I have a relational database where each entry is marked as a dot with latitude/longitude coordinates. I give the user the ability to mark an arbitrary polygon on a map, and want to return all entries that are within the polygonal shape.
What would be the best way to achieve this?
Also, it might be worth to point out that small errors are ok (ie. if there is an effective way to turn the polygon into a set of rectangles, then that is fine).
Use spatial extensions, most databases have this.
In MySql you can only use them with MyISAM tables which are not transactional.
http://dev.mysql.com/doc/refman/5.0/en/spatial-extensions.html
One way to quickly cut down on the number of points to consider is to compute the bounding rectangle for the polygon (i.e. just min-x, min-y, max-x, max-y of the points in the polygon), and then select for points within the bounding rectangle (i.e. where x is between min-x and max-x and same for y).
Of course not all these points are necessarily inside the polygon, but now you can hone it with code.
An old hack:
Count the number of times a line connecting <point far away> to <point in question> crosses any of the bounding segments of the polygon.
Even numbers mean the point is outside the polygon
Odd numbers mean it is inside the polygon
Related
Which of these (k-d tree, r-tree) would be suitable for searching and indexing polygon.
My usecase is that i have been given some lat-long points (min 3 for a valid polygon) and from these points i need to find the polygon which is the smallest one.
By smallest i mean that if there is a polygon inside another polygon, then the inside polygon should be returned.
And if polygon overlap, they should not be chosen.
I think finding the location and then the area might be tried but i am not sure.
I would also like get some idea about which data structure would be useful. I think postgis uses R-tree indexing.
R-tree is good for polygons, because it works on bounding boxes, including all the points for a particular polygon. You can easily find candidate polygons and then do a fine-grain check for overlap, area, etc.
Kd-tree works on points, so polygons would be hard to index.
R-tree also supports adding and removing data items. As I recall a kd-tree, once built, is hard to update for new or changing data.
Given a concave polygon, how can I determine whether a segment(edge) connecting two vertices lies within the polygon? In picture below there is an edge(red) connecting two same vertices that weren't connected in original polygon. I have no idea how determine interior and exterior. Thank you for any help.
Example of polygons
If the additional segment intersects any other segment of the polygon, it is partly inside and partly outside.
Otherwise take a point on the additional segment, for example its midpoint and check if it is inside or outside. To test if a point is inside, take any ray extending from it and count the number of intersections with polygon edges. If the number of intersections is odd, it is inside.
Sounds simple, but be prepared to handle special cases like collinear lines or intersections at vertex points. That's what will make the implementation difficult.
Say I have a 2D plane, covered with polygons (identified as an array of vertexes), analogous to:
Lets say I also have a point with coordinates on this plane, what is the easiest method to return which of the polygons the point is present in?
Although this example lists 4 polygons, it would be simple to run a check on each polygon to see if the point is within it, but I am building a system that presently has about 150 polygons, and could extend up to thousands, so doing it that way could become very slow.
So, are there any solutions to doing this that do not incur iterating through all available polygons, and checking if the point is present?
You can use a kd-tree or a r-tree. It can reduces the search space. You can also look for a quadtree. You can choose the quad size to fit the polygons and to minimize overlapping bounding boxes.
I have given the coordinates of 1000 triangles on a plane (triangle number (T0001-T1000) and its coordinates (x1,y1) (x2,y2),(x3,y3)). Now, for a given point P(x,y), I need to find a triangle which contains the point P.
One option might be to check all the triangles and find the triangle that contain P. But, I am looking for efficient solution for this problem.
You are going to have to check every triangle at some point during the execution of your program. That's obvious right? If you want to maximize the efficiency of this calculation then you are going to create some kind of cache data structure. The details of the data structure depend on your application. For example: How often do the triangles change? How often do you need to calculate where a point is?
One way to make the cache would be this: Divide your plane in to a finite grid of boxes. For each box in the grid, store a list of the triangles that might intersect with the box.
Then when you need to find out which triangles your point is inside of, you would first figure out which box it is in (this would be O(1) time because you just look at the coordinates) and then look at the triangles in the triangle list for that box.
Several different ways you could search through your triangles. I would start by eliminating impossibilities.
Find a lowest left corner for each triangle and eliminate any that lie above and/or to the right of your point. continue search with the other triangles and you should eliminate the vast majority of the original triangles.
Take what you have left and use the polar coordinate system to gather the rest of the needed information based on angles between the corners and the point (java does have some tools for this, I do not know about other languages).
Some things to look at would be convex hull (different but somewhat helpful), Bernoullies triangles, and some methods for sorting would probably be helpful.
I need to create a (large) set of spatial polygons for test purposes. Is there an algorithm that will create a randomly shaped polygon staying within a bounding envelope? I'm using OGC Simple stuff so a routine to create the well known text is the most useful, Language of choice is C# but it's not that important.
Here you can find two examples of how to generate random convex polygons. They both are in Java, but should be easy to rewrite them to C#:
Generate Polygon example from Sun
from JTS mailing list, post Minimum Area bounding box by Michael Bedward
Another possible approach based on generating set of random points and employ Delaunay tessellation.
Generally, problem of generating proper random polygons is not trivial.
Do they really need to be random, or would some real WKT do? Because if it will, just go to http://koordinates.com/ and download a few layers.
What shape is your bounding envelope ? If it's a rectangle, then generate your random polygon as a list of points within [0,1]x[0,1] and scale to the size of your rectangle.
If the envelope is not a rectangle things get a little more tricky. In this case you might get best performance simply by generating points inside the unit square and rejecting any which lie in the part of the unit square which does not scale to the bounding envelope of your choice.
HTH
Mark
Supplement
If you wanted only convex polygons you'd use one of the convex hull algorithms. Since you don't seem to want only convex polygons your suggestion of a circular sweep would work.
But you might find it simpler to sweep along a line parallel to either the x- or y-axis. Assume the x-axis.
Sort the points into x-order.
Select the leftmost (ie first) point. At the y-coordinate of this point draw an imaginary horizontal line across the unit square. Prepare to create a list of points along the boundary of the polygon above the imaginary line, and another list along the boundary below it.
Select the next point. Add it to the upper or lower boundary list as determined by it's y-coordinate.
Continue until you're out of points.
This will generate convex and non-convex polygons, but the non-convexity will be of a fairly limited form. No inlets or twists and turns.
Another Thought
To avoid edge crossings and to avoid a circular sweep after generating your random points inside the unit square you could:
Generate random points inside the unit circle in polar coordinates, ie (r, theta).
Sort the points in theta order.
Transform to cartesian coordinates.
Scale the unit circle to a bounding ellipse of your choice.
Off the top of my head, that seems to work OK