I am working on google map images based location classification problem here in a capital city, I want to get access to the images dataset, of any capital city so that i can do the classification on that basis, so how will i get such a dataset.i am willing to access the dataset.
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I am currently working on a school project. The objective is to find a route through Europe from trainstation to trainstation, from country to country where the names of the consecutive trainstations have to start with the letters of the alphabet consecutively and a country can only be used once. To give an example route:(Amsterdam Central, Netherlands) --> (Berlin, Germany) --> (Carcasonne, France) etc. Countries also need to be neighbouring countries. We have received a dataset in which countries and some of their specific stations are mentioned. Some of the countries don't have a large selection of stations, making it important that a certain letter is used with a certain country, because only a small selection first letters will be present for this specific country. Can someone maybe provide me with some guidance as to how I can tackle this problem. I am currently coding in python.
cheers!
- Sort countries in order of increasing number of letter choices
- Loop C over countries in order of increasing number of letter choices
- Place C in position for a random letter that it provides
- IF neighbouring positions have been populated, but they are NOT neighbours geographically
- THEN choose a different letter for those available in C
I would use a constraint solver for this. (I'm familiar with CP-SAT because I use it at work, but you have options.)
For each letter from A to Z, create a variable whose domain is the set of stations whose name starts with that letter. Create 26 corresponding country variables and, for each corresponding station variable and country variable, add a table constraint to ensure that they describe the same thing (so the table contains entries like ("Amsterdam Central, Netherlands", "Netherlands"), though you have to translate into integer indices). Add an all-different constraint on the country variables. For each pair of consecutive country variables, add a table constraint that they be neighbors.
The solver contains a powerful deduction engine that will surely pick through the possibilities much faster than brute force or simple heuristics.
I'm trying to build a geoloc service (from France only) with Elastic Search. I have several indexes to create such as country, region, county, city, neighbour containing itself a polygon.
For each city, I have a list of the nearest cities to include.
How should I design this kind of data, I would like to be able to:
search by coordinates
search by full text
search by zip code, city name, neighbour name
manage faceting (n cities in n county in n region for instance)
etc...
I don't know if I have to use the path Hierarchy Tokenizer pattern.
I was trying to build a unique index Neighbours by referencing the data from the bottom to the top(neighbour => city => county => region => country). But I don't know if it's a good idea regarding the volume of data. (1 country, 40 regions (old + new ones), 101 counties, 36000 cities and 7700 neighbours), especially the polygones.
Any idea?
Thanks in advance!!
I need to get drive times for a place to the nearest airports. There is a service which is already in place which gives me the address of the place as well as the address of nearest airports in the north america region. One airport has a 5 digit zipcode, one has the zipcode this format 83402 4906, other has a zipcode in this format(canada) A12 123
The distance matrix api is not accepting all other zipcode formats apart from the 5 digit one. If I remove the space its not working.
I need to get the drive times irrespective of the zipcode format
I have a set of 900 Latitude and Longitude Coordinates-- I need a relatively simple method for finding the 'State' referred to by these coordinates. If it helps, the data is in excel.
Google provide a Geocoding service. Part of this is reverse geocoding which converts geographic coordinates into a human-readable address including States. This Demo illustrates what can be done. There are limits to what you can do with this service.
Try to use the average values as provided here. With a bit of luck, most of your 900 coordinate pairs belong to the state with the nearest center. Calculation of distances between longitude/latitude locations is explained here.
An alternative would be to use a ZIP table with US postcodes as provided here. Once you know the postcode, you know the state, don't you? I'm not sure, but each state has an interval of ZIP codes. Once you know the ZIP code of a location, you can find the interval and the state it belongs to.
A list of coordinates of US locations could help to get a more exact allocation: http://www.bcca.org/bahaivision/fast/latlong_us.html
Find the nearest location in the list and take its state as result.
Google requires that geocoding / reverse geocoding be used with maps that users can see, so if that isn't an option for you, I think the best way is to use a database with spatial functions. First, you'll need the state boundaries found for free at NationalAtlas.gov. I use SQL Server (need 2008 or 2012 versions) and you can use the STContains() method to find what state it belongs to.
A simpler solution would be to just use the ezcmd.com rest API services.
They provide two APIs:
http://ezcmd.com/apps/app_geo_postal_codes#geo_postal_codes_api
1) All you have to do is just give it a zip code and a country code (for usa you either use US or USA) and optionally you'll pass the distance radius, and units (Miles or Km) and it'll return all other zip codes with state and province that are within the given distance
2) Free search, where you give it any fuzzy search phrase that includes either one of zip / city / state / province and country and it returns the best matches for that search phrase.
Hint: You can use #2 to find the zip code for a fuzzy (human readable) address and pass that zip code to #1 to find nearest places to that zip code.
Also they have another API that returns zip code along with full geo location information for a given IP address here:
http://ezcmd.com/apps/app_ezip_locator#ezip_locator_api
Enjoy ! I hope this helps.
I'm developing an Android app that has postal address routing in it.
We would like to sort each address in a database table in such a way where each address can be printed out for our driver. We don't want to spend time sorting addresses ourselves when a database table would be ideal for that.
I was thinking somehow to create a primary key in the table on a number that we can easily sort in ascending order. That would make it easy to create a manifest for the driver.
I was researching and found that there was something called WOEID (Where on Earth ID) which I think represents a region but I'm not sure if it would be good for us since 2 postal address in the same neighbourhood could use the same WOEID.
For example these 3 addresses have the same WOEID:
100 Bowden St., Lowell, MA
131 Stedman St., Lowell, MA
50 Stromquest Ave., Lowell, MA
The concept of using a single number like WOEID is perfect for us but we need to sort addresses like these in order so we know which ones are closest to each other.
Maybe there is a web site we can use to send out a request from within our app providing them with the postal address and the site will return a single number representing that address in a format our app can parse.
Maybe there is a way to Geocode or convert latitude and longitude numbers into a single number we can use.
Thanks.
So the problems arise when multiple addresses share the same WOEID? I don't know how many resources are available but couldn't it be in idea to fed this data to some API like Google Maps and calculate the distance from your position to there?
If you want to avoid google a really basic approach could be to do the calculation by yourself. (Though this would be more of an estimation.)
However I got the feeling you want to find the best route over total distance so I think your problem is also related to the travelling salesman problem
Given a list of cities and their pairwise distances, the task is to
find the shortest possible tour that visits each city exactly once.
I found a web site that allows me to do a reverse Geocoding. It returns a latitude and longitude.
I experimented a bit and found that I can add the latitude and longitude together to get a single number. Since giving an exact address to the web site will give results not completely what I'm looking for I give it just a street and city and US state to locate. I can then use the latitude and longitude returned and then sort the house addresses in numeric ascending order.
For example we have many streets that are very grid like so 1 number from the adding of the latitude and longitude represent many homes on 1 particular street. On another street a block away I did the same thing. Now all I have to do is just list everything in the database table like this:
City chosen by a dropdown, US state also chosen by a dropdown, then the geocoded number for each street followed by the home numbers.
Here is the web site I used to get the Geocoding along with a sample street address:
http://where.yahooapis.com/geocode?q=stedman+st,+lowell,+ma