dist.mat {REAT}

Euclidean distance matrix between points

Description

Calculation of an euclidean distance matrix between points with stated coordinates (lat, lon)

Usage

dist.mat(startpoints, sp_id, lat_start, lon_start, endpoints, ep_id, 
lat_end, lon_end, unit = "km")

Arguments

startpoints

A data frame containing the start points

sp_id

Column containing the IDs of the startpoints in the data frame startpoints

lat_start

Column containing the latitudes of the start points in the data frame startpoints

lon_start

Column containing the longitudes of the start points in the data frame startpoints

endpoints

A data frame containing the end points

ep_id

Column containing the IDs of the endpoints in the data frame endpoints

lat_end

Column containing the latitudes of the end points in the data frame endpoints

lon_end

Column containing the longitudes of the end points in the data frame endpoints

unit

Unit of the resulting distance: unit="m" for meters, unit="km" for kilometers or unit="miles" for miles

Details

The function calculates an euclidean distance matrix between points with stated coordinates (lat and lon). While m start points and n end points are given, the output is a linear m * n distance matrix.

Value

The function returns a data.frame containing 4 columns: The start point IDs (from), the end point IDs (to), the combination of both (from_to) and the calculated distance (distance).

Author(s)

Thomas Wieland

References

de Lange, N. (2013): “Geoinformatik in Theorie und Praxis”. 3rd edition. Berlin : Springer Spektrum.

Krider, R. E./Putler, R. S. (2013): “Which Birds of a Feather Flock Together? Clustering and Avoidance Patterns of Similar Retail Outlets”. In: Geographical Analysis, 45, 2, p. 123-149

See Also

dist, dist.buf

Examples

citynames <- c("Goettingen", "Karlsruhe", "Freiburg")
lat <- c(51.556307, 49.009603, 47.9874)
lon <- c(9.947375, 8.417004, 7.8945)
citynames <- c("Goettingen", "Karlsruhe", "Freiburg")
cities <- data.frame(citynames, lat, lon)
dist.mat (cities, "citynames", "lat", "lon", cities, "citynames", "lat", "lon")
# Euclidean distance matrix (3 x 3 cities = 9 distances)
dist.buf (cities, "citynames", "lat", "lon", cities, "citynames", "lat", "lon", bufdist = 300000)
# Cities within 300 km