I have a data set of eastings and northings and I need to convert these to a latitude and longitude value. Does anyone have any idea how to do this on iOS. I have tried using convert eastings and northings
javascript function but I got stuck in an infinite loop in the do while statement.
If anyone has any thoughts or experience on the matter please do share, I would really appreciate it.
Many thanks
Jules
You need a projection library, and proj4 is a dominant one. Here's a helpful description of using it with iOS: https://gis.stackexchange.com/questions/6658/how-to-integrate-proj4-into-an-ios-iphone-project
You'll need to know what the source coordinate system is, e.g. UTM, NAD, mercator, etc.
Related
I'm looking for some help on comparative OpenLayer functions for the following Google maps functions, can someone please let me know what these would be?
I'm currently using
For getting distance, using the distance matrix API:
http://maps.googleapis.com/maps/api/distancematrix
For getting latitude and longitude of the current address:
http://maps.googleapis.com/maps/api/geocode/json?address
Kindly check the attachment which are using for getting latitude, longitude and distance matrix.
Function names:
function getLatLng($add)
function getRoadDistance($from, $to)
--
things are a little bit more complicated in OL than they are with the google-api
Routing: if you have a small road network you can consider creating a Database in PostGIS and use pgrouting to get routing functions, you can find more on it here
Or if you want to use it on a bigger scale there some APIs that do it for you, for example yourNavigator, you'll have to make a get request with your coordinates like this
http://www.yournavigation.org/api/1.0/gosmore.php?format=geojson&flat=startLatitude&flon=startLongitude&tlat=destLatitude&tlon=destinationLongitude
there is also the OSRM for the same purpose.
to get the longitude and latitude based on an address you can use the geocoder for Openlayers 3
that's what I could think of right now, I hope it helps
currently, i have a table with locations (latitude, longitude). I calculate nearby calculations using sin, cos as described here
This seems rather slow. I am having the idea of pre-calculating the distance to a fixed point f and store it along the locations. When I now want to find locations nearby i just calculate distance to the same fix point and can then find them by doing some less or equal comparing.
Does my idea make sense? Is there a standard way to do that? I am in the thinking phase, so i do not have any code to show yet.
Your idea won't work unless all your locations are collinear, which most probably is not the case.
Are you using SQL to do the calculations? Are you properly using indexes? Maybe you could share a bit of your code with us.
I'm working with openCV and I'm a newbie in this field. I'm researching about Camshift. I want to extend this method by using multiple histograms. It means when tracking an object has many than one apperance (ex: rubik cube with six apperance), if we use only one histogram, Camshift will most likely fail.
I know calcHist function in openCV (http://docs.opencv.org/modules/imgproc/doc/histograms.html#calchist) has a parameter is "accumulate", but I don't know how to use and when to use (apply for camshiftdemo.cpp in opencv samples folder). This function can help me solve this problem? Or I have to use difference solution?
I have an idea, that is: create an array histogram for object, for every appearance condition that strongly varies in color, we pre-compute and store all to this array. But when we compute new histogram? It means that the pre-condition to start compute new histogram is what?
And what happend if I have to track multiple object has same color?
Everybody please help me. Thank you so much!
I have tried a lot and googled a lot but finally I'm ending up by putting this query here.
I have user's long and lat, now I want to get all the nearby localities of specific range i.e 500 Kilometres. I searched and came to know google places API can help me out in this, but It is not bringing correct result.
https://maps.googleapis.com/maps/api/place/search/json?location=33.7167,73.0667&radius=500&type=funeral_home&sensor=false&key=key
In above mentioned link I have given a type "funeral_home" respectively but the result it brings is not of type funeral_home. It is bringing data from every type irrespective of the type i provide. Anyone please help and thanks in advance.
The parameters name is types (not type). Changing that returns zero results (no errors).
The radius parameter is actually measured in meters (not km), with a max of 50,000. Changing that too gives 5 results (no errors).
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.