Anirudh Govind (16 November, 2020)
# Load Bangalore ward boundary
bangaloreWardBoundary <- read_sf(here::here("data/raw-data/bangaloreWardBoundary.shp"))
bangaloreWardBoundary <- bangaloreWardBoundary%>%
st_transform(3857)# Load in previously downloaded data from OSM
#
# bangaloreBuildings <- readRDS(here::here("data/raw-data/bangaloreBuildings.rds"))
#
# bangaloreBuildings <- bangaloreBuildings %>%
# select(osm_id, geometry)
#
# bangaloreBuildings <- bangaloreBuildings %>%
# st_transform(3857)# Get cycle path data from OSM. Looks like there are multiple tags for cycleways. I'll have to query OSM multiple times.
# Query A
#
# queryA <- getbb("Bangalore") %>%
# opq() %>%
# add_osm_feature("cycleway")
#
# str(queryA)
#
# cycleWaysA <- osmdata_sf(queryA)
#
# saveRDS(cycleWaysA, here::here("data/raw-data/cycleWaysA.rds"))
cycleWaysA <- readRDS(here::here("data/raw-data/cycleWaysA.rds"))
# Query B
#
# queryB <- getbb("Bangalore") %>%
# opq() %>%
# add_osm_feature("highway", "cycleway")
#
# str(queryB)
#
# cycleWaysB <- osmdata_sf(queryB)
#
# saveRDS(cycleWaysB, here::here("data/raw-data/cycleWaysB.rds"))
cycleWaysB <- readRDS(here::here("data/raw-data/cycleWaysB.rds"))
# Query C
# queryC <- getbb("Bangalore") %>%
# opq() %>%
# add_osm_feature("cycleway", "track")
#
# str(queryC)
#
# cycleWaysC <- osmdata_sf(queryC)
#
# saveRDS(cycleWaysC, here::here("data/raw-data/cycleWaysC.rds"))
#
# cycleWaysC <- readRDS(here::here("data/raw-data/cycleWaysC.rds"))
# I think that is all the tagging schemes.# Okay. So each tagging scheme contains lines as well as polygons. I'll have to extract and combine accordingly.
# Lines
cycleLinesA <- cycleWaysA$osm_lines
cycleLinesB <- cycleWaysB$osm_lines
# cycleLinesC <- cycleWaysC$osm_lines
# Polygons
cyclePolygonsA <- cycleWaysA$osm_polygons
# cyclePolygonsB <- cycleWaysB$osm_polygons
# cyclePolygonsC <- cycleWaysC$osm_polygons
# PolygonsB & C have 0 observations so I can discard them. PolygonsA are all marked as private. I want only the ones which the general public has access to, so I'm going to ignore the rest of it.
# Keep only needed info. I'm keeping only those marked explicitly as yes to bicycles. I'm also going to discard cycleLinesC.
cycleLinesA <- cycleLinesA %>%
filter(bicycle == "yes") %>%
select(osm_id, geometry)
cycleLinesB <- cycleLinesB %>%
select(osm_id, geometry)
# Bind rows
cycleLines <- bind_rows(cycleLinesA, cycleLinesB)
cycleLines <- cycleLines %>%
st_transform(3857)
# Quick viz
tm_shape(cycleLines) +
tm_lines()
# I want to present the areas around these cyclepaths as islands in Bangalore. I'll show the buildings within these buffers as islands. I like the visuals of townscaper the video game and will try and replicate them.# Buffers of 1000m around the cycle lines
cycleIslands <- st_buffer(cycleLines,
singleSide = T,
dist = c(900, -100))
# Clip to Bangalore's boundary
cycleIslands <- st_intersection(cycleIslands, bangaloreWardBoundary)## Warning: attribute variables are assumed to be spatially constant throughout all
## geometries
# Okay. I quite like the output that's showing up with the test visuals. The variable buffers make a huge difference.
cycleIslandsBoundary <- st_union(cycleIslands)
# I want buffers around the islands
cycleIslandsBufferA <- st_buffer(cycleIslandsBoundary, 100)
cycleIslandsBufferA <- st_intersection(cycleIslandsBufferA, bangaloreWardBoundary)
cycleIslandsBufferB <- st_buffer(cycleIslandsBoundary, 600)
cycleIslandsBufferB <- st_intersection(cycleIslandsBufferB, bangaloreWardBoundary)
cycleIslandsBufferC <- st_buffer(cycleIslandsBoundary, 1000)
cycleIslandsBufferC <- st_intersection(cycleIslandsBufferC, bangaloreWardBoundary)
cycleIslandsBufferD <- st_buffer(cycleIslandsBoundary, 5000)
cycleIslandsBufferD <- st_intersection(cycleIslandsBufferD, bangaloreWardBoundary)# Clip to buildings
#
# buildingIslands <- st_intersection(bangaloreBuildings, cycleIslands)
#
# buildingIslands <- buildingIslands %>%
# select(osm_id, geometry) %>%
# st_union(.)
# Okay. The buildings don't look great. I'm going to leave them out.# Palettes
# Blue: "#219ebc"
# Browns: "#edc4b3" "#c38e70" "#774936"
# Put layers together
mapBangaloreCycleIslands <- tm_shape(bangaloreWardBoundary) +
tm_fill(col = "#219ebc") +
tm_borders(col = "#ffffff",
lwd = 3,
lty = "dashed") +
tm_layout(bg.color = "#219ebc",
frame = F,
attr.outside = T,
outer.margins = 0,
asp = 0,
scale = 0.8,
main.title = "Bangalore's Cycle Network Exaggerated as Islands",
main.title.color = "#ffffff",
main.title.size = 1.75,
main.title.fontface = 2,
main.title.fontfamily = "Arial Narrow") +
tm_credits("#30DayMapChallenge | Day 16 | Anirudh Govind | Nov 2020\nMap data © OpenStreetMap contributors and available from https://www.openstreetmap.org",
col = "#ffffff",
size = 0.8,
position = c("left", "bottom"),
fontfamily = "Arial Narrow") +
tm_shape(cycleIslands) +
tm_fill(col = "#edc4b3") +
tm_shape(cycleIslandsBoundary) +
tm_borders(col = "#ffffff") +
tm_shape(cycleIslandsBufferA) +
tm_borders(col = "#ffffff",
lwd = 0.75) +
tm_shape(cycleIslandsBufferB) +
tm_borders(col = "#ffffff",
lwd = 0.45,
alpha = 0.6) +
tm_shape(cycleIslandsBufferC) +
tm_borders(col = "#ffffff",
lwd = 0.25,
alpha = 0.3) +
tm_shape(cycleIslandsBufferD) +
tm_borders(col = "#ffffff",
lwd = 0.15,
alpha = 0.5)# Export the map as an image to upload onto twitter
tmap_save(tm = mapBangaloreCycleIslands,
filename = here::here("exports/Day16.png"),
dpi = 450,
width = 200,
height = 200,
units = "mm")## Map saved to G:\00_Git Repos\30DayMapChallenge\exports\Day16.png
## Resolution: 3543.307 by 3543.307 pixels
## Size: 7.874016 by 7.874016 inches (450 dpi)