I would like to analyse the locations of electric vehicle charging stations for Germany, Italy and France. Those three countries, because they differ quite a lot in regard to their respective incentive programmes for public charging station infrastructure.
What I have so far are .csv exports from both OpenChargeMap and OpenStreetMap containing the location data (latitude and longitude) of all charging stations in those three countries along with a few other information that I can process in R.
What I would like to do now is some sort of reverse geocoding on those latitude and longitude coordinates to retrieve additional information on the surroundings. Especially, whether the respective charging station is located in a residential area in a city for example or at a rest stop on the highway. By knowing at what kind of locations the charging stations are placed in those three countries I am hoping to be able to draw conclusions regarding the incentive programmes. I'm not looking for specific addresses in this case, but rather an API or another way to process thousands of coordinates and retrieve information regarding for example population density or any other piece of data from which I could derive conclusions.
I have tried to get OpenStreetMap exports to work, but unfortunately I cannot seem to be able to query for the 'landuse' attribute through the Overpass Turbo API. This is my basic query that I'm using in this specific API, but as soon as I query for ["landuse" = "residential"] instead of ["landuse" = ""] I get prompted empty fields as result.
I found an API from Google which would offer lookup for various address components/types. Unfortunately, registering an API key at Google is not quite realistic for the scope of my work. Does somebody know of a (preferably FOSS) API that is able to do something like this? Or even how to make a 'landuse' query work in the Overpass Turbo API linked above?
Thank you in advance for your time.
Your Overpass API query is looking for elements that are tagged as amenity=charging_station and landuse. This is rather uncommon since charging stations and landuse are mapped as distinct objects. Instead you need to look around charging stations for landuse elements.
So instead of
area["ISO3166-1"="DE"]->.a;
nwr(area.a)["amenity"="charging_station"]["landuse"=""];
you will need a query like
area["ISO3166-1"="DE"]->.a;
nwr(area.a)["amenity"="charging_station"];
way(around:200)["landuse"];
This searches for ways with a landuse tag located within 200 meters of charging stations.
Note that this is a rather heavy query. You should probably use your own Overpass API server for it.