#' Read in HIFLD Facility level Data
#'
#' Reads in data from HIFLD on facility information including population, adds
#' coordinates (latitude and longitude) for the centroid of each facility, replaces
#' -999 population and capacity values with NA.
#'
#' @return data frame with facility info and coordinates
#'
#' @import dplyr
#' @importFrom geojsonsf geojson_sf
#' @export
#'
#' @examples
#' \dontrun{
#' read_hifld_data()
#' }
read_hifld_data <- function(){
"https://opendata.arcgis.com/datasets/2d6109d4127d458eaf0958e4c5296b67_0.geojson" %>%
geojson_sf() %>%
# we have to manually set the CRS here because of GDAL version issues
# so ignoring the warnings is fine in this case
{suppressWarnings(mutate(., geometry = sf::st_set_crs(geometry, 4326)))} %>%
mutate(geometry = sf::st_transform(geometry, 2901),
coords = sf::st_centroid(geometry),
coords = sf::st_transform(coords, 4326)) %>%
as_tibble() %>%
mutate(lon = sf::st_coordinates(coords)[,1] %>% unname(),
lat = sf::st_coordinates(coords)[,2] %>% unname()) %>%
rename(hifld_id = FACILITYID) %>%
mutate(POPULATION = na_if(POPULATION, -999),
CAPACITY = na_if(CAPACITY, -999),
WEBSITE = na_if(WEBSITE, "NOT AVAILABLE")) %>%
select(hifld_id,
NAME,
ADDRESS,
CITY,
STATE,
ZIP,
TELEPHONE,
TYPE,
STATUS,
POPULATION,
COUNTY,
COUNTYFIPS,
COUNTRY,
NAICS_CODE,
NAICS_DESC,
SOURCE,
SOURCEDATE,
VAL_METHOD,
VAL_DATE,
WEBSITE,
SECURELVL,
CAPACITY,
lat,
lon)
}
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