teelou teelou - 1 month ago 35
JSON Question

R + Weather Underground - how to use longitude and latitude to get the closest airport station?

How can I find the nearest Airport station by using longitude and latitude?

For instance I have this json data store in my db,

"location" : {
"long" : "Devon, 8 Market Road, Plympton, Plymouth PL7 1QW, United Kingdom",
"street_number" : "",
"route" : "Market Road",
"locality" : "Plymouth",
"administrative_area_level_1" : "England",
"country" : "United Kingdom",
"postal_code" : "PL7 1QW",
"lat" : "50.38693379999999",
"lng" : "-4.0598999999999705"
}


And I know that my locality is
Plymouth
, so I will request the stations data from the Weather Underground via this URL below:

http://api.wunderground.com/api/[MY-API-CODE]/geolookup/conditions/q/UK/Plymouth.json

Here is how I do it:

locality <- 'Plymouth'

pullUrl <- paste(apiUrl, 'geolookup/conditions/q/UK/', locality, '.json', sep='')

# Reading in as raw lines from the web service.
conn <- url(pullUrl)
rawData <- readLines(conn, n=-1L, ok=TRUE)

# Convert to a JSON.
geoData <- fromJSON(paste(rawData, collapse=""))

# Get the station data in location only.
# Turn the result into a data frame.
stationsDF <- as.data.frame(geoData$location$nearby_weather_stations$airport$station)


So I get 3 stations below:

city state country icao lat lon
1 Plymouth United Kingdom EGDB 50.35491562 -4.12105608
2 Exeter UK EGTE 50.73714066 -3.40577006
3 Culdrose UK EGDR 50.08427429 -5.25711393


But my problem is how can I ensure that I will get
EGDB
instead of
EGTE
or
EGDR
- because Plympton is closer to Plymouth?

So can I use the lat and lng below in my db to determine which station is the closest?

"lat" : "50.38693379999999",
"lng" : "-4.0598999999999705"


So how can I know the lat and lng above should go for
EGDB 50.35491562 -4.12105608
?

Any ideas?

Answer

If you've got the data already, say

df <- read.table(text = 'city state        country icao         lat         lon
                   1 Plymouth     "United Kingdom" EGDB 50.35491562 -4.12105608
                   2   Exeter                   UK EGTE 50.73714066 -3.40577006
                   3 Culdrose                   UK EGDR 50.08427429 -5.25711393', head = T)

loc <- c(lat = "50.38693379999999", lng = "-4.0598999999999705")

Then you can use geosphere::distHaversine to calculate the distances (in meters, by default) betweeen loc and each observation of df:

dists <- geosphere::distHaversine(as.numeric(loc[c('lng', 'lat')]), df[, c('lon', 'lat')])

dists
## [1]  5617.667 60493.398 91661.079

With which.min, you can index df to give you a result:

df[which.min(dists), ]
##   city    state        country icao      lat       lon
## 1    1 Plymouth United Kingdom EGDB 50.35492 -4.121056
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