Calculate Distance to Features

Calculates distances from point locations to features. The usual approach for eg. resource selection function analyses is to generate a complete distance to features surface then sample it with your observed and random points. Since these raster based approaches can be pretty costly with large areas, and often lead to memory issues in R, the distanceto package opts to compute these distances using efficient, vector based approaches. As a helper, there's a decidedly low-res raster based approach for visually inspecting your region's distance surface. But the workhorse is distance_to.

distance-to

Overview

The distanceto package is designed to quickly sample distances from points features to other vector layers. Normally the approach for calculating distance to (something) involves generating distance surfaces using raster based approaches eg. raster::distance or gdal_proximity and subsequently point sampling these surfaces. Since raster based approaches are a costly method that frequently leads to memory issues or long and slow run times with high resolution data or large study sites, we have opted to compute these distances using vector based approaches. As a helper, there’s a decidedly low-res raster based approach for visually inspecting your region’s distance surface. But the workhorse is distance_to. See the Example.

Install

install.packages('distanceto', repos = 'https://robitalec.r-universe.dev')

Example

library(distanceto)
library(sf)

## Linking to GEOS 3.11.2, GDAL 3.7.0, PROJ 9.2.0; sf_use_s2() is TRUE

# Load nc data
nc <- st_read(system.file("shape/nc.shp", package="sf"))

## Reading layer `nc' from data source 
##   `/home/alecr/R/x86_64-pc-linux-gnu-library/4.3/sf/shape/nc.shp' 
##   using driver `ESRI Shapefile'
## Simple feature collection with 100 features and 14 fields
## Geometry type: MULTIPOLYGON
## Dimension:     XY
## Bounding box:  xmin: -84.32385 ymin: 33.88199 xmax: -75.45698 ymax: 36.58965
## Geodetic CRS:  NAD27

# Set number of sampling points
npts <- 1e3

# Sample points in nc
ncpts <- st_sample(nc, npts)

# Select first 5 of nc
ncsub <- nc[1:5,]

# Measure distance from ncpts to first 5 of nc
dists <- distance_to(ncpts, ncsub, measure = 'geodesic')

head(dists, 30)

##  [1] 237543.35 217923.10  91920.82 225703.62  63642.69 141852.37 178301.66
##  [8]  88882.68  20298.52      0.00 100173.24 149001.91  68735.30  11992.49
## [15] 151591.39 162214.72  67969.38 227235.50  49860.75  42067.82  50899.94
## [22]  69211.60 111186.57  35096.09  95508.78 105467.67  31168.95 209061.13
## [29]  48339.16  25743.09

# Add to ncpts
ncpts$dist <- dists

Other approaches

• nngeo::st_nn
• gdal_proximity
• raster::distance
• GUI GIS applications