Abstract Map using Open Street Map

AbstractMap_UsingOpenStreetMap.r

library(tidyverse)
library(sf)
library(tidygraph)
library(igraph)

library(units)
library(tmap)
library(osmdata)
library(rgrass7)
library(link2GI)
library(nabor)
library(ggthemes)
library(ggraph)

## 
my_bbox <- c(140.841169,37.033766,140.908632,37.061785)
q <- opq(bbox=my_bbox) %>% ## bild an overpass query
  add_osm_feature(key="highway") %>%  ## highway, amenity etc. 
  osmdata_sf() %>%  ## return the data osmdata in sf format!  
  osm_poly2line()  ## circular highways are stored in polygon, so this function will combine those with line

## what does it look like?
q ## osm_lines --> shows how many linestrings!

## 
q_map <- q$osm_lines %>%
  select(name, highway) %>%
  mutate(highway = fct_infreq(highway))

## What are named road in this data
q_map %>% as_tibble() %>% count(name, sort=T)
q_map %>% as_tibble() %>% count(highway, sort=T)


## Quick Plotting
ggplot(data=q_map) +
  geom_sf(aes(color=highway)) +
  theme_map() +
  scale_color_tableau("Hue Circle") +
  coord_sf(xlim=c(my_bbox[1], my_bbox[3]), ylim=c(my_bbox[2], my_bbox[4]))



### Prepping Edges

edges <- q_map %>%
  mutate(edgeID = c(1:n()))

## creating Nodes from Edges
nodes <- edges %>%
  st_coordinates() %>% ## covert all of line segments to points
  as_tibble() %>%
  rename(edgeID = L1) %>%
  group_by(edgeID) %>%
  slice(c(1, n())) %>%  ## get first and last points
  ungroup() %>%
  mutate(start_end = rep(c('start', 'end'), times = n()/2))

nodes
## using ?group_indices to assign unique id to each of groups
nodes <- nodes %>%
  mutate(xy = paste(.$X, .$Y)) %>% 
  mutate(nodeID = group_indices(., factor(xy, levels = unique(xy)))) %>%
  select(-xy)

nodes

edges <- nodes %>% 
  select(start_end, nodeID, edgeID) %>%
  pivot_wider(id_cols=edgeID,names_from=start_end, values_from=nodeID) %>%
  rename(from=start, to=end) %>%
  inner_join(edges)

edges <-edges %>% st_as_sf()
edges

## reducing duplicate nodes
nodes <- nodes %>%
  distinct(nodeID, .keep_all = TRUE) %>%
  select(-c(edgeID, start_end)) %>%
  st_as_sf(coords = c('X', 'Y')) 

nodes <- nodes %>% st_set_crs(st_crs(edges))
nodes


## graph objects
g <- tbl_graph(nodes=nodes, edges=as_tibble(edges), directed=F)

g <- g %>%
  activate(edges) %>%
  mutate(length = st_length(geometry))

g %>% activate(edges) %>% as_tibble() 
g %>% activate(nodes) %>% as_tibble()

g <- g %>% 
  activate(nodes) %>%
  mutate(degree = centrality_degree()) %>%
  mutate(betweenness = centrality_betweenness(weights = length)) %>%
  activate(edges) %>%
  mutate(betweenness = centrality_edge_betweenness(weights = length))

ggplot() +
  geom_sf(data = g %>% activate(edges) %>% as_tibble() %>% st_as_sf(),
          aes(alpha = betweenness, size=betweenness), color="white",
          lineend="round") +  
  theme_map() +
  scale_size_continuous(range=c(0.1,1.2), guide="none", trans="sqrt") +
  scale_alpha_continuous(guide="none", range=c(0.3,1)) +
  scale_color_manual(values=gray.colors(n=18), guide="none") +
  theme(plot.background=element_rect(fill="#000000de"))+
  coord_sf(xlim=c(my_bbox[1], my_bbox[3]), ylim=c(my_bbox[2], my_bbox[4]))

abs(my_bbox[1]-my_bbox[3])/abs(my_bbox[4]-my_bbox[2]) -> asp

ggsave(filename=str_c("Map_",paste(round(my_bbox,2),collapse="_"),".pdf"), height=9, width=asp*9*0.7)