[is.na(la_regions$Region),]
 
+sf::write_sf(la_regions, "la_regions_scotland_bfe_simplified_2023.geojson", delete_dsn = TRUE)
+sf::write_sf(la, "la_uk_bfe_simplified_2023.geojson", delete_dsn = TRUE)
+
 # system("gh release upload boundaries-2024 las_scotland_2023.geojson las_2023.geojson --clobber")
-dir.create("inputdata/boundaries", showWarnings = FALSE)
-sf::write_sf(la_regions, "inputdata/boundaries/la_regions_2023.geojson", delete_dsn = TRUE)
-sf::write_sf(la, "inputdata/boundaries/las_2023.geojson", delete_dsn = TRUE)
+system("gh release upload boundaries-2024 la_regions_scotland_bfe_simplified_2023.geojson la_uk_bfe_simplified_2023.geojson --clobber")
 
 # https://github.com/nptscot/npt/releases/download/boundaries-2024/las_2023.geojson