Make a vector of coordinates to filter data within a certain area

Question

Rookie R user here and I would greatly appreciate any help you someone could give me.

My project requires me to create a vector boundary box around a city of my choice and then filter a lot of data so I only have the data relative to the area. However, it is several years since I have used R studio and its fair to say I remember little to nothing about the language.

I have initially used

geocode("Hereford, UK")

bbox <-c(Longitude=-2.72,Latitude=52.1)

myMap <- get_map(location = "Hereford, UK",source="google",maptype="roadmap")

I then must create a new tibble which filters out and gives only the relevant data to the area.

I am unsure how to proceed with this and I then must overlay the data onto the map which I have created.

As I only have a centre point of coordinates, is it possible to create a circle with a radius of say 3 miles around the centre of my location so I can then filter this area?

Thank you all for taking the time to read my post. Cheers!

Answer 1

Most spatial work can now be done pretty easily using the sf package.

Example code for a similar problem is below. The comments explain most of what it does.

The difficult part may be in understanding map projections (the crs). Some use units(meters, feet, etc) and others use latitude / longitude. Which one you choose depends on what area of the globe you're working with and what you're trying to accomplish. Most web mapping uses crs 4326, but that does not include an easily usable distance measurement.

The map below shows points outside ~3 miles from Hereford as red, and those inside in dark maroon. The blue point is used as the center for Hereford & the buffer zone.

library(tidyverse)
library(sf)
#> Linking to GEOS 3.6.2, GDAL 2.2.3, PROJ 4.9.3
library(mapview)

set.seed(4)
#hereford approx location, ggmap requires api key
hereford <- data.frame(place = 'hereford', lat = -2.7160, lon = 52.0564) %>% 
  st_as_sf(coords = c('lat', 'lon')) %>% st_set_crs(4326)

#simulation of data points near-ish hereford
random_points <- data.frame(point_num = 1:20, 
                            lat = runif(20, min = -2.8, max = -2.6),
                            lon = runif(20, min = 52, max = 52.1)) %>%
  st_as_sf(coords = c('lat', 'lon')) %>% st_set_crs(4326) %>%st_transform(27700)

#make a buffer of ~3miles (4800m) around hereford
h_buffer <- hereford %>% st_transform(27700) %>% #change crs to one measured in meters
  st_buffer(4800)


#only points inside ~3mi buffer
points_within <- random_points[st_within( random_points, h_buffer, sparse = F), ]

head(points_within)
#> Simple feature collection with 6 features and 1 field
#> geometry type:  POINT
#> dimension:      XY
#> bbox:           xmin: 346243.2 ymin: 239070.3 xmax: 355169.8 ymax: 243011.4
#> CRS:            EPSG:27700
#>    point_num                  geometry
#> 1          1 POINT (353293.1 241673.9)
#> 3          3   POINT (349265.8 239397)
#> 4          4 POINT (349039.5 239217.7)
#> 6          6 POINT (348846.1 243011.4)
#> 7          7 POINT (355169.8 239070.3)
#> 10        10 POINT (346243.2 239690.3)

#shown in mapview
mapview(hereford, color = 'blue') + 
  mapview(random_points, color = 'red', legend = F, col.regions = 'red') + 
  mapview(h_buffer, legend = F) + 
  mapview(points_within, color = 'black', legend = F, col.regions = 'black')

^{Created on 2020-04-12 by the reprex package (v0.3.0)}