geospatial

+---------+---------+------+-----+---------+----------------+ | Field | Type | Null | Key | Default | Extra | +---------+---------+------+-----+---------+----------------+ | id | int(11) | NO | PRI | NULL | auto_increment | | user_id | int(11) | NO | UNI | NULL | | | utm | point | NO | MUL | NULL | | +---------+---------+------+-----+---------+----------------+ insert into life(user_id, utm) values(99,point(4,4)); ERROR 1416 (22003): Cannot get geometry object from data you send to the GEOMETRY field Have you tried: insert into life(user_id, utm) values(99,PointFromWKB(POINT(4,4))); 来源： https:

I have implemented a simple Dijkstra's algorithm for finding the shortest path on an .osm map with Java. The pathfinding in a graph which is created from an .osm file works pretty well. But in case the user's current location and/or destination is not a node of this graph (just raw coordinates) how do we 'link' those coordinates to the graph to make pathfinding work? The simple straightforward solution "find the nearest to the current location node and draw a straight line" doesn't seem to be realistic. What if we have a situation like on the attached picture? (UPD) The problem here is that

Using O'Reilly's Data Mashups in R as inspiration, I'm trying to plot a handful of addresses on a shapefile of Salt Lake County, Utah found here . I have data frame geoTable: > geoTable address Y X EID 1 130 E 300 S 40.76271 -111.8872 1 2 875 E 900 S 40.74992 -111.8660 2 3 2200 S 700 E 40.72298 -111.8714 3 4 702 E 100 S 40.76705 -111.8707 4 5 177 East 200 S 40.76518 -111.8859 5 6 702 3rd ave 40.77264 -111.8683 6 7 2175 S 900 E 40.72372 -111.8652 7 8 803 E 2100 S 40.72556 -111.8680 8 And I've coerced it into an eventData object: > addressEvents<-as.EventData(geoTable,projection=NA) >

I have a table with a POINT geometry field. I enter latitude/longitude points into it like this: INSERT INTO table( point ) VALUES( POINT( lon_value, lat_value ); Sometimes I do not have lat/lon values to enter. I am unable to enter a blank, a NULL, or an empty POINT() ... since POINT(0,0) is actually a location on the globe, that won't work either. What is the solution here? I would use coordinates of North Pole INSERT INTO table( point ) VALUES( POINT(0.0000,90.0000); If the actual coordinates of the pole may be an issue i would change the lon value from 0.0000. 来源： https://stackoverflow.com

I have a basic geospatial query working well in MongoDB. It seems that it should be easy to apply $not to get the complement... but it's not working for me. Is it simple user error? Or can MongoDB not handle this query conceptually? I could not find any such limitation in the documentation . Working query (correctly finds the 2 cities within 10 miles of the center): db.customers.find({ "location" : { $within : { $center : [[-117.15,32.72],0.15] } } }) Attempted complement query (desired result is the 1 city that is not within 10 miles): db.customers.find({ "location" : { $not : { $within : {

I need to sort a coordinate list for a rectangle counterclockwise, and make the north-east corner the first coordinate. These are geographic coordinates (i.e. Longitude, Latitude) in decimal form. 1 For example, here are the 4 corners of a rectangle, starting with the north-west corner and moving clockwise: [ { "lat": 34.495239, "lng": -118.127747 }, # north-west { "lat": 34.495239, "lng": -117.147217 }, # north-east { "lat": 34.095174, "lng": -117.147217 }, # south-east { "lat": 34.095174, "lng": -118.127747 } # south-west ] I need to sort these counterclockwise and change the "anchor"

Since Cassandra is based off of the Dynamo paper (distributed, self-balancing hash table) + BigTable and there are spatial indexes that would fit nicely into that paradigm ( quadkey or geohash ). Is there a reason that Geospatial support hasn't been implemented? You could add a GeoPoint datatype as a tuple with an internal geohash and specify a CF as containing geo data. From there you can choose the behavior as having the geo data being a secondary index, or a denormalized SCF. That could lay the ground work for geospatial development and you could start by implementing some low hanging fruit