For a project on geospatial data analytics, we are currently extracting road type and speed limit data of certain roads along a track by using Overpass' polygon query (where we define the roads by a buffer zone around them). The problem is that in the case of separate tracks, we can end up with disconnected polygons which often lead to a significant increase in computation time. In this situation, we were wondering how Overpass' polygon query actually works. Does the algorithm actually query only the data inside this polygon/these polygons, or does it query inside a bounding box, after which it filters out the data inside the polygons?
The algorithm checks if nodes are inside the defined polygon, or if a way crosses the polygon. It's not based on bounding boxes as you mentioned.
From your description it's not quite clear why disconnected polygons pose an issue. You should get decent performance with a lz4-based backend and a reasonable number of lat/lon pairs in your (poly: ) filter (the more pairs you provide, the more expensive the computation gets).
BTW: The best approach to tackle this issue would be something I described in this blog post: https://www.openstreetmap.org/user/mmd/diary/42055 - unfortunately, this feature is not yet available in the official branch. If you see some use for it, please upvote here: https://github.com/drolbr/Overpass-API/issues/418
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I have a high volume dataset with keys like this:
lat:6.897585,
long:52.785805,
speed:12,
bearing:144
Basically it is a dataset of records of various trips on cars. The data was stored every few seconds during each trip. The main goal of this project is to be able to visualize only u-turns (turn arounds) on a map. But for now, I am trying to at least show the data on specifc roads. For that, I am using Overpass API
With the help of Overpass Turbo, I can get a dataset with all the roads I need.
However, in the dataset, the road's geometry is represented with LineString type.
My question is, How can I get a bounding box(es) of the roads from Overpass API, so later on, I can display events that happened only on the given roads? Or maybe you have a better solution on how to achieve this?
A bounding box wouldn't be very helpful here, as using it to filter your points would show everything that falls within the box (which could include other nearby roads)
It sounds like getting a buffer around a linestring might get you closer, but could still include points that are within the buffer but not on the road you are inspecting.
The smarter way to do this would be to assign each event to a road segment using some logic based on their attributes/properties, so you don't have to depend on a spatial filter.
I've created a base layer and 6 different overlay (Points of Interest) layers for a leaflet map.
The base layer of markers can appear on the map almost anywhere in the world, but I want the POI layers to appear only if they are in the same area (mapBounds) of the base layer. Probably the screen size.
All the data is pulled from a MySQL database and using Ajax I create the various sets of markers from two different tables, base and poi. This much is all done and working, you can see it at https://net-control.us/map2.php. The green and blue markers are from the base table, other markers are currently selected for view by clicking on the appropriate icon in the lower right. The only one active at the moment is 'Fire Station'. But if you zoom out far enough you will see additional fire stations in the Kansas City area, and in Florida. Those sets are not needed.
After the query runs I create a fitBounds variable of the base layer and another poiBounds for the poi layer. But I'm not sure I need the poiBounds. The number of base markers is generally less than 50 for the base query, but if all the poi markers are pulled world wide that number could be very large.
So I'm hoping someone can help me determine a best practice for this kind of scenario and maybe offer up an example of how it should be done. Should I...
1) Download all POIs and not worry about them appearing outside the base bounds layer? Should I inhibit them from showing in the javascript or in the SQL? How?
2) If I inhibit the unwanted points from SQL do I test one POI at a time to see if its included in the base bounds? How? Are there MySQL functions perhaps to work with this kind of data?
I'm fairly new at leaflet maps and would appreciate examples if appropriate.
2) If I inhibit the unwanted points from SQL do I test one POI at a time to see if its included in the base bounds? How? Are there MySQL functions perhaps to work with this kind of data?
You probably want a column of type POINT, a spatial index on such column (which internally is likely to be implemented as an R-Tree), and spatial relation functions on your SQL query to make use of that index.
Start by reading https://dev.mysql.com/doc/refman/8.0/en/spatial-types.html. Take your time, as spatial databases, spatial data types and spatial indices work a bit differently than their non-spatial equivalents.
I have a number of spatial database, through which I have identified particular types of land-cover. The topographic layer [defining land-cover] is made up of multi-polygons and I am using a separate point layer in order to join a classification type to it. However, the areas portrayed in the topographic layer may be formed from several individual polygons, without a total perimeter outline to identify the area. Therefore, the classification point may sit in just one individual polygon of the overall area [see below].
Example. Image is of a park, which consists of over 20 individual polygons. The point that classifies the area as a park sits within one of the polygons and cannot be attached to the entire area.
I would like to be able to apply the point based classification to the whole park area. I have tried to use ST_UNION function in order to do such, but have been unable. Does anyone know of a way to dissolve the area into a single shape/remove the pathways? This is a small example of a much larger data set, where there is little scope of manually defining area sand buffers in order to classify the data, thus I wondered if there was a practicable solution.
If anyone can help, it would be hugely appreciated....
SELECT ST_Collect(t.the_geom) as singlegeom FROM TABLE t; http://postgis.net/docs/ST_Collect.html
I created a website (http://www.cartescolaire.paris) that basically loads a GeoJSON and displays it on a map using Leaflet.
This geoJSON is pretty large (over 2 Mb), the loading time can be very long (it doesn't even load on IE 11). More importantly the resulting map is not very responsive when zooming / navigating.
There are around 110 zones (clicking on a point in the map highlights the zone it belongs to), each of them made from dozens of polygons.
However the only important information that I want to visualize is the external boundaries of each zone.
Such a compressed geometry would be much more efficient performance-wise.
The complexity arises from the constraint that the zones shouldn't overlap.
The final result should be disjoint clusters.
Any idea how I could do that ?
Thanks a lot !
Bonjour,
You sound to need merging of polygons, so that you decrease your number of vector features, the weight of your GeoJSON file and map responsiveness. Keeping your resulting polygons disjoint should not be difficult.
You should have plenty resources on SO / GIS Stack Exchange and Google on this, for example:
https://gis.stackexchange.com/questions/118223/merge-geojson-polygons-with-wgs84-coordinate
https://gis.stackexchange.com/questions/118547/convert-geojson-with-multiple-polygons-and-multipolygons-into-single-multipolygo
http://morganherlocker.com/post/Merge-a-Set-of-Polygons-with-turf/
(see also the related posts on SO on the right menu of this page, just above "Hot Network Questions")
Your case might be slightly different as most of your polygons are not adjacent, but are actually separated by empty areas / a margin (streets).
You might also be interested in UTFGrid for the interaction (clicking on the map to open the school associated with that area), as it would dramatically restore your map responsiveness: instead of vector shapes, you have the equivalent of tiles. See an example: http://danzel.github.io/Leaflet.utfgrid/example/map.html
However, I do not think you can visually show the areas with UTFGrid.
But you could combine this approach with canvas-based tiles, or even pre-generate tiles on your server and have them ready for display, rather than keeping a GeoJSON for client-side computation.
Bon courage !
I'm a complete illiterate when it comes to working with geographical data, so bear with me.
For our application we will be tracking a fairly large amount of rapidly changing points on a map. It would be nice to be able to cache the location of these points in some kind of map-tile structure so it would be easy to find all points currently in the same tile or neighbouring tiles, making it easier to quickly determine the nearest neigbours and have special logic for specific tiles, etc.
Although we're working for one specific (but already large) location, it would be nice if a solution would scale to other locations as well. Since we would only cache tiles that concern the system, would just tiling the enitre planet be the best option? The dimensions of a tile would then be measured in arc seconds/minutes, or is that a bad idea?
We already work with Postgres and this seems like something that could be done with PostGIS (is this what rasters are?), but jumping in to the documentation/tutorials without knowing what exactly I'm looking for is proving difficult. Any ideas?
PostGIS is all that you need. It can store your points in any coordinate reference system, but you'll probably be using longitude/latitude. Are your points coming from a GPS device?
PostGIS uses GIST indexing, making the search for points close to a given point quite efficient. One option you might want to look at, seeing that you are interested in tiling, is to "geohash" your points. Basically, this turns an (X,Y) coordinate pair into a single "string" with a length depending on the level of partitioning. Nearby points will have the same geohash value (= 1 tile) and are then easily identified with standard database search tools. See this answer and related question for some more considerations and an example in PostgreSQL.
You do not want to look at rasters. These are gridded data, think aerial photography or satellite images, weather maps, etc.
But if you want a more specific answer you should give some more details:
How many points? How are they collected?
Do you have large clusters?
Local? Regional? Global?
What other data does this relate to?
Pseudo table structure? Data layout?
etc
More info = better answer
Cheers, hope you get your face back