jlm_neighbourhood_clustering.R

library(osmdata)
library(tidyverse)
library(tidygraph)
library(igraph)
library(sf)
library(lwgeom)
library(sfnetworks)
library(stplanr)
df <- getbb("Jerusalem",format_out = "polygon")

df[[3]][2] %>% st_polygon() %>% plot()
x <- opq(bbox = df[[3]][2]) %>%
  add_osm_feature(key = 'highway') %>%
  osmdata_sf()
types_of_highways <- x$osm_lines[,c("highway","highway_1")] %>% 
  st_drop_geometry() %>% 
  unlist() %>% 
  unique()
x$osm_polygons[,c("highway","highway_1")] %>% 
  st_drop_geometry() %>% 
  unlist() %>% 
  unique()
lines <- x$osm_lines
polygons_to_lines <- x$osm_polygons %>% st_cast("LINESTRING")
united <- bind_rows(lines,polygons_to_lines)

isin <- united %>% st_intersects(st_polygon(df[[3]][2]),sparse = F)
main_jlm <- united[isin,] %>% 
  filter(! highway %in% c("footway","steps","unclassified","path","construction","track","cycleway","proposed","pedestrian"))
nodes_to_split_by <- main_jlm %>%
  st_cast("POINT") %>% 
  group_by(osm_id) %>% 
  filter(row_number() == 1| row_number() == max(row_number())) %>% 
  st_geometry() %>% 
  st_sf() %>% 
  distinct() %>% 
  st_transform(2039) %>% 
  st_snap(main_jlm %>% st_transform(2039),tolerance = 1e-9) 

main_jlm_break <- st_split(main_jlm$geometry %>% st_transform(2039), nodes_to_split_by$geometry) %>% 
  st_collection_extract("LINESTRING") %>% 
  st_sf()
main_jlm_fin <- as_sfnetwork(main_jlm_break)
cl <- clusters(main_jlm_fin)
giant_jlm <- induced.subgraph(main_jlm_fin, which(cl$membership == which.max(cl$csize))) %>% 
  as_tbl_graph() %>% 
  as_sfnetwork() %>% 
  activate(edges) %>% 
  as_tibble() %>% 
  st_as_sf()

groups <- rnet_group(giant_jlm,igraph::cluster_fast_greedy)
giant_jlm$group <- groups
mapview::mapviewOptions(vector.palette = randomcoloR::randomColor(max(groups)))