When using overpass turbo to query the OpenStreetMaps data I am finding different results when I define the search area using geocode area, bbox, and area.
For example:
Geocode Area
[out:json]
{{geocodeArea:Bulacan, Philippines}}->.searchArea;
Area
[out:json]
area["ISO3166-2"="PH-BUL"];
and one can also use bbox as well.
However, when I use Geocode area vs the area command I get different resulting outputs for the same query. In the Geocode version I get many more data points whereas in the area query I get just one. Is there any specific reason why this is the case?
How does the geocodeArea work vs area in the above example? Shouldn't these statements be equivalent?
In fact both areas are exactly the same:
{{geocodeArea:Bulacan, Philippines}}->.searchArea;
.searchArea out;
area["ISO3166-2"="PH-BUL"];
out;
As you haven't provided a full query in your question, most likely the issue is caused by the lack of .searchArea in the second example. Due to this the query result would be stored in a default set ._ instead. If you're not careful enough, this default set gets easily overwritten by subsequent statements in your query.
So by replacing
area["ISO3166-2"="PH-BUL"];
by
area["ISO3166-2"="PH-BUL"]->.searchArea
you should get exactly the same results.
Related
I want to simulate a 2D heat transfer process in the subsurface on a region which is infinite on the r-direction. So, as you know, the very basic way to model this is to draw a geometry that is very long in the r direction. I have done this, and the results that I obtain is correct as in this case, the results are matched with the analytical solution. As you know, there is a capability in Comsol called infinite element domain which serves the purpose to the problem mentioned above. In this case, we need to define a limited geometry on which we want to solve the PDE, and also need to draw a small domain acting as the Infinite Element Domain. However, in this case, the results are not correct because they are not matched with the analytical solution. Is there anything that I am missing to correctly use Infinite Element Domain in comsol?
Any help or comment would be appreciated.
Edit:
I edited the post to be more specific.
Please consider the following figure where a fluid with high temperature is being injected into a region with lower temperature:
https://i.stack.imgur.com/BQycC.png
The equation to solve is:
https://i.stack.imgur.com/qrZcK.png
With the following initial and boundary conditions (note that the upper and lower boundary condition is no-flux):
https://i.stack.imgur.com/l7pHo.png
We want to obtain the temperature profile over the length of rw<r<140 m (rw is very small and is equal to 0.005 m here) at different times. One way to model this numerically in Comsol is to draw a rectangle that is 2000 m in the r-direction, and get results only in the span of r [rw,140] m:
https://i.stack.imgur.com/BKCOi.png
The results of this case is fine, because they are well-matched with the analytical solution.
Another way to model this is to replace the above geometry with a bounded one that is [rw, 140] m in the r-direction and then augment it with an Infinite Element domain that is meshed mapped, as follows:
https://i.stack.imgur.com/m9ksm.png
Here, I have set the thickness of Infinite Element to 10 m in the r-direction. However, the results in this case are not matched with the analytical solution (or the above case where Infinite Element domain was not used). Is there anything that I am missing in Comsol? I have also changed some variables with regard to Infinite Element in Comsol such as physical width or distance, but I didn't see any changes in the results.
BTW, here are the results:
https://i.stack.imgur.com/cdaPH.png
Is there a way to reorder points in geojson so that my line "sticks" to the road. Right now I tried sorting based on longitude, but "S" shaped curves puts some points out of gps sequence, but in sort order (hence, the zig-zag)
How would I go about reordering my points correctly? Currently I'm using turf for other stuff, but another library would also be fine.
Where did these points come from? If they were ordered either chronologically or antichronologically, then perhaps that order was fine to begin with. Perhaps there is additional metadata that can help order your points with ease.
If not, the only thing I can think of is to employ some sort of nearest neighbor sorting: https://en.wikipedia.org/wiki/Nearest-neighbor_chain_algorithm
This page: https://github.com/pastelsky/nnc seems to be the source of the animation seen on wikipedia and relies on javascript code, so perhaps you can make use of the underyling library used?
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
Has anyone used the ogrinfo [-spat xmin ymin xmax ymax] option in the GDAL tools? I am able to run the - sql query on the shape files and get the answers/shapes but however if I use the lat/long values in spat, I dont get the results (However I dont get an error). I could not find an example at all.
This suggests one of three options:
Your file is not georeferenced as you expect
Your area of interest extent values are entered incorrectly
There are no features that both match your sql query AND lie within the extent as you have defined it.
You can test your understanding of the -spat values by creating a polygon to match and overlaying it in (say) QGIS to see how it overlaps with your data. This will quickly help you eliminate the options above. After that - you'll understand the feature for future use :)
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.