I would like to calculate the number of unique kilometers of roadways in my city. More generally, I wish to sum the distance of every road within a bound, for simplicity a rectangle will do.
Is this possible using the Google Maps suite of APIs? If so, how would you go about doing it? If anyone has any resources related to this type of problem, I would be interested in reading them regardless of language (or even solutions with other mapping tools).
Bonus points: A general solution to this problem that can be applied to the pre set "cities" (example) that appear in Google Maps with well defined city limits.
You can use OpenStreetMap to calculate the total road length of a specific country or geographic area. There are multiple solutions available, based on multiple similar questions already asked.
Approach 1 from Total road length in Kilometers for a country at help.openstreetmap.org:
Use the Perl script osm-length-2.pl. There is an example at a mailing list post.
Approach 2 from Actual road length of exported map at help.openstreetmap.org:
Import your data (the planet or an country or area extract) into a PostGIS database, then use the following queries proposed by Frederik Ramm:
SELECT way AS clip
INTO clipping_polygon
FROM planet_osm_polygon
WHERE boundary='administrative' AND admin_level='8' and name='My City';
SELECT name, highway, ST_INTERSECTION(way, clip)
INTO clipped_roads
FROM planet_osm_line, clipping_polygon
WHERE ST_INTERSECTS(way, clip) AND highway IS NOT NULL;
SELECT highway, SUM(ST_LENGTH(way::geography))
FROM clipped_roads
GROUP BY highway;
Related
I have a google maps application where users can search by Country, State, City or a street address. Users may be anywhere in the world and they may be searching for anywhere else in the world, not just within their own country.
I need the geocoder to have a bias such that if a state is entered (without the country) it geocodes to the state and not to a city with the same name. Our application prioritises countries first, then states, then cities etc... however the geocoder is not doing the same.
Eg. I want to search for "Victoria" which is a state within Australia.
http://maps.googleapis.com/maps/api/geocode/json?address=victoria shows Victoria, BC, Canada.
http://maps.googleapis.com/maps/api/geocode/json?address=victoria®ion=au shows the state of Victoria in Australia however I cannot include the region as my users may be anywhere in the world so I have no way of knowing which region they are searching for.
I have looked at "administrative levels" and also "types" but I cannot find a solution which suits my needs of simply prioritising in the order country > state > city.
I ideally want something like this:
maps.googleapis.com/maps/api/geocode/json?address=victoria&components=administrative_area:WILDCARD
OR
maps.googleapis.com/maps/api/geocode/json?address=victoria&types=administrative_area_level_1
Of course neither of these solutions work but I hope they illustrate what I am trying to achieve.
Any suggestions?
Thanks,
Nicole
You can do a query without specifying the address, use
...?components=administrative_area:victoria
and then iterate over the results.address_components to pick out ones where the types include administrative_area_level_1
Update: I noticed that depending on the search term provided to administrative_area, google is using some kind of heuristics to determine the certainty of the results. If there's a clear winner, then only 1 result is shown. If the matching is similar for a group of locations, then you will get several. So when there's several results, you can pick towards a higher or lower administrative_area_level to suit your needs.
Our website lets people create listings and these include a location field, which is populate by Google's API, just like on Airbnb, for example. You start typing any part of your address and then you select from the Google's suggestions of matching places.
People can search the listings by location (same Google API populated location field, and you can choose what distance from that location), and this seems to work fine in principle.
The issue is that the search doesn't seem to work for areas, e.g. counties. It seems to take a point within the region and measures from that. So, if I search for listings in "United Kingdom" I get hardly any results 'Within 10 miles' but I get a lot 'Within 250 miles'.
Instead, I want to get all results within the UK if I search for United Kingdom (or a UK county, or within a large city like London).
Why doesn't it work right now, and how can this be done?
To restrict the Autocomplete Box (I guess this is the component you're using) to a country, you can use componentRestrictions as described here (scroll to Restrict the search to a specific country )
If you need to restrict your search in a specific area, such as "10 miles around a defined point", it's a little more complicated. According to the doc, you'll have to
Set the bounds on creation of the Autocomplete object.
Change the bounds on an existing Autocomplete.
Set the bounds to the map's viewport.
Restrict the search to a specific country.
You can find an exemple here on paragraph Set the bounds on creation of the Autocomplete object
I'll find a route between two places, for example using google maps. I'd like to divide the route to kilometers (two following places will be at a distance of 1 km), and get GPS coordinations of these places. This is because then I'll be able to get exacly the coordinations of, for example, 5th kilometer on the route. Could you please advice me how to achieve it?
This is extremely nontrivial. Is say your best bet is to find an algorithm to load the bearing between two points, then one to load a coordinate given a start point, distance, and bearing. This could give you it, but only if the data contained only straight lines. Since I assume the Google Maps API only gives you the turns the user has to make, this approach will be inaccurate when there are bends in roads. You'd need GIS data for roads and what will undoubtedly turn into a complicated algorithm to find something like this. It's definitely doable, but that's l how I'd start. Look into the Census TIGER road data, it should help.
Unless, of course, I'm wrong and the API does actually give enough points to cleanly map it, in which case those functions should be easy to find and implement.
This will only work if you have the polyline as a sequence of lat/lon (or other) coordinates, wherever you get that from.
Then you start at the beginning an iterate through the lines (point[i], point[i+1]).
THis distance you calculate with standard API.
while itersting you sum up the distance.
Once you exceed the 1000m, you know that the splitting point (the 1000m marker) is at line segment [i,i+1].
To calculate the exact position where on the line that is, you take the total summed meters from previous segment, and the value of this segment and do a linear interpolation.
The working code is a bit complexer: there can be multiple markes within one segement.
But first find out where you get the polyline from, whitou that it will not work.
I would like to find all points that are within N miles of a given area.
E.g. the area is California: Find all points that are within 50 miles of the border of California (not the middle of California).
When using Google Maps the distance is calculated using 'the middle' of the given location, but I need to calculate the distance using the borders of the given location. The location could be any zip code, city or country.
Could that be done by drawing a polygon using California's coordinates on a map and calculate the distance to location B using the points of the polygon?
Is there a more elegant solution to this? Any ideas?
Thanks!
I'm not sure if I understand your requirements completely, but I will give it a try with different interpretations:
1. You want to filter own map points:
This can be done with any GIS or a own service that offers a call like my_points_in_area(bbox). Bbox means here boundingbox and is the 2x lat/lon pair describing the rectangle around your given centerpoint. If you want to be accurate and really just deliver whats within 100km, you might need to test the distance to the POIs once more, as the rectangle will also include points that are a bit more far away.
2. You want to filter OSM data:
You might use a reverse-geocoding service as Nominatim to get informations about points of interests that are within this distance: http://wiki.openstreetmap.org/wiki/Nominatim
Otherwise import the OSM data using osmosis to a PostGIS DB. AFAIK there is (currently) no DB tool for Oracle: http://wiki.openstreetmap.org/wiki/Oracle
I'm sorry if I missed your question, but then please add more details :)
I'm using http://maps.google.com/maps/geo? web service to geocode some addresses.
The problem I have is that a fuller address doesn't necessarily give a more accurate geocode.
e.g passing in Llantysilio, Denbighshire, UK is far more accurate than Llantysilio, Llangollen, Denbighshire, UK
The Accuracy attribute in the XML doesn't seem very helpful in deciding which address to pick.
How have other people dealt with this issue? Is there a good way to pick the best geocode that works most/all of the time?
*edit
A bit of extra info - when I put in the fuller address the first line of the address is ignored and the geocoder jumps to a different, but exact, address which is a central street located in the extra line added to the address. In this example, it picks Castle Street in the middle llangollen, seemingly disregarding Llantysilio.
Edit by kdgregory: here are the two API requests that I used (missing API key doesn't seem to be an issue):
http://maps.google.com/maps/geo?q=Llantysilio,+Denbighshire,+UK&sensor=false&output=xml
http://maps.google.com/maps/geo?q=Llantysilio,Llangollen,++Denbighshire,+UK&sensor=false&output=xml
You have to interpret the accuracy my friend. There are usually 2 parts to an accuracy, first the address macthing. The second part is the important part. You can geocode something to a accuracy level of the United States, or a city level, zipcode centroid, street interpolated level or an actual parcel precision level. The first example has a 4 and the second is 9. For this service higher is better.
Accuracy Value Description
0 Unknown accuracy.
1 Country level accuracy.
2 Region (state, province, prefecture, etc.) level accuracy.
3 Sub-region (county, municipality, etc.) level accuracy.
4 Town (city, village) level accuracy.
5 Post code (zip code) level accuracy.
6 Street level accuracy.
7 Intersection level accuracy.
8 Address level accuracy.
9 Premise (building name, property name, shopping center, etc.) level accuracy.
It's probably good to note that Google does not follow the XAL specs, but rather implements them in a subset.
So, this means that you won't necessarily be able to do:
place.AddressDetails.Country.AdministrativeArea.Locality.LocalityName
place.AddressDetails.Country.AdministrativeArea.AdministrativeAreaName
place.AddressDetails.Country.CountryName
Because a country and sub-locality may be provided while a administrative area is not.
The data that is returned is identified with an accuracy gauge that gives you a relative idea of what you can expect for data. So, you can store objects and chop off parts of the full address using this variable and try to geocode in such a fashion - It's not recommended though.
Typically, a full address is (without the thoroughfare) is a good way of finding the general location. You can use some of the weighted-preferential logic Google provides to refine the address.
E.g. Use the setViewPort or setCountryCode to give your searches a bit more accuracy.
Remember, Geocoding is not a science. You can't expect consistent results.
A geocode response.Placemark[0] via gmap you can check what you got, and take the level or try again. I chose default in the order
place.AddressDetails.Country.AdministrativeArea.Locality.LocalityName
place.AddressDetails.Country.AdministrativeArea.AdministrativeAreaName
place.AddressDetails.Country.CountryName
It could be more logically named as seen above. gmaps 3 works somewhat incompatible with v2.
You can try a very ugly hack which consists in geocoding your full adresse and all subsets of the words your adress contains, you get a lot of geocodes that you use to get the adresses related to them with reverse geocoding tool.
Once you have plenty of adresses you compare them with the one you first gave, then you take the most accurate geocode...
Many requests, lot of iteration growing with each word you add to your adress, well an ugly work but can be fun to make some statistics ^^
In the end I concluded that there are far too many weird blips in address consistency with google's geocoding webservice in the UK, but eventually managed to figure out a way of using postcodes instead, which is far more accurate: how it's done