-
Main R script
-
## school focus
-school_focus <- data.frame(name = c("East High School"), NCES_CODE = c("550852000925"))
-
-## walk boundary
-walk_boundary_m <- 1.5 * 1609
-
-## load school locations
-
-WI_schools <- st_transform(st_read(dsn = "data/Schools/Wisconsin_Public_Schools_-5986231931870160084.gpkg"), crs = 4326)
-
## Reading layer `WI_Public_Schools' from data source
-## `/home/ben/Bike Fed/Documents/data_analysis/route_analysis/data/Schools/Wisconsin_Public_Schools_-5986231931870160084.gpkg'
-## using driver `GPKG'
-## replacing null geometries with empty geometries
-## Simple feature collection with 2274 features and 32 fields (with 120 geometries empty)
-## Geometry type: POINT
-## Dimension: XY
-## Bounding box: xmin: 298957.7 ymin: 225953.4 xmax: 760547.6 ymax: 704946.8
-## Projected CRS: NAD83(HARN) / Wisconsin Transverse Mercator
-
WI_schools <- WI_schools %>% mutate(geom = SHAPE)
-
-## load addresses
-addresses <- read_csv(file="data/addresses/Addresses_Students_EastHS_2024_GeocodeResults.csv") %>%
- filter(lat > 0) %>%
- st_as_sf(coords=c("lon","lat"), crs=4326) # remember x=lon and y=lat
-
-## set osrm options
-options(osrm.server = "http://127.0.0.1:5000/")
-options(osrm.profile = "walk")
-
-register_stadiamaps(key = substr(read_file(file = "api_keys/stadia_api_key"), 1, 36))
-
-## subset addresses within 1.5 miles
-walk_boundary_poly <- fill_holes(st_make_valid(osrmIsodistance(
- loc = WI_schools %>% filter(NCES_CODE %in% school_focus$NCES_CODE),
- breaks = c(walk_boundary_m),
- res = 80)
-), units::set_units(1, km^2))
-
-addresses_near <- st_intersection(addresses, walk_boundary_poly)
-
-## load bike tls
-bike_lts <- st_read("data/bike_lts/bike_lts_DANE.geojson")
-
## Reading layer `Bike_LTS' from data source
-## `/home/ben/Bike Fed/Documents/data_analysis/route_analysis/data/bike_lts/bike_lts_DANE.geojson'
-## using driver `GeoJSON'
-## Simple feature collection with 43355 features and 5 fields
-## Geometry type: MULTILINESTRING
-## Dimension: XY
-## Bounding box: xmin: -89.84212 ymin: 42.8404 xmax: -89.0082 ymax: 43.2942
-## Geodetic CRS: WGS 84
-
bike_lts[["lts"]] <- as.factor(bike_lts$LTS_F)
-
-bike_lts_scale <- data.frame(code = c(1, 2, 3, 4, 9),
- color = c("#1a9641",
- "#a6d96a",
- "#fdae61",
- "#d7191c",
- "#d7191c"))
-
-## calculate routes
-routes <- list(NULL)
-for(i in addresses_near$number) {
- routes[[i]] <- osrmRoute(
- src = addresses_near %>% filter(number == i),
- dst = WI_schools %>% filter(NCES_CODE %in% school_focus$NCES_CODE))
- message(paste0("done - ", i, "of", max(addresses_near$number)))
-}
-routes <- bind_rows(routes)
-
-## combine routes
-# Count the routes that intersect or overlap with each segment of the bike_tls network.
-# The intersections have a buffer of 20m
-bike_lts_buffer <- st_buffer(st_intersection(bike_lts, walk_boundary_poly), 20)
-
-bike_lts_buffer["student_use"] <- unlist(lapply(st_intersects(bike_lts_buffer, routes), length))
-
-bike_lts <- st_join(bike_lts, bike_lts_buffer %>% select(OBJECTID, student_use))
-
-## make maps
-# load logo
-logo <- image_read(path = "other/BFW_Logo_180_x_200_transparent_background.png")
-school_symbol <- image_read_svg(path = "other/school_FILL0_wght400_GRAD0_opsz24.svg")
-
-
-bbox <- st_bbox(st_buffer(walk_boundary_poly, dist = 500))
-bbox <- c(left = as.double(bbox[1]),
- bottom = as.double(bbox[2]),
- right = as.double(bbox[3]),
- top = as.double(bbox[4]))
-
-#get basemap
-basemap <- get_stadiamap(bbox = bbox, zoom = 15, maptype = "stamen_toner_lite")
-
-# generate map
-ggmap(basemap) +
- labs(title = paste0("Walking routes for students at ",
- school_focus %>% pull(name)),
- subtitle = "only showing routes within the 1.5 walk boundary",
- x = NULL,
- y = NULL,
- color = NULL,
- linewidth = "Potential student walkers") +
- theme(axis.text=element_blank(),
- axis.ticks=element_blank(),
- plot.caption = element_text(color = "grey")) +
- geom_sf(data = walk_boundary_poly,
- inherit.aes = FALSE,
- aes(color = paste0(1.5, " mile walking boundary")),
- fill = NA,
- linewidth = 1) +
- scale_color_manual(values = "blue", name = NULL) +
- new_scale_color() +
- geom_sf(data = bike_lts %>% filter(!is.na(student_use), student_use > 3),
- inherit.aes = FALSE,
- aes(linewidth = student_use),
- color = "mediumvioletred",
- fill = NA) +
- scale_linewidth_continuous(range = c(0, 3)) +
- annotation_raster(school_symbol,
- # Position adjustments here using plot_box$max/min/range
- ymin = as.double((WI_schools %>% filter(NCES_CODE %in% school_focus$NCES_CODE) %>% pull(geom))[[1]])[2] - 0.001,
- ymax = as.double((WI_schools %>% filter(NCES_CODE %in% school_focus$NCES_CODE) %>% pull(geom))[[1]])[2] + 0.001,
- xmin = as.double((WI_schools %>% filter(NCES_CODE %in% school_focus$NCES_CODE) %>% pull(geom))[[1]])[1] - 0.0015,
- xmax = as.double((WI_schools %>% filter(NCES_CODE %in% school_focus$NCES_CODE) %>% pull(geom))[[1]])[1] + 0.0015) +
- geom_sf_label(data = WI_schools %>% filter(NCES_CODE %in% school_focus$NCES_CODE),
- inherit.aes = FALSE,
- mapping = aes(label = school_focus %>% pull(name)),
- nudge_y = 0.0015,
- label.size = 0.04,
- size = 2)
-
-
ggsave(file = paste0("figures/",
- school_focus %>% pull(name),
- " Routes.pdf"),
- title = paste0(school_focus %>% pull(name), " Walking Routes"),
- device = pdf,
- height = 8.5,
- width = 11,
- units = "in",
- create.dir = TRUE)
-
-# generate map
-ggmap(basemap) +
- labs(title = paste0("Walking routes for students at ",
- school_focus %>% pull(name)),
- subtitle = "only showing routes within the walk boundary",
- x = NULL,
- y = NULL,
- color = NULL,
- linewidth = "Potential student walkers") +
- theme(axis.text=element_blank(),
- axis.ticks=element_blank(),
- plot.caption = element_text(color = "grey")) +
- geom_sf(data = walk_boundary_poly,
- inherit.aes = FALSE,
- aes(color = paste0(1.5, " mile walking boundary")),
- fill = NA,
- linewidth = 1) +
- scale_color_manual(values = "blue", name = NULL) +
- new_scale_color() +
- geom_sf(data = bike_lts %>% filter(!is.na(student_use), student_use > 0),
- inherit.aes = FALSE,
- aes(color = lts,
- linewidth = student_use)) +
- scale_color_manual(values = bike_lts_scale$color, name = "Bike Level of Traffic Stress") +
- scale_linewidth_continuous(range = c(0, 3)) +
- annotation_raster(school_symbol,
- # Position adjustments here using plot_box$max/min/range
- ymin = as.double((WI_schools %>% filter(NCES_CODE %in% school_focus$NCES_CODE) %>% pull(geom))[[1]])[2] - 0.001,
- ymax = as.double((WI_schools %>% filter(NCES_CODE %in% school_focus$NCES_CODE) %>% pull(geom))[[1]])[2] + 0.001,
- xmin = as.double((WI_schools %>% filter(NCES_CODE %in% school_focus$NCES_CODE) %>% pull(geom))[[1]])[1] - 0.0015,
- xmax = as.double((WI_schools %>% filter(NCES_CODE %in% school_focus$NCES_CODE) %>% pull(geom))[[1]])[1] + 0.0015) +
- geom_sf_label(data = WI_schools %>% filter(NCES_CODE %in% school_focus$NCES_CODE),
- inherit.aes = FALSE,
- mapping = aes(label = school_focus %>% pull(name)),
- nudge_y = 0.0015,
- label.size = 0.04,
- size = 2)
-
-
ggsave(file = paste0("figures/",
- school_focus %>% pull(name),
- " Routes - Traffic Stress.pdf"),
- title = paste0(school_focus %>% pull(name), " Walking Routes - Traffic Stress"),
- device = pdf,
- height = 8.5,
- width = 11,
- units = "in",
- create.dir = TRUE)
-
-ggmap(basemap) +
- labs(title = paste0("Student homes at ",
- school_focus %>% pull(name)),
- x = NULL,
- y = NULL,
- color = NULL,
- fill = "How many students live there") +
- theme(axis.text=element_blank(),
- axis.ticks=element_blank(),
- plot.caption = element_text(color = "grey")) +
- geom_hex(data = addresses %>% extract(geometry, into = c('Lat', 'Lon'), '\\((.*),(.*)\\)', conv = T),
- aes(x = Lat,
- y = Lon),
- alpha = 0.7) +
- scale_fill_distiller(palette = "YlOrRd", direction = "reverse") +
- geom_sf(data = walk_boundary_poly,
- inherit.aes = FALSE,
- aes(color = paste0(1.5, " mile walking boundary")),
- fill = NA,
- linewidth = 1) +
- scale_color_manual(values = "blue", name = NULL) +
- new_scale_color() +
- annotation_raster(school_symbol,
- # Position adjustments here using plot_box$max/min/range
- ymin = as.double((WI_schools %>% filter(NCES_CODE %in% school_focus$NCES_CODE) %>% pull(geom))[[1]])[2] - 0.001,
- ymax = as.double((WI_schools %>% filter(NCES_CODE %in% school_focus$NCES_CODE) %>% pull(geom))[[1]])[2] + 0.001,
- xmin = as.double((WI_schools %>% filter(NCES_CODE %in% school_focus$NCES_CODE) %>% pull(geom))[[1]])[1] - 0.0015,
- xmax = as.double((WI_schools %>% filter(NCES_CODE %in% school_focus$NCES_CODE) %>% pull(geom))[[1]])[1] + 0.0015) +
- geom_sf_label(data = WI_schools %>% filter(NCES_CODE %in% school_focus$NCES_CODE),
- inherit.aes = FALSE,
- mapping = aes(label = school_focus %>% pull(name)),
- nudge_y = 0.0015,
- label.size = 0.04,
- size = 2)
-
-
ggsave(file = paste0("figures/",
- school_focus %>% pull(name),
- " Addresses.pdf"),
- title = paste0(school_focus %>% pull(name), " Addresses"),
- device = pdf,
- height = 8.5,
- width = 11,
- units = "in",
- create.dir = TRUE)
-