I need to georeference automatically thousands of scanned maps (263 inner points inside the map and some in the territory limits), all maps represent the same territory and only change some conventions. I Tried to identify contours with OpenCV and look like good parameters for machine learning and georeferencing, but i dont know how to identify an specific contourn in different images, If I succeed, I can put the georeference for that contur. ¿some ideas?, ¿other possibilities?.
Here i put two maps for clarifying the idea: ;
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I'm trying to figure out the best way to analyse a grasshopper/rhino floor plan. I am trying to create a room map to determine how many doors it takes to reach an exit in a residential building. The inputs are the room curves, names and doors.
I have tried to use space syntax or SYNTACTIC, but some of the components are missing. Alot of the plugins I have been looking at are good at creating floor plans but not analysing them.
Your help would be greaty appreciated :)
You could create some sort of spine that goes through the rooms that passes only through doors, and do some path finding across the topology counting how many "hops" you need to reach the exit.
So one way to get the topology is to create a data structure (a tuple, keyValuePair) that holds the curve (room) and a point (the door), now loop each room to each other and see if the point/door of each of the rooms is closer than some threshold, if it is, store the relationship as a graph (in the abstract sense you don't really need to make lines out of it, but if you plan to use other plugins for path-finding, this can be useful), then run some path-finding (Dijkstra's, A*, etc...) to find the shortest distance.
As for SYNTACTIC: If copying the GHA after unblocking from the installation path to the special components folder (or pointing the folder from _GrasshopperDeveloperSettings) doesn't work, tick the Memory load *.GHA assemblies using COFF byte arrays option of the _GrasshopperDeveloperSettings.
*Note that SYNTACTIC won't give you any automatic topology.
If you need some pseudo-code just write a comment and I'd be happy to help.
I am developing a location-based application in which I need to get nearby location name of any geopoint selected by user. I'm using Google Places API which is working fine for me.
Only problem is the service returns null for geopoints in water. Is there any way that I can retrieve nearby locations for a geopoint in water or ocean?
AFAIK the API has no way to do that.
So, you've got two options, in order of the effort it takes:
When user taps water just throw a dialog saying "Please select a
point on land". Next to no effort and will slightly annoy the user.
Try to find the closest land geopoint yourself and use it to run the API request on
(instead of the original point). Below are some ideas on that.
A good approach can be based on this answer: basically you can get a KML file with land polygons. For performance reasons, you can simplify the polygons to the extent that makes sense for your zoom levels. Now if your point is in one of those polygons -- it's sea. And you can simply iterate over all polygon edges and pick the one that's closest to your point, then pick a point on it - again closest to your point - and do one little epsilon-sized step towards the outside of the polygon to get a land point you can do a geocode request on. Also, the original author suggests you can use Haversine formula to determine neares land point -- I'm not really familiar with the appliance of that one.
The downside is, you have to deal with KML, iterate over a lot of polygons and optimize them (and lose precision doing that, in addition to possible differences between marineregions.org data and Google Places data)
Another cool trick you could try is using Sobel Filter [edge detection] on the visible map fragment to determine where coastline is (although you will get some false positives there), then trace it (as in raster->vector) to get some points and edges to calculate the closest land position with, in a manner similar to the former approach. Here's a clumsy drawing of the idea
For Sobel edge detection, consider GPUImage lib -- they have the filter implemented and it's probably going to work crazy fast since the lib does all the calculations on GPU.
UPD Turns out there's also a service called Koordinates that has coastline data available, check the answer here
my Application is given a list of Geocorrdinates and now I have to determine which of those Coordinates are inside a defined Area. For example the Search would definiton would be: Show me all Areas where 100 Coordinates are in an Area of 1km^2. So I have to find out which of these coordinates are together in Areas of 1km^2 and more than 100.
But that seems to be a hard Job for my understanding of geocoordinates and I hope someone can help me with that.
The Latitude coordinates are consistent and Distance between two degrees is 111km. For example the Distance between N50,985° and N50,995° is 1,11km. The Distance between 2 Longtitude Coordinates is not so easy and depends on the Latitude coordinate.
But to be honest, I really don't know how to start.
Does someone have an Idea and can help me?
Thank you
twickl
what you need is a geospatial database, I'd recommend PostgreSQL with PostGIS. It provides the function you need to calculate this kind of stuff. Also search for good tutorials about it. An example is a radius search like "give me all McDonalds in a radius of 10km where I live"
If the problem with having a database is simply that you don't want to host it (or pay for someone to host it) then I recommend Fusion Tables.
I don't know if it supports exactly the functionality you are looking for, however I suppose you could select a random point and do a count of everything within range of that point.
I think that what you are talking could be quite a cpu intensive task (depending on how accurate you want it to be). Not something I would personally try and unload onto a portable device.
Say I want to build a check-in aggregator that counts visits across platforms, so that I can know for a given place how many people have checked in there on Foursquare, Gowalla, BrightKite, etc. Is there a good library or set of tools I can use out of the box to associate the venue entries in each service with a unique place identifier of my own?
I basically want a function that can map from a pair of (placename, address, lat/long) tuples to [0,1) confidence that they refer to the same real-world location.
Someone must have done this already, but my google-fu is weak.
Yes, you can submit the two addresses using geocoder.net (assuming you're a .Net developer, you didn't say). It provides a common interface for address verification and geocoding, so you can be reasonably sure that one address equals another.
If you can't get them to standardize and match, you can compare their distances and assume they are the same place if they are below a certain threshold away from each other.
I'm pessimist that there is such a tool already accessible.
A good solution to match pairs based on the entity resolution literature would be to
get the placenames, define and use a good distance function on them (eg. edit distance),
get the address, standardize (eg. with the mentioned geocoder.net tools), and also define distance between them,
get the coordinates and get a distance (this is easy: there are lots of libraries and tools for geographic distance calculations, and that seems to be a good metric),
turn the distances to probabilities ("what is the probability of such a distance, if we suppose these are the same places")(not straightforward),
and combine the probabilities (not straightforward also).
Then maybe a closure-like algorithm (close the set according to merging pairs above a given probability treshold) also can help to find all the matchings (for example when different names accumulate for a given venue).
It wouldn't be a bad tool or service however.
I'm working on a project that contains Thomas Brothers Map page and grid numbers. Is there a way to programatically convert from this map page to a latitude & longitude?
An Example would be for the intersection of the US101 & I405 freeways.
ThomasBrothers: 561-3G (page-grid)
Not that I know of, but I don't have a lot of experience with Thomas bros maps. Are you talking about printed version of the maps or is there a link somewhere to an online map?
If you just need a few lat/longs, then you can look up the locations that correspond to the grid and get the lats and longs manually at many websites, including http://itouchmap.com/latlong.html
If you provide a link to a Thomas bros map that you are using, I might be able to help further.
By looking at the link above, you can determine that US 101 and I-405 has a latitude of 34.16073390017978 and a longitude of -118.46952438354492.
Your best source would be the map publisher. If they choose to help, someone there can tell you exactly what you need to know. If they won't help you, it's unlikely that they've released the information to anyone else.
If that's the case, you could do some work by hand to correlate one point from the map grid to your target coordinate system. Effectively, you could reverse engineer a mapping "datum" for each page. You'd also have to know what map projection was used to render the maps, so that you can calculate the transform from the map coordinates to the geographic coordinates as you move away from your "origin". Finally, you'll need to establish the orientation of the map, since different notions of "north" exist.
It sounds like the Thomas maps use a new grid for every page, rather than bleeding the grid continuously from page to page. If that's the case, you'll have to correlate one point on each map. For example, find a spot where a map grid intersection coincides with a notable road intersection. Then you can find the coordinates of the road intersection using a map with latitude and longitude (a topographic map, TerraServer, etc.). Doing this with two points on the same vertical grid line should help you establish the north used on the map as well.
The short answer is that each of the nine regions has a grid derived from a Lambert conformal conic projection with custom parameters, so you cannot write a conversion program without the parameters.
I've also got ThomasBros. pages that I would like to convert to lat/long for lookup against Google Maps API. They also provided something called TBXY ... not sure what this is -- perhaps some notation for GPS/lat/long?
<Area>"El Cajon"</Area>
<ThomasBrothers>"1297 5E"</ThomasBrothers>
<TBXY>"6481390:1827008"</TBXY>
Thomas Brothers Maps invested a lot when developing their GIS system to create their digital mapping system. Though the first "digitally produced" map was Sacramento County-1990, the development began back in 1986. I expect that their map projection equations are a well guarded trade-secret, which Rand McNally now owns. I'd don't know those equations, but would also like to know them.
There are 9 projections covering the 48 states. If you know the equations for Los Angeles, it is valid across California & Nevada. Oregon & Washington have their own projection. Arizona, New Mexico, Colorado, and Utah share another projection.
I do know this...
As many know, the page grid is an exact 1/2 mile square, or 2640 feet by 2640 feet. The coordinate measurement unit is 1 foot.
To determine the Thomas Brothers XY Coordinate, get one or more of the Thomas Guide CD- ROM maps, which were recently discontinued. The last ones produced for certain California counties were the 2008 edition. Last editions for Seattle, Portland, Las Vegas, and Phoenix/Tucson were the 2007 edition. Each is still available on the Rand McNally website for $20.
When you geo-code a group of addresses, you'll see an output file with the TGXY coordinates and Lat/Lon for the addresses you specified, and the page # and grid that point is in. Once that file is open, you can click on the map to add additional geo-coded points, which will also provide both the coordinates. The output file is saved in an Access database ".mdb" file.
If you know a lot about map projections or solid geometry, the set of corresponding TGXY and Lat/Lon coordiantes will provide you some good data for testing.
As you mentioned San Diego Page 1297, I'll provide its bordering coordinates.
West x=3062760
East x=3086520
North y=0985040
South-y=0966560
This is not in range of the "TBXY" you found on Google. Maybe it's the same projection, with a relocated origin.