spatial-query

Does The Microsoft StCrosses() function for Geography data support Spatial Index? When I try to execute this function with Spatial Index I get this error message: "The query processor could not produce a query plan for a query with a spatial index hint. Reason: Spatial indexes do not support the method name supplied in the predicate. Try removing the index hints or removing SET FORCEPLAN" No. Indexing spatial data is nontrivial, and the class you are discussing can contain arbitrarily complex figures, not just simple geometric shapes. The specific way shapes and indexing is implemented can

I have tried various functions like MBRWithin, MBRContains, Intersects, Contains (all of them found in a plenty of posts around here) but no luck yet. This is the simplified query: SELECT * FROM users WHERE Intersects( GeomFromText( 'POINT(50 50)' ), GeomFromText( 'POLYGON(0 0, 100 0, 100 100, 0 100, 0 0)' ) ); I expected it to evaluate that condition as true (like 1=1) and return all users, however this did not happen. Please tell me, what am I doing wrong? I am running MySql 5.5 This worked for me: SELECT * FROM users WHERE MBRContains( GeomFromText('Polygon((0 0,0 100,100 100,100 0,0 0))'),

I have a list of points P=[p1,...pN] where pi=(latitudeI,longitudeI). Using Python 3, I would like to find a smallest set of clusters (disjoint subsets of P) such that every member of a cluster is within 20km of every other member in the cluster. Distance between two points is computed using the Vincenty method . To make this a little more concrete, suppose I have a set of points such as from numpy import * points = array([[33. , 41. ], [33.9693, 41.3923], [33.6074, 41.277 ], [34.4823, 41.919 ], [34.3702, 41.1424], [34.3931, 41.078 ], [34.2377, 41.0576], [34.2395, 41.0211], [34.4443, 41.3499],

I have +10k points (latitude, longitude) and I'm building an app that shows you the k nearest points to a user's location. I think this is a very common problem and I don't want to reinvent the wheel. I'm learning about Quadtrees. It seems to be a good approach to solve this spatial problem. I'm using these tools: Python 2.5 MySQL MongoDb Building the Quadtree is not that hard: http://donar.umiacs.umd.edu/quadtree/points/pointquad.html But once I've created the tree and saved it to a db (MySQL or MongoDb), how I run the query? I need to run queries like these: Find all points within 10 km of

I am fluent in SQL but new to using the SQL Geometry features. I have what is probably a very basic problem to solve, but I haven't found any good resources online that explain how to use geometry objects. (Technet is a lousy way to learn new things...) I have a collection of 2d points on a Cartesian plane, and I am trying to find all points that are within a collection of radii. I created and populated a table using syntax like: Update [Things] set [Location] = geometry::Point(@X, @Y, 0) (@X,@Y are just the x and y values, 0 is an arbitrary number shared by all objects that allows set

I have to find which points are inside a grid of square cells, given the points coordinates and the coordinates of the bounds of the cells, through two pandas dataframes. I'm calling dfc the dataframe containing the code and the boundary coordinates of the cells (I simplify the problem, in the real analysis I have a big grid with geographical points and tons of points to check): Code,minx,miny,maxx,maxy 01,0.0,0.0,2.0,2.0 02,2.0,2.0,3.0,3.0 and dfp the dataframe containing an Id and the coordinates of the points: Id,x,y 0,1.5,1.5 1,1.1,1.1 2,2.2,2.2 3,1.3,1.3 4,3.4,1.4 5,2.0,1.5 Now I would