I need to be able to evaluate how remote a location is given its geographical coordinates. I rate remoteness based off of a few key metrics, so far, I am only able to calculate a subset of all the required metrics:
The cellular reception at the given coordinate. More specifically, the density of cell towers around the coordinate. This can be found using opencellid.org.
Elevation. This can be found using Google's Elevation API
How can one find these remaining metrics for remoteness?
The type of natural feature the coordinate is in. (eg. Lake, River, Glacier, Ocean, Island, Mountain)
Distance to the nearest road. (Google's Snap Road API and Nearest Road API only work if the coordinate is within 50m of a road, that will not work as some coordinates are hundreds of km from the nearest road).
About land type
For your first question it has already been answered here, except it is only for land/water.
My approach would be the following:
Using maps static, you get the image at your coordinate, you get the pixel at the center of your image (your coordinates) and you use a hashmap/dictionary that contains all the different possible colors and their land type, would be very quick to implement. But you can find out different ideas by reading the first link provided.
For strength of cellular signal
As for your second question, you can use Google API to detect the closest cell towers object, using the locationAreaCode that you can obtain through the coordinates:
An example cell tower object is below.
{
"cellTowers": [
{
"cellId": 170402199,
"locationAreaCode": 35632,
"mobileCountryCode": 310,
"mobileNetworkCode": 410,
"age": 0,
"signalStrength": -60,
"timingAdvance": 15
}
]
}
What is the purpose I wonder? You could take a sampling of coordinates around the fix and if they are mostly on a hill or in water it is definitive, it seems people know how to figure out this kind of stuff with google apis.
Would this be good enough?
Get Lat/Lon and range from a sources like this: https://my.opencellid.org/dashboard/login?ref=opencellid for free. Use a formula to determine the distance between the gps locations like this: https://nathanrooy.github.io/posts/2016-09-07/haversine-with-python/. Then make your own determination on strength based on "range" and terrain. perhaps create a DB table of say 500 zip codes with label for terrain type rating. If 10 or something it's the worst terrain and you drop the strength by something that makes sense.
Related
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
As part of a developer challenge, I am trying to determine the land mass closest to a given coordinate. Obviously, if the point is on land, I use reverse geocoding and can get details. The problem is that if the point is in a body of water, especially oceans, it often won't return anything (Google, Nokia, Bing). I'd like to know that a point 3 miles off the coast of California is 3 miles from USA, or x miles from Japan, y miles from South Korea when a point is reasonably near more than one country. Is there any service that provides this information?
Take a KML file of the world's Maine Regions
Simplify it down to a minimum number of rough polygons.
Take your location, does it lie within one of the polygons?
If your location lies with a polygon, then it is at sea, iterate though the points on the inner and outer boundary to find the nearest one using the Haversine Formula. This will be the nearest point on land.
If your location does not lies with a polygon, you are already on land, do a direct reverse geocode.
Just imagine the world is a bit like the board from the game Diplomacy
Now coalesce the sea areas into larger polygons with holes for islands.
If you're not at sea you must be on the land right?
check older post in here Verify if a point is Land or Water in Google Maps, check the answer about the Koordinates Vector JSON Query service
I have set up a system that calculates the distance between two locations using http://www.rubygeocoder.com/, however, to be able to calculate the (tax-deductible) kilometer-costs (e.g travel compensation) I would need to get distance by road, for example by using Google.
How is this best done?
You can use https://developers.google.com/maps/documentation/directions/.
For example a request to:
http://maps.googleapis.com/maps/api/directions/json?origin=Toronto&destination=Montreal&sensor=false
will get you the directions from Toronto to Montreal and along with it the total distance.
https://github.com/apneadiving/Google-Maps-for-Rails wraps the directions API so you might find that it makes your life easier. You might also find that it is overkill in this case since we're only talking about a single request.
I'm working on a GeoTargeting application. I'm curious if longitude and latitude of a point on the earth can change?
If you know the exact position of the statue of liberty how sure is it that longitude and latitude will stay the same.
Does it change according to the season, time in the year, or slowly over time
Wikipedia to the rescue:
The surface layer of the Earth, the
lithosphere, is broken up into several
tectonic plates. Each plate moves in a
different direction, at speeds of
about 50 to 100 mm per year. As a
result, for example, the longitudinal
difference between a point on the
equator in Uganda (on the African
Plate) and a point on the equator in
Ecuador (on the South American Plate)
is increasing by about 0.0014
arcseconds per year.
It depends on the map projection variables you use. Currently WGS-84 is used mostly.
The same point can have different coordinates depending on the variables. They do not differ a lot, I remember the difference between EUR-50 (or something like that) and WGS-84 was at most 50 meters or something.
You're tangentially referring to geodetics, which is the science of modelling (representing) the shape of the earth. So while a physical location may not change, the datum (model) used by a geodetic coordinate system will change, fortunately this does not happen frequently.
In North America NAD83 is the mostly widely used datum, which replaced NAD27.
Did I mention that Geographic Information Systems (GIS) was my foray into software development?
Yes. Zip codes get split all the time, and doing so would move the center of the zip code to a new location.
47.554 always equals 47.554
But if the shape of the earth changes or you are using different methods of calculations (there are plenty) or if the input data changes in precision or if if your compiler treats floating point differently..
you'll end up in different long/lat
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.