multi_county_distance: Hurricane exposure by distance for communities

In geanders/hurricaneexposure: Explore and Map County-Level Hurricane Exposure in the United States

Description

This function takes a dataframe with multi-county communities and returns a community-level dataframe of "exposed" storms, based on the shortest distance between the storm's track and the population-based centers of each county in the community.

Usage

multi_county_distance(communities, start_year, end_year, dist_limit)

Arguments

communities	A dataframe with the FIPS codes for all counties within each community. It must include columns with a column identifier (commun) and with the FIPS codes of counties included in each community (fips). See the example code.
start_year	Four-digit integer with first year to consider.
end_year	Four-digit integer with last year to consider.
dist_limit	Maximum distance, in kilometers, of how close the storm track must come to the county's population mean center to classify the county as "exposed" to the storm.

Value

Returns the same type dataframe as county_distance, but with storms listed by community instead of county.

Examples

# Ensure that data package is available before running the example.
#  If it is not, see the `hurricaneexposure` package vignette for details
# on installing the required data package.
if (requireNamespace("hurricaneexposuredata", quietly = TRUE)) {

communities <- data.frame(community_name = c(rep("ny", 6), "no", "new"),
                         fips = c("36005", "36047", "36061",
                                  "36085", "36081", "36119",
                                  "22071", "51700"))
distance_df <- multi_county_distance(communities = communities,
                                     start_year = 1995, end_year = 2005,
                                     dist_limit = 75)
}

geanders/hurricaneexposure documentation built on Feb. 16, 2020, 8:19 a.m.