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route_analysis/R/route_analysis.Rmd
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Working my way through the code trying to understand it. Added section headers, broke code into chunks, moved a couple of lines, etc.
2024-10-31 17:12:08 -05:00

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---
title: "East High Active Travel"
output:
html_document:
toc: true
toc_depth: 5
toc_float:
collapsed: false
smooth_scroll: true
---
# Input Data & Configuration
## Libraries
```{r libs, eval = TRUE, echo = TRUE, results = "show", warning = FALSE, error = TRUE, message = FALSE}
date()
rm(list=ls())
library(tidyverse)
library(ggmap)
library(sf)
library(osrm)
library(smoothr)
library(magick)
library(ggnewscale)
library(rsvg)
fig.height <- 6
set.seed(1)
```
## GeoPackage Data
```{r gpkg, eval = TRUE, echo = TRUE, results = "show", warning = FALSE, error = TRUE, message = FALSE}
WI_schools <- st_transform(st_read(dsn = "data/Schools/Wisconsin_Public_Schools_-5986231931870160084.gpkg"), crs = 4326)
WI_schools <- WI_schools %>% mutate(geom = SHAPE)
```
## Addresses Data
```{r addresses, eval = TRUE, echo = TRUE, results = "show", warning = FALSE, error = TRUE, message = FALSE}
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
```
## Open Source Routing Machine (OSRM)
```{r osrm, eval = TRUE, echo = TRUE, results = "show", warning = FALSE, error = TRUE, message = FALSE}
options(osrm.server = "http://127.0.0.1:5000/")
options(osrm.profile = "walk")
```
## Stadia Maps API Key
```{r stadiamaps, eval = TRUE, echo = TRUE, results = "show", warning = FALSE, error = TRUE, message = FALSE}
register_stadiamaps(key = substr(read_file(file = "api_keys/stadia_api_key"), 1, 36))
```
# Analysis
## Subset Addresses Within 1.5 Miles
```{r walkBoundary, eval = TRUE, echo = TRUE, results = "show", warning = FALSE, error = TRUE, message = FALSE}
walk_boundary_m <- 1.5 * 1609 ## walk boundary
school_focus <- data.frame(name = c("East High School"), NCES_CODE = c("550852000925")) ## school focus
walk_boundary_poly <- fill_holes(st_make_valid(osrmIsodistance(
loc = st_transform(WI_schools %>% filter(NCES_CODE %in% school_focus$NCES_CODE), crs = 4326),
breaks = c(walk_boundary_m),
res = 80)
), units::set_units(1, km^2))
addresses_near <- st_intersection(addresses, walk_boundary_poly)
```
## Bike Level of Traffic Stress (LTS)
```{r bikelts, eval = TRUE, echo = TRUE, results = "show", warning = FALSE, error = TRUE, message = FALSE}
bike_lts <- st_read("data/bike_lts/bike_lts_DANE.geojson")
bike_lts[["lts"]] <- as.factor(bike_lts$LTS_F)
bike_lts_scale <- data.frame(code = c(1, 2, 3, 4, 9),
color = c("#1a9641",
"#a6d96a",
"#fdae61",
"#d7191c",
"#d7191c"))
```
## The Rest
```{r therest, eval = TRUE, echo = TRUE, results = "show", warning = FALSE, error = TRUE, message = FALSE}
## 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$number)))
}
routes <- bind_rows(routes)
## combine routes
# Count the routes that intersect or overlap with each segment of the bike_tls network.
# The intersections have a buffer of 20m
bike_lts_buffer <- st_buffer(st_intersection(bike_lts, walk_boundary_poly), 20)
bike_lts_buffer["student_use"] <- unlist(lapply(st_intersects(bike_lts_buffer, routes), length))
bike_lts <- st_join(bike_lts, bike_lts_buffer %>% select(OBJECTID, student_use))
## make maps
# load logo
logo <- image_read(path = "other/BFW_Logo_180_x_200_transparent_background.png")
school_symbol <- image_read_svg(path = "other/school_FILL0_wght400_GRAD0_opsz24.svg")
bbox <- st_bbox(st_transform(st_buffer(walk_boundary_poly, dist = 500), crs = 4326))
bbox <- c(left = as.double(bbox[1]),
bottom = as.double(bbox[2]),
right = as.double(bbox[3]),
top = as.double(bbox[4]))
#get basemap
basemap <- get_stadiamap(bbox = bbox, zoom = 15, maptype = "stamen_toner_lite")
# generate map
ggmap(basemap) +
labs(title = paste0("Walking routes for students at ",
school_focus %>% pull(name)),
subtitle = "only showing routes within the 1.5 walk boundary",
x = NULL,
y = NULL,
color = NULL,
linewidth = "Potential student walkers") +
theme(axis.text=element_blank(),
axis.ticks=element_blank(),
plot.caption = element_text(color = "grey")) +
geom_sf(data = walk_boundary_poly,
inherit.aes = FALSE,
aes(color = paste0(1.5, " mile walking boundary")),
fill = NA,
linewidth = 1) +
scale_color_manual(values = "blue", name = NULL) +
new_scale_color() +
geom_sf(data = bike_lts %>% filter(!is.na(student_use), student_use > 3),
inherit.aes = FALSE,
aes(linewidth = student_use),
color = "mediumvioletred",
fill = NA) +
scale_linewidth_continuous(range = c(0, 3)) +
annotation_raster(school_symbol,
# Position adjustments here using plot_box$max/min/range
ymin = as.double((st_transform(WI_schools %>% filter(NCES_CODE %in% school_focus$NCES_CODE), crs = 4326) %>% pull(geom))[[1]])[2] - 0.001,
ymax = as.double((st_transform(WI_schools %>% filter(NCES_CODE %in% school_focus$NCES_CODE), crs = 4326) %>% pull(geom))[[1]])[2] + 0.001,
xmin = as.double((st_transform(WI_schools %>% filter(NCES_CODE %in% school_focus$NCES_CODE), crs = 4326) %>% pull(geom))[[1]])[1] - 0.0015,
xmax = as.double((st_transform(WI_schools %>% filter(NCES_CODE %in% school_focus$NCES_CODE), crs = 4326) %>% pull(geom))[[1]])[1] + 0.0015) +
geom_sf_label(data = st_transform(WI_schools %>% filter(NCES_CODE %in% school_focus$NCES_CODE), crs = 4326),
inherit.aes = FALSE,
mapping = aes(label = school_focus %>% pull(name)),
nudge_y = 0.0015,
label.size = 0.04,
size = 2)
ggsave(file = paste0("figures/",
school_focus %>% pull(name),
" Routes.pdf"),
title = paste0(school_focus %>% pull(name), " Walking Routes"),
device = pdf,
height = 8.5,
width = 11,
units = "in",
create.dir = TRUE)
# generate map
ggmap(basemap) +
labs(title = paste0("Walking routes for students at ",
school_focus %>% pull(name)),
subtitle = "only showing routes within the walk boundary",
x = NULL,
y = NULL,
color = NULL,
linewidth = "Potential student walkers") +
theme(axis.text=element_blank(),
axis.ticks=element_blank(),
plot.caption = element_text(color = "grey")) +
geom_sf(data = walk_boundary_poly,
inherit.aes = FALSE,
aes(color = paste0(1.5, " mile walking boundary")),
fill = NA,
linewidth = 1) +
scale_color_manual(values = "blue", name = NULL) +
new_scale_color() +
geom_sf(data = bike_lts %>% filter(!is.na(student_use), student_use > 0),
inherit.aes = FALSE,
aes(color = lts,
linewidth = student_use)) +
scale_color_manual(values = bike_lts_scale$color, name = "Bike Level of Traffic Stress") +
scale_linewidth_continuous(range = c(0, 3)) +
annotation_raster(school_symbol,
# Position adjustments here using plot_box$max/min/range
ymin = as.double((st_transform(WI_schools %>% filter(NCES_CODE %in% school_focus$NCES_CODE), crs = 4326) %>% pull(geom))[[1]])[2] - 0.001,
ymax = as.double((st_transform(WI_schools %>% filter(NCES_CODE %in% school_focus$NCES_CODE), crs = 4326) %>% pull(geom))[[1]])[2] + 0.001,
xmin = as.double((st_transform(WI_schools %>% filter(NCES_CODE %in% school_focus$NCES_CODE), crs = 4326) %>% pull(geom))[[1]])[1] - 0.0015,
xmax = as.double((st_transform(WI_schools %>% filter(NCES_CODE %in% school_focus$NCES_CODE), crs = 4326) %>% pull(geom))[[1]])[1] + 0.0015) +
geom_sf_label(data = st_transform(WI_schools %>% filter(NCES_CODE %in% school_focus$NCES_CODE), crs = 4326),
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$max/min/range
ymin = as.double((st_transform(WI_schools %>% filter(NCES_CODE %in% school_focus$NCES_CODE), crs = 4326) %>% pull(geom))[[1]])[2] - 0.001,
ymax = as.double((st_transform(WI_schools %>% filter(NCES_CODE %in% school_focus$NCES_CODE), crs = 4326) %>% pull(geom))[[1]])[2] + 0.001,
xmin = as.double((st_transform(WI_schools %>% filter(NCES_CODE %in% school_focus$NCES_CODE), crs = 4326) %>% pull(geom))[[1]])[1] - 0.0015,
xmax = as.double((st_transform(WI_schools %>% filter(NCES_CODE %in% school_focus$NCES_CODE), crs = 4326) %>% pull(geom))[[1]])[1] + 0.0015) +
geom_sf_label(data = st_transform(WI_schools %>% filter(NCES_CODE %in% school_focus$NCES_CODE), crs = 4326),
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)
```
# Appendix
```{r chunklast, eval = TRUE, echo = TRUE, results = "show", warning = TRUE, error = TRUE, message = TRUE}
date()
sessionInfo()
```
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