+
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)
+