4  Distance from Storm Track

4.1 Data Procurement

• Hurricane track data was downloaded from the hurricaneexposuredata package using the data("hurr_tracks") command. This data originates from the HURDAT2.
• ZCTA to County Crosswalk was downloaded from https://www2.census.gov/geo/docs/maps-data/data/rel/zcta_county_rel_10.txt
• ZCTA shapefiles were downloaded for the entire US using the tigris package

4.2 Data Processing

1. Hurricane data was downloaded using hurricaneexposuredata package using the data("hurr_tracks") command and filtered using the Harvey Automated Tropical Cyclone Forecasting code (AL092017)
2. Hurricane track was imputed to every 15 minutes using create_full_track from the stormwindmodel package.
3. Separately, 2017 ZCTAs downloaded from the US Census Cartographic Boundary Files
4. Then, the ZCTAs were joined to the US Census ZCTA to County Crosswalk in order to identify Texas and Louisiana ZCTAs
5. The ZCTAs were filtered to Texas and Louisiana
6. ZCTA geo centroid were calculated
7. The distance from geo-centroid of each ZCTA to closest point on imputed track and time when imputed track was closest were calculated

4.3 Output

• TXLA_ZCTA_dist2track
  • GEOID - ZCTA GEOID
  • dist2track - Distance from geo-centroid to closest point on imputed track (meters)
  • dateTime - UTC date and time where geo-centroid is closest to imputed track

Download, filter, and impute hurricane tract

library(tidyverse)
library(sf)
library(hurricaneexposure)

data(hurr_tracks, package = "hurricaneexposuredata")

AL092017_track <- hurr_tracks %>%
  filter(usa_atcf_id == "AL092017") %>%
  create_full_track() %>%
  arrange(date) %>%
  st_as_sf(coords = c("tclon", "tclat"), crs = "epsg:4269")

AL092017_track_line <- AL092017_track %>%
  st_combine() %>%
  st_cast("LINESTRING")

Downloaded ZCTA shapefiles and calculated centroids

library(tigris)

ZCTAs <- read_csv("https://www2.census.gov/geo/docs/maps-data/data/rel/zcta_county_rel_10.txt") %>%
  filter(STATE %in% c(48, 22)) %>%
  distinct(ZCTA5) %>%
  rename(GEOID = ZCTA5)

ZCTAs_sf <- ZCTAs %>%
  left_join(zctas(cb = FALSE, year = 2017), by = join_by(GEOID == GEOID10)) %>%
  st_as_sf() %>%
  select(-c(ZCTA5CE10, CLASSFP10, MTFCC10, FUNCSTAT10, ALAND10, AWATER10, INTPTLAT10, INTPTLON10))

ZCTAs_center <- ZCTAs_sf %>%
  st_transform("ESRI:102003") %>%
  st_centroid() %>%
  st_transform("EPSG:4269")

Calculated shortest distance to track from geo centroids

TXLA_dist2track <- st_join(ZCTAs_center, AL092017_track, join = st_nearest_feature) %>%
  rename(dateTime = date) %>%
  rowwise() %>%
  mutate(est_track_point = 
    AL092017_track %>%
      filter(date == dateTime) %>%
      st_geometry()
  ) %>%
  mutate(dist2track = st_distance(geometry, est_track_point)) %>%
  mutate(dist2track = as.numeric(dist2track)) %>%
  st_drop_geometry() %>%
  select(GEOID, dateTime, dist2track)

TXLA_dist2track %>%
  left_join(ZCTAs_sf) %>%
  st_as_sf() %>%
  ggplot() +
    geom_sf(aes(fill = dist2track)) +
    geom_sf(data = st_crop(AL092017_track_line, ZCTAs_sf)) +
    coord_sf(datum = "ESRI:102003") +
    scale_fill_distiller(
      palette = "Oranges",
      name = "Smallest Distance to Hurricane Track",
      direction = 1,
      guide = guide_colorbar(
        direction = "horizontal",
        title.position = "top")) +
    theme_void() +
    theme(
      plot.title = element_text(face = "bold", size = 16),
      plot.subtitle = element_text(face = "bold", size = 12),
      plot.caption = element_text(size = 10, hjust = 0),
      legend.title = element_text(face = "bold", size = 12),
      legend.text = element_text(face = "bold", size = 12),
      legend.title.align=0.5,
      legend.position = "bottom",
      legend.key.width = unit(dev.size()[1] / 10, "inches")) +
    labs(
      title = "Smallest Distance to Hurricane Track by ZCTA ", 
      subtitle = "Texas and Louisiana",
      caption = "Author: Ryan Zomorrodi\nDate: 4/1/2024\nSource: hurricaneexposuredata")

TXLA_dist2track %>%
  st_write("output/TXLA_ZCTA_dist2track.gpkg", "TXLA_ZCTA_dist2track", append = FALSE)