Given a GPS point, we want to check if it is within a parking area. Typically, parking areas in OSM have the amenity:parking key value pair and also are defined as a way that looks like a closed shape. If the search radius of the query has part of the shape boundary in it, then it will return the parking tags. But, if it is within the shape and not intersecting the boundary, then it doesn't return any tags. Is there a way to determine if that GPS point is within the shape to then return its tags?
We know there is a solution to load all parking lots within a certain area (e.g. a whole state or city) and then check if your GPS point is within any of them but this isn't ideal.
Related
I have a sequence of images (video frames). I need to identify the objects as they move (and also some leave the region of interest or new ones appear in the region of interest). By using bwlabel the object to the left of the region of interest is always object 1, but i want to maintain the numbering of the objects as they appear in time (and move out of the region of interest). When one or more objects move out of the region of interest I still want the other objects to have the labeling as if that object was still there. In addition the objects change size throught time. For better clarity I'm attaching a sketch of what i want to achive.
Does anybody have any tips/sugesstions or knows about a function that does this (i was not able to find any)?
So in this model I have several hospital-agents that are placed randomly in an area. These hospitals contains a process flow and at some point in this process flow a new agent 'Bones' is generated, using a split block. The location of these Bones-agents is correctly specified by setting it equal to the (x,y) coordinates of the hospital.
Now I want to make the model more realistic by placing the hospitals in actual location in a GIS map. I did this with success. However, now I need to re-specify the location of the Bones-agents. At the moment of generating the first Bones-agent, I get the follow error:
root.Hospital1.splitblock:
Error when trying to initialize new agent
Caused by: root.Hospital2:
This agent is already defined as agent living in space 'Continuous, based on
GIS map' and can't have behaviour for space 'Continuous'This agent is already
defined as agent living in space 'Continuous, based on GIS map' and can't
have behaviour for space 'Continuous'
What do I need to do to make this work? I have tried setting the location of the Bones-agent equal to the longitude and latitude of the hospital agent with a function:
double longitude = getLongitude();
return longitude;
I did the same for het latitude. I then inputted these functions in the 'latitude' fields of the split block.
When you develop a model, you have to choose what kind of space you will use. Remember that all the canvas in which you put agents, and the map and stuff is based on a scale, so you can't mix a map with elements that are created with the space markup (with space markup i mean nodes, paths, rectangular nodes etc).
So the bones agents should also be placed in the map... It seems that you are not doing that, and you are probably placing the bones agent using the space markup.
But it's possible to do this of course, but you have to do it in another agent. Create a new agent called continuousSpace for instance, and place your bones agents there.
After that you will have to create a navigation button using viewAreas (from the presentation palette) to move from one agent to the other (meaning from the gis space to the markup space).
Otherwise, you can also place the bonesagents in the gis space (in the map) and it will also work.
Good luck :)
I need a framework which takes a set of latitude longitude points and plots on a world map, grouped by country having the count of points as a marker on each country. Grouping here is the count of latitude longitude points in a country.
And as I drill down into a country, the clustering should change to state based one. And the next level, to districts.
Leaflet marker cluster is something very similar to what I have asked for, but the grouping is based on proximity and it doesn't consider country or state boundaries. That is, they are not region aware.
Regionbound.com has tweaked in some code in the leaflet code for making it region aware,
Sample marker definition:
var marker1 = new L.marker([-37.8, 145], {regions: ["Asia-Pac", "Australia", "VIC", "Melbourne"]} );
But the sample code says, every latitude longitude must be defined along with some extra parameter containing place information.
I could get the place information using reverse geocoding, but reverse geocoding every latitude longitude is time consuming right.
Highmaps provided by Highcharts is one another solution, but there, every country has code which should be assigned a value[count of point coordinates belonging to that country].
But all I have is latitude longitude points, no country or state information.
Thus, I need something which takes only a set of latitude longitude and does clustering based on country, state, district depending on the zoom level.
You have 2 separate needs in your questions:
Map your lat/lng coordinates to appropriate administrative areas. E.g. through the reverse geocoding that you mention.
Display "clusters" on those administrative areas depending on zoom level.
As for point 1, you know that lat/lng points do not say by themselves which administrative area(s) they belong to. So "reverse geocoding every latitude longitude" is a mandatory step. Whether time consuming or not depends on the solution you choose to perform this operation.
If I understand correctly, you would like a "framework" that could do that automatically for you. But frameworks are usually data agnostic, and if they do not have data about boundaries of those administrative areas, they cannot help you.
You may rather look for "services" (like the Mapbox Geocoding API that you mention) or software that would already have such data. It is not time consuming if you can program the lookup (or perform "bulk" operations) and if you are not limited by the requests rate and your amount of points to map (which may be the case with Mapbox).
You could very well set up your own application to perform this mapping:
As for the dataset for administrative areas boundaries, you would probably be interested in links in this post: Are there any free administrative boundaries available as shapefiles? If your points are limited to a few countries, it will be easier for you to find the appropriate data source(s).
Once you have that data, many GIS software should be capable of mapping your lat/lng points to the areas they belong to. This would be mainly for a "one-shot" operation, if your set of points do not change much.
A "web-compatible" alternative would be for example to use Leaflet with point in polygon for Leaflet plugin. You would need your boundaries data converted to GeoJSON format first. Again, GIS software should be capable of doing so, or many online services as well (search for "convert geojson" for example).
A server-side solution would avoid having to manage the entire boundaries data through network and in client browser (if you need to perform the mapping dynamically). I am sure many GIS servers are capable of performing this operation, once they are fed with the boundaries data.
For point 2, once you have completed the above step, I think you would have many options available, including those you mention (RegionBound, Highmaps).
Even with standard mapping libraries (Leaflet, OpenLayers 3), you would just need to build your "clusters" (markers on administrative areas with a number saying how many points are in there), like you have to do with Highmaps anyway for example.
Computing the number of "clustered" point is as easy as filtering your points per area name / code. Then switch the clusters to the desired administrative level when the map zoom changes.
So the key is really to determine first to which areas your points belong to (point 1).
Then a small question would rise about where to place the "cluster" marker:
On centroid of the administrative area? You need the coordinates of that centroid from your data source, or a good algorithm to compute it from the boundaries (good luck on that…).
On "center" of the bounding box of the area? Leaflet can easily compute that: from your area vector shape, you would do myShape.getBounds().getCenter().
On barycentre / centroid of the clustered points? This is what Leaflet.markercluster and RegionBound do (do not know for Highmaps).
Good luck!
I have a table that contains a bunch of Earth coordinates (latitude/longitude) and associated radii. I also have a table containing a bunch of points that I want to match with those circles, and vice versa. Both are dynamic; that is, a new circle or a new point can be added or deleted at any time. When either is added, I want to be able to match the new circle or point with all applicable points or circles, respectively.
I currently have a PostgreSQL module containing a C function to find the distance between two points on earth given their coordinates, and it seems to work. The problem is scalability. In order for it to do its thing, the function currently has to scan the whole table and do some trigonometric calculations against each row. Both tables are indexed by latitude and longitude, but the function can't use them. It has to do its thing before we know whether the two things match. New information may be posted as often as several times a second, and checking every point every time is starting to become quite unwieldy.
I've looked at PostgreSQL's geometric types, but they seem more suited to rectangular coordinates than to points on a sphere.
How can I arrange/optimize/filter/precalculate this data to make the matching faster and lighten the load?
You haven't mentioned PostGIS - why have you ruled that out as a possibility?
http://postgis.refractions.net/documentation/manual-2.0/PostGIS_Special_Functions_Index.html#PostGIS_GeographyFunctions
Thinking out loud a bit here... you have a point (lat/long) and a radius, and you want to find all extisting point-radii combinations that may overlap? (or some thing like that...)
Seems you might be able to store a few more bits of information Along with those numbers that could help you rule out others that are nowhere close during your query... This might avoid a lot of trig operations.
Example, with point x,y and radius r, you could easily calculate a range a feasible lat/long (squarish area) that could be used to help rule it out if needless calculations against another point.
You could then store the max and min lat and long along with that point in the database. Then, before running your trig on every row, you could Filter your results to eliminate points obviously out of bounds.
If I undestand you correctly then my first idea would be to cache some data and eliminate most of the checking.
Like imagine your circle is actually a box and it has 4 sides
you could store the base coordinates of those lines much like you have lines (a mesh) on a real map. So you store east, west, north, south edge of each circle
If you get your coordinate and its outside of that box you can be sure it won't be inside the circle either since the box is bigger than the circle.
If it isn't then you have to check like you do now. But I guess you can eliminate most of the steps already.
I have a collection that has a 2d geospatial index on a field (center) which is an array of long/lat, the collection also has a radius field. So each item can represent a circle. I know that mongodb has a operator $within, and I want to get a list of all items that contain a specific point [long,lat], but it seems that I can only check which points are within a specific shape.
You are correct, right now, you can't do what you want. Please file a feature request at http://jira.mongodb.org as I can't find one already existing for this.
This is how I solved it (i.e. get a shape that covers a given point) in my situation, using a basic grid. It has a limited accuracy, depending on the grid resolution:
create a collection "grid" with points that covers the common bounding box of all your shapes (use a nested for loop in javascript)
create a 2d index on the grid
for each shape, search for all the grid points that lie within the shape; label each grid point with the id of the shape (use an array attribute on the grid point)
To see in what shape(s) a point lies, search for the closest grid point, and return its assigned shape(s) property. First check for the common bounding box, because points outside it should always return 'not in any shape', and not use the closest grid point.
Depending on the precision you need, this might or might not be a usable solution. The accuracy depends on how many points you put in your grid, and you may be able to do something smart with local densities of your grid.