ben/wisconsin_crashes
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edited municipality maps, played around with census tract data

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This commit is contained in:
Ben Varick 2024-08-02 18:05:23 -05:00
parent cba47e7bdd
commit 07bc51e525
Signed by: ben
SSH Key Fingerprint: SHA256:jWnpFDAcacYM5aPFpYRqlsamlDyKNpSj3jj+k4ojtUo
2 changed files with 39 additions and 5 deletions
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30
scripts/dynamic_crash_map.R
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@ -129,6 +129,7 @@ Pedestrian_Crash_Data <- TOPS_data %>%
select(c(all_of(focus_columns), "longitude", "latitude"))
County_Crash_Data <- Pedestrian_Crash_Data %>%
filter(PedestrianInjurySeverity %in% c("Fatality", "Suspected Serious Injury", "Suspected Minor Injury")) %>%
group_by(County, Year) %>%
summarise(TotalCrashes = n(),
longitude = mean(longitude, na.rm = TRUE),
@ -151,6 +152,35 @@ County_Crash_geom$CrashesPerPopulation[is.na(County_Crash_geom$CrashesPerPopulat
county_pal <- colorNumeric(palette = "YlOrRd", domain = c(min(County_Crash_geom$CrashesPerPopulation, na.rm = TRUE), max(County_Crash_geom$CrashesPerPopulation, na.rm = TRUE)))
# ---- census block data
census_year <- 2020
state <- "WI"
tract_data <- st_transform(get_decennial(
geography = "tract",
variables = "P1_001N", # Total population variable for 2020 census
state = state,
year = census_year,
geometry = TRUE
),
crs = 4326)
Census_Crash_geom <- st_join(tract_data,
st_as_sf(Pedestrian_Crash_Data %>% filter(PedestrianInjurySeverity %in% c("Fatality", "Suspected Serious Injury", "Suspected Minor Injury"),
latitude > 0),
coords = c("longitude", "latitude"),
crs = 4326),
join = st_contains) %>%
group_by(GEOID, value) %>%
summarize(crash_count = n()) %>%
filter(value > 0) %>%
mutate(CrashesPerPopulation = crash_count/(value/100000))
census_pal <- colorNumeric(palette = "YlOrRd", domain = c(min(Census_Crash_geom$CrashesPerPopulation, na.rm = TRUE), 3000))
#---- make map
#title style
tag.map.title <- tags$style(HTML("
.leaflet-control.map-title {

12
scripts/municipality_maps.R
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@ -117,10 +117,12 @@ school_symbol <- image_read_svg(path = "other/school_FILL0_wght400_GRAD0_opsz24.
#county_focus <- str_to_upper(unique(WI_schools %>% pull(CTY_DIST)))
#county_focus <- c("DANE")
county_focus <- c("DANE")
county_focus <- "Dane"
municipality_focus <- c("Monona", "Verona", "Fitchburg")
municipality_geom <- st_read("data/WI_Cities,_Towns_and_Villages_January_2024.geojson")
#municipality_focus <- c("Mcfarland")
#municipality_focus <- c("Monona", "Fitchburg")
municipality_focus <- municipality_geom %>% filter(CNTY_NAME == county_focus) %>% pull(MCD_NAME)
for(municipality in municipality_focus) {
@ -131,8 +133,10 @@ for(municipality in municipality_focus) {
readRDS(file_drawer("index.rds"))
file_drawer("index.rds")
municipality_filtered <- municipality_geom %>% filter(CNTY_NAME == county_focus, MCD_NAME == municipality) %>% pull(geometry)
# create bounding box from school, 5km away.
bbox_poly <- st_transform(st_buffer(municipality_geom %>% filter(MCD_NAME == municipality) %>% pull(geometry), 1000), crs = 4326)
bbox_poly <- st_transform(st_buffer(municipality_filtered, 1000), crs = 4326)
bbox <- st_bbox(bbox_poly)
bbox <- c(left = as.double(bbox[1]),
bottom = as.double(bbox[2]),
@ -185,7 +189,7 @@ for(municipality in municipality_focus) {
shape = 23,
size = 3) +
scale_fill_manual(values = injury_severity$color, name = "Crash Severity") +
geom_sf(data = municipality_geom %>% filter(MCD_NAME == municipality),
geom_sf(data = municipality_filtered,
inherit.aes = FALSE,
color = 'black',
fill = NA,