I am building an application that uses both GeoNames and Google Places API. The thing is, when I do a search nearby by a specific location (say lat: 47.16, lng: 27.56) on both of the services I do not know how to remove entities that appear both in the results from Google Places and the results from GeoNames(findNearby). I was thinking about using location (latitude and longitude) but it isn't accurate enough. Also, the name varies considerably so this wouldn't work either. Another idea that crossed my mind would be using the types (feature codes for GeoNames and type for Google Places), but there are a lot of types and obviously I can not do a cross reference manually. Any ideas?
Note: I want to use both of them as this is a school project and the requirements specify using more than one source of info.
Thanks.
I think that, unfortunately, the reason you haven't received an answer is that there is no answer that would fully satisfy the requirements.
Even with one provider, a single coordinate could be associated with multiple results. Imagine a large building in New York, for example, where dozens of companies each occupying a floor or part of a floor in the same building, and yet they would all be associated with the same (latitude, longitude) coordinate.
Now consider two sources. Source A says there's a doctor at that location (let's say on the 7th floor). Source B says there'S a doctor too. Can we assume they're the same doctor? Nope. It might be another doctor on another floor. Or it could be the same doctor. It's impossible to tell. The point is, you could try to use feature codes / types to reduce the number of hits by assuming similar locations are the same location, but it's still an assumption.
Anyway, good luck with your assignment from 3 years ago. It was a good idea nonetheless. :)
Related
I'm new to geocoding so I'm not certain this is even the question I should be asking, but all of the other discussions I've seen on this topic (here and on the Google API forum) are so application specific that I feel like I might be missing a very elementary step - I don't need to know how to implement a store finder - I need to know if I should.
Here is my specific situation - I have been contracted to design an application wherein we will build a database of shops (say, independently owned bars and pubs). This list will continually grow and change as shops close and new ones open. The user can enter his/her point of origin (zip code or address) and be shown a list or map containing all the various shops within a given radius in order of proximity.
I know how to deliver these results from a static database:
One would store the longitude and latitude as columns for each row and then just use that information to check distances.
But I have inherited an (already fairly large) database of shops which have addresses but not coordinates - so I'm not sure what the best way to get those addresses is. I could write a script to query them one at a time against google geocoding, I could have a data entry person manually look up the coordinates for each one and populate the data that way, or maybe there is a third option I'm not aware of.
Is this the right place to be asking this question? Google Maps Geocoding doesn't host a forum of their own, but refers people to Stack Overflow. Other forums on the net dealing with this topic are all relating to a specific technical question but no one seems to be talking about it from a top-down perspective (ie the big picture).
Google imposes a 2,500 queries per day limit on free users and a 100,000 queries a day limit on paid ones - neither of these seem to be up to the task of a site with even moderate traffic if, every time a user makes a request, the entire database (perhaps thousands of shops) are being checked against Google's data. It seems certain we must store the coords locally but even storing them locally, there will have to be checks against Google in order to plot them on a map. If I had a finite number of locations (if, for example, I had six hardware shops) and I wanted to make a store locator, there would be a wealth of discussions, tutorials, and stack overflow questions available to point the way for me, but I'm dealing with a potentially vast number of records and not sure how to proceed or where to begin.
Any advice would be welcome - Additionally, if this is not the best place to be asking this question, a helpful response would be to indicate a better place to post it. I've searched for three days but haven't found what looks like a good resource for asking such subjective questions.
The best way of course would be when you use a geocoding-service to get coordinates and store the coordinates in your DB. But it's not possible with google's geocoding-service, because it's not permitted to store geocoded data permanent.
There are free services without this restriction, some keywords to search for: mapquest, nominatim, geonames(but these services are less accurate than google)
Another option would be to use a FusionTable. The geocoding would run automatically(but the daily limits are the same as for the geocoding-service). The benefit: the geocoding is permanent(you can't access the locations directly by e.g. downloading the DB-dump), but you may use the coordinates for plotting markers(via a FusionTablesLayer) or filtering(e.g. by distance)
The number of entries shouldn't be an issue, 100k is no problem for a database
When geocoding human readable address into lat lng e.g. 3 mystreetname, myarea, mycity, mypostcode.
Should I use full address or just some part of it, for instance post code?
I know that it works ether way, but I'd like to know what would be the best practice to avoid errors geocoding locations.
Some cities span multiple postal codes, and some postal codes span multiple cities. You might not have problems with smaller data sets but as you start dealing with a lot of addresses things like that can pop up. It's entirely possible that there are two 201 Main Streets in the same zip code, located in two different cities.
So yep, give as much detail as you can.
I'd really recommend storing your information in a spatial datatype if your database supports that as well.
This link is the google's documentation of geocoding
https://developers.google.com/maps/documentation/geocoding/?csw=1
And refer below link for the real time sample..!
http://gmaps-samples.googlecode.com/svn/trunk/geocoder/singlegeocode.html
And for better results use more information so that you will get accurate answers
Hope it helps
I would try running the queries with as much detail as possible, and if a query fails rerun without the zip, as sometimes the zip causes problems with the google api (especially zips greater then 5 digits).
I want a list of locations (coordinates) for all possible colonies/neighborhoods of some Indian cities. Take for example Delhi. Can this data be obtained with the Places API?
The only thing that comes to my mind is to use a query like -
https://maps.googleapis.com/maps/api/place/search/xml?location=28.540346,77.210026&radius=500&types=administrative_area_level_1|administrative_area_level_2|administrative_area_level_3|locality|neighborhood|street_address|sublocality|sublocality_level_4|sublocality_level_5|sublocality_level_3|sublocality_level_2|sublocality_level_1|subpremise&sensor=false&key=MYKEY
and then keep changing the radius by 500 till the whole city is covered.
Is there a better way of doing this?
Given how often you would need to do this for your map, since caching that data goes against the terms of service, this is not a great approach. If you map gets any decent usage, you'll rapidly hit your quota. Plus you're only get center points of the colonies/neighborhoods. I'd recommend trying to find another source of that data you can download. The Places API was not designed with this in mind.
Is there a way using the Google Maps API to get back an "optimized" route given a set of waypoints (in other words, a "good-enough" solution to the traveling salesman problem), or does it always return the route with the points in the specified order?
There is an option in Google Maps API DirectionsRequest called optimizeWaypoints, which should do what you want. This can only handle up to 8 waypoints, though.
Alternatively, there is an open source (MIT license) library that you can use with the Google Maps API to get an optimal (up to 15 locations) or pretty close to optimal (up to 100 locations) route.
See http://code.google.com/p/google-maps-tsp-solver/
You can see the library in action at www.optimap.net
It always gives them in order.
So I think you'd have to find the distance (or time) between each pair of points, one at a time, then solve the traveling salesman problem yourself. Maybe you could convince Google Maps to add that feature though. I guess what constitutes a "good enough" solution depends on what you're doing and how fast it needs to be.
Google has a ready solution for Travel Salesman Problem. It is OR-Tools (Google's Operations Research tools) that you can find here: https://developers.google.com/optimization/routing/tsp
What you need to do basically is 2 things:
Get the distances between each two points using Google Maps API: https://developers.google.com/maps/documentation/distance-matrix/start
Then you will feed the distances in an array to the OR-Tools and it will find a very-good solution for you (For certain instances with millions of nodes, solutions have been found guaranteed to be within 1% of an optimal tour).
You can also note that:
In addition to finding solutions to the classical Traveling Salesman
Problem, OR-Tools also provides methods for more general types of
TSPs, including the following:
Asymmetric cost problems — The traditional TSP is symmetric: the distance from point A to point B equals the distance from point B to
point A. However, the cost of shipping items from point A to point B
might not equal the cost of shipping them from point B to point A.
OR-Tools can also handle problems that have asymmetric costs.
Prize-collecting TSPs, where benefits accrue from visiting nodes
TSP with time windows
Additional links:
OR-tools at Github: https://github.com/google/or-tools
Get Started: https://developers.google.com/optimization/introduction/get_started
In a typical TSP problem, the assumption is one can travel directly between any two points. For surface roads, this is never the case. When Google calculates a route between two points, it does a heuristic spanning tree optimization, and usually comes up with a fairly close to optimal path.
To calculate a TSP route, one would first have to ask Google to calculate the pair-wise distance between every node in the graph. I think this requires n*(n-1) / 2 calcs. One could then take those distances and perform a TSP optimization on them.
OpenStreetMaps.org has a Java WebStart application which may do what you want. Of course the calculations are being run client side. The project is open source, and may be worth a look.
Are you trying to find an optimal straight line path between locations, or the optimal driving route? If you just want to order the points, if you can get the GPS coordinates, it becomes a very easy problem.
Just found http://gebweb.net/optimap/ It looks nice and easy. Online version using google maps.
If I had lat/long data for all our leads in Salesforce, is there a way to write a query to group them, or say list all the leads within 10 miles of San Francisco, CA ?
[EDIT: Clarification]
I have thousands of leads with both a full address, and long/lats.
I want to build a query on these leads that will give me all of the leads near San Francisco, CA. This means doing GIS type work within salesforce.
I could of course filter specifically on city, or zipcodes or area code, but this presents some problems when trying to rollup a whole metro area.
Yes. You need to Reverse GeoCode them with a tool/service. In the past I have used Maporamas service but it was quite expensive and that was before Google maps and virtual earth existed so I am sure there is something cheaper(free) out there now.... Googling around I have found this and this
EDIT:
OK from What I understand you are trying to calculate the distance between 2 lat/long points. I would start by discounting the ones that where outside you sphere of (lets say) 10 miles. So from your central point you will want to get the the coordinates 10 miles, East, West, South and North. To do this you need to use the Great-circle distance formula.
From that point you have you Sales Force Data if you wish to break this data up further then you need to order the points by distance from the central point. To do this you need to use the Haversine formula
I am not sure what you language preference is so I just included some examples from SQL(mainly) and C#
Haversine Formula in C# and in SQL
Determine the distance between ZIP codes using C#
Great Circle SQL
Great Circle 2
Use GeoHash.org (either as a web service or implement the algorithm). It hashes your lat-long coords into a form that appears similar for nearby places. For example A may have a hash like "akusDf3af" and B might have a hash like "akusDf3b2" if they are nearby. Then do a SOQL query that looks for places starting with the same n characters as a known location. Your n will determine the radius of the lookup.
These are some great technical solutions that can provide very exact answers, but two things to consider:
geospatial proximity does not map neatly to responsibility
Ownership calculation seems to be done best through postal code lookups or other rules that don't allow for gaps or overlaps. Otherwise, you'll have two (or more) salespeople fighting over leads that are close to both of them, and ignore those leads that are far away from both of them.
So, if you're using geo-calculations like those above to assign ownership, just acknowledge the system will leak and create business rules to accomodate for that. But a simple postal lookup to define territories (as salesforce's own territory management feature does) might be better.
I'd suggest the problem we're trying to solve geospatially is not who owns which lead. Rather, given all the leads you own, which are nearby?
maps often offer more data per pixel than columnar reports
Again, geospatial data in a report may not be the best answer. A lead 50km away, but along a major road, is more interesting than another lead 50km away on the other side of a mountain or lake. Or a lead close to other leads is more interesting than a lead by itself.
A report can't show this, but a map can.
Salesforce has some great examples of Google Maps integrations. Instead of a columnar report called "My Nearby Leads", why not a visualforce page, with a google map inside? You're giving the user far more information than a columnar report could. They might like it better, and it's easier to implement than trying to calculate some of the equations above.
Just another perspective that may (or may not) be appropriate to the problem at hand.
This post is really old, but is showing up at the top of Google results, so I figured I would post some info to it anyways.
2 nice mapping tools are batchgeo.com and geocod.io. Geocod.io can even give you lat and long coordinates from an address.
If you just need a one time calculation, you can use Excel. Export all your leads with the lat and long. Then go to Google Maps and get the lat and long in decimal degrees for the city center of wherever you want to measure to.
Then use this formula in excel to calculate the distance between the coordinates in miles. Lat1dd and Long1dd are the coordinates for one point, and the lat2dd and long2dd are coordinate points for the other point.
=3963*ACOS(COS(RADIANS(90-lat1dd))*COS(RADIANS(90-lat2dd))+SIN(RADIANS(90-lat1dd))*SIN(RADIANS(90-lat2dd))*COS(RADIANS(long1dd-long2dd)))
After you run it, just sort the results from smallest to largest to get those results that are the closest.
I haven't done this next part yet, but conceptually it should work. We have a field that lists the major market each account is in. Example, Chicago IL. I am going to build a trigger or formula field that essentially says IF(Market="Chicago IL") then use X and Y for the lat and long. These will be hardcoded as the city center for that specific market. The query will then run each individual account's lat and long against the one from the city center to calculate a distance.
If you wanted to break the market into different zones, you could adjust your formula so it uses < and > on the lat and long fields. Everything less than X but greater than Y goes in Zone A, etc.
Hope this helps someone.