Geonames.org

There’s a dedicated R package to use geonames. First we need to create an account on geonames: https://www.geonames.org/login in order to get your own geonamesUsername. You will also need to enable the web service capacity: http://www.geonames.org/enablefreewebservice.

Install package

#install.packages("geonames")
library(geonames)
library(kableExtra)
##options(geonamesUsername="user")

Available functions in the package

###
### some sample usages

# GNsearch(q="london",maxRows=10)
# GNcities(north=44.1,south=-9.9,east=-22.4,west=55.2,lang="de")
# GNchildren(3175395)

# GNneighbours(3041565)
# GNneighbourhood(40.7834,-73.96625)
# GNfindNearbyPlaceName(52,-128,300, "30","FULL") 
# GNfindNearbyStreets(37.45,-122.18)

# GNcountryCode(lat=47.03,lng=10.2)
# GNcountryInfo()
# GNcountryInfo("DE")

## Wikipedia functions
# GNwikipediaSearch("london")
# GNfindNearbyWikipedia(postalcode=8775,country="CH",radius=10)
# GNwikipediaBoundingBox(north=44.1,south=-9.9,east=-22.4,west=55.2)

# GNtimezone(57.01,-2)
# GNtimezone(lat=0,lng=-40)
# GNtimezone(lat=0,lng=-40, radius=200)

# GNfindNearbyPostalCodes(lat=47,lng=9)
# GNpostalCodeSearch(postalcode=90210,country="FI")
# GNpostalCodeSearch(postalcode=90210,country="US")
# GNpostalCodeLookup(postalcode="LA1",country="UK")
# GNpostalCodeLookup(postalcode="90210")
# GNpostalCodeCountryInfo()

Practical example in DRC

Let’s use a dataset recently shared on the “GRP Inter Agency IM” skype group.

drc <- read.delim("drc.tsv")
str(drc)

## 'data.frame':    40 obs. of  5 variables:
##  $ Departement: Factor w/ 2 levels "cuvette","Likouala": 1 1 2 2 2 2 2 2 2 2 ...
##  $ District   : Factor w/ 8 levels "betou","Bouanela",..: 8 8 7 7 3 7 3 3 7 2 ...
##  $ VILLAGES   : Factor w/ 40 levels "","Afrique du sud",..: 37 36 40 39 38 35 34 33 32 31 ...
##  $ Lat        : Factor w/ 1 level "#N/A": 1 1 1 1 1 1 1 1 1 1 ...
##  $ Long       : Factor w/ 1 level "#N/A": 1 1 1 1 1 1 1 1 1 1 ...

We can search location one by one.

This would be the URL on geonames https://www.geonames.org/advanced-search.html?q=Ndoumba&country=CD&featureClass=P&continentCode=AF&fuzzy=0.6.

Beyond searching for the location name, you can note additional arguments to query the API:

• featureClass = “P”, - Here we are looking for populated place, you can narrow down this search by selecting one feature among the 645 different type available: https://www.geonames.org/export/codes.html

• fuzzy = “0.6”, - This enables the fuzzy search. By changing this variable, you will tune the sensitivity of the similar locations identification capacity.

• country = “CD”, continentCode = “AF” - This will narrow down your search to a country of continent.

More documentation on the webservice is available at https://www.geonames.org/export/web-services.html.

search1 <- GNsearch(q = "Ndoumba",
         featureClass = "P",
         fuzzy = "0.6",
         country = "CD",
         continentCode = "AF",
         maxRows = 20)



kable(search1)

In order to get quick results, we can also loop through the list of locations.

First we create an empty dataframe with the right structure.

results <- data.frame( adminCode1= "",
                       lng= "",
                       geonameId= "",
                       toponymName= "",
                       countryId= "",
                       fcl= "",
                       population= "",
                       countryCode= "",
                       name= "",
                       fclName= "",
                       adminCodes1.ISO3166_2= "",
                       countryName= "",
                       fcodeName= "", 
                       adminName1= "",
                       lat= "", 
                       fcode= "",
                       Village= "",
                       Departement= "",
                       District= "",
                       stringsAsFactors = FALSE)

names(results)

##  [1] "adminCode1"            "lng"                   "geonameId"            
##  [4] "toponymName"           "countryId"             "fcl"                  
##  [7] "population"            "countryCode"           "name"                 
## [10] "fclName"               "adminCodes1.ISO3166_2" "countryName"          
## [13] "fcodeName"             "adminName1"            "lat"                  
## [16] "fcode"                 "Village"               "Departement"          
## [19] "District"

Now we can loop around locations, to search and append results.

for (i in 1:nrow(drc)) {
  #i <- 1
  Village <- as.character(drc[ i, c("VILLAGES")])
  Departement <- as.character(drc[ i, c("Departement")])
  District <- as.character(drc[ i, c("District")])
  cat(paste0("searching for ", Village, "\n"))
  
  resulti <- GNsearch(q = Village ,
                      country = "CD",
                      featureClass = "P",
                      continentCode = "AF",
                      fuzzy = "0.6",
                      maxRows = 20)
  cat(paste0("Results potential ", nrow(resulti), "\n"))
  if (nrow(resulti) > 0 ) {
    resulti$Village  <- Village
    resulti$Departement  <- Departement
    resulti$District  <- District
  results <- rbind(results, resulti) } else { results <- results}
}

## searching for Obembo
## Results potential 0
## searching for Obambou
## Results potential 0
## searching for Yeleyele
## Results potential 4
## searching for Yabayeleyele
## Results potential 0
## searching for Talanamisso
## Results potential 0
## searching for Nongo
## Results potential 12
## searching for Nianga Kake
## Results potential 3
## searching for Ndzokou
## Results potential 0
## searching for Ndoumba
## Results potential 17
## searching for Moutembou
## Results potential 0
## searching for Moumenguele
## Results potential 0
## searching for Monokoboli
## Results potential 1
## searching for Mongombete
## Results potential 6
## searching for Moliangolo
## Results potential 0
## searching for Mogbala
## Results potential 20
## searching for Mobéyé (village autochtones)
## Results potential 0
## searching for Mawangui
## Results potential 20
## searching for Mankolo
## Results potential 20
## searching for Makolo
## Results potential 20
## searching for Loumbe
## Results potential 20
## searching for Lissala Ngomba
## Results potential 0
## searching for Ligoyi
## Results potential 8
## searching for Lignete
## Results potential 1
## searching for Kpeta
## Results potential 1
## searching for Itele
## Results potential 6
## searching for Ikongolo
## Results potential 10
## searching for Gaga
## Results potential 20
## searching for Etima
## Results potential 2
## searching for Epena centre (4 quartiers)
## Results potential 0
## searching for Elenda
## Results potential 19
## searching for Bossessengue
## Results potential 0
## searching for Bokpende
## Results potential 20
## searching for Bokoumba
## Results potential 20
## searching for Bogboko
## Results potential 20
## searching for Boboukou
## Results potential 2
## searching for Bissobe
## Results potential 1
## searching for Bete-Ntolo
## Results potential 1
## searching for Bangala
## Results potential 20
## searching for Afrique du sud
## Results potential 0
## searching for 
## Results potential 0

#names(resulti)

Last write resuts in csv file.

write.csv(results, "results.csv", row.names = FALSE)

et voila…