I have a list of a couple of hundred latitude-longitude coordinate pairs for different locations. My goal is to obtain an estimate of the driving duration from a 'home' location to each of the coordinate pairs, using R.
I have had some success using the googleway package in R, but have (predictably) run into problems for locations which are far from a road, e.g. if the coordinates are for a mountain top. In these instances I would like to estimate instead the driving times to the nearest road to each problematic coordinate pair.
To illustrate, let's say my home location is;
home <- "Edinburgh, UK"
...and an example dataframe of locations I want to find driving times to could be;
location <- c("place_a", "place_b", "place_c")
latitude <- c("56.87034", "57.69380", "57.36243")
longitude <- c("-4.199001", "-5.128715", "-5.104728")
df <- data.frame(location, latitude, longitude)
I can obtain distance/duration, etc., between home and place_a, and between home and place_b using something like;
(NB. You'll need your own Google Maps api key to replicate this section... )
library(googleway)
api_key <- [insert your Google Maps api key here!]
results <- google_distance(origins = home,
destinations = list(c("56.87034,-4.199001"),
("57.69380,-5.128715")),
mode = "driving",
key = api_key,
units = "imperial")
I get all the data I want using:
results$rows[[1]]
We run into trouble however when trying the same for the coordinates for place_c, which returns ZERO_RESULTS;
results2 <- google_distance(origins = home,
destinations = ("57.36243,-5.104728"),
mode = "driving",
key = api_key,
units = "imperial")
Here I think the issue is that the coordinates are for half-way up a mountain, so in this case I want to find the nearest road to the coordinates instead. I'd hoped to have some luck with the nearest_road function of googleway but cannot seem to get it working, e.g something like this doesn't work;
df_points <- read.table(text = "lat lon
57.36243 -5.104728", header = T)
nearest_road <- google_nearestRoads(df_points, key = api_key)
Can anyone advise what the problem is here? Or suggest a better solution altogether?!
Many thanks.
I am working on this very problem in a package that will be available on github soon (called spaceheater). In the meantime:
I would download the Open Street Maps shapefile from geofabrik for the country you are working with. For example Nigeria: http://download.geofabrik.de/africa/nigeria.html
EDITED WITH THE SUGGESTIONS OF monkeytennis(thanks!):
library(sp)
library(rgdal)
library(raster)
library(googleway)
library(geosphere)
library(foreach)
###I did Nigeria because I have it in my file downloaded, you would use UK###
roadshp <- readOGR(dsn="nigeria-latest-free.shp",
layer="gis.osm_roads_free_1")
#Isolate primary roads (or secondary and tertiary) if you wish#
roads <- roadshp[roadshp$fclass %in% c("primary", "secondary", "tertiary"),]
#Use SpatialPoints for your gps coords
location <- c("place_a", "place_b", "place_c")
latitude <- c(8.641, 10.892, 11.797)
longitude <- c(6.0046, 11.146, 5.477)
df <- data.frame(location, latitude, longitude)
coordinates(df)=~longitude+latitude
sp1 <- SpatialPoints(df)
proj4string(sp1)=CRS("+proj=longlat +datum=WGS84 +no_defs +ellps=WGS84
+towgs84=0,0,0")
clodist <- dist2Line(sp1, roads)
df <- as.data.frame(df)
df$clodist <- clodist[,c("distance")]
df$lat <- clodist[,c("lat")]
df$lon <- clodist[,c("lon")]
iters <- nrow(df)
origin <- as.character("9.056, 7.497")
gc1 <- data.frame(round(df[,c("lat")],3), round(df[,c("lon")],3))
colnames(gc1) <- c("lat","lon")
df$lat <- as.character(gc1$lat)
df$lon <- as.character(gc1$lon)
gt2 <- paste(df[,c("lat")], df[,c("lon")], sep=",")
results <- google_distance(origins =origin, destinations= gt2,
mode="driving",
key="Your API Key Here")
results <-unlist(results)
results <- as.data.frame(results)
ttt <- head(results,-1)
ttt <- ttt[-c(iters+1), ]
m1 <- matrix(ttt, ncol=iters, byrow=TRUE)
distance <- as.data.frame(m1)
rownames(distance) <- c("Address", "DistanceKM",
"DistanceM","TimeTextLow","TimeSecondsLow","TimeTextHigh","TimeSecondsHigh",
"Status")