Difference between revisions of "Point Clustering"
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Please fill this in with any approaches that you have tried for Point Clustering along with code snippets. Please include discussion on why a particular method worked well or didn't work well and what circumstances it may be good for. | Please fill this in with any approaches that you have tried for Point Clustering along with code snippets. Please include discussion on why a particular method worked well or didn't work well and what circumstances it may be good for. | ||
| − | === Possible Approaches | + | === Possible Approaches === |
* Coordinate interleaving (i.e. 1. rounding input coordinates, 2. grouping/aggregating them, and then 3. averaging their original coordinates so that the cluster position is at the weighted coordinate of all input geometries). | * Coordinate interleaving (i.e. 1. rounding input coordinates, 2. grouping/aggregating them, and then 3. averaging their original coordinates so that the cluster position is at the weighted coordinate of all input geometries). | ||
* K-means Clustering | * K-means Clustering | ||
* Hierarchical Clustering | * Hierarchical Clustering | ||
* Distance calculation for each coordinate pair | * Distance calculation for each coordinate pair | ||
| + | |||
| + | === Input Parameters === | ||
| + | Depending on algorithm... | ||
| + | |||
| + | Partitioning methods | ||
| + | * Map grid width ("quare / manhattan world", see coordinate interleaving/rounding) | ||
| + | * Some self-correlation threshold (see e.g. k-means) | ||
| + | * Predefined irregular polygons (e.g. zip code boundaries) | ||
=== Implementations === | === Implementations === | ||
| Line 14: | Line 22: | ||
=== References === | === References === | ||
* [http://en.wikipedia.org/wiki/Data_clustering Wikipedia] Article on Data Clustering | * [http://en.wikipedia.org/wiki/Data_clustering Wikipedia] Article on Data Clustering | ||
| − | * [http:// | + | * [http://bonsai.ims.u-tokyo.ac.jp/~mdehoon/software/cluster/software.htm#pycluster PyCluster]: Python Cluster Functions (2013) |
| − | * [http://trac.osgeo.org/postgis/ticket/174 Point Clustering Utility Trigger] enhancement idea reported as ticket to PostGIS Trac. | + | * [http://trac.osgeo.org/postgis/ticket/174 Point Clustering Utility Trigger] enhancement idea reported as ticket to PostGIS Trac (2012). |
| − | * [http:// | + | * [http://gis.stackexchange.com/questions/11567/spatial-clustering-with-postgis "Spatial Clustering with PostGIS] from gis.stackexchange.com (2011) |
| − | + | * [http://www.geocomputation.org/2000/GC015/Gc015.htm Using Genetic Algorithms in Clustering Problems]: paper from [http://www.geocomputation.org/ GeoComputation] 2000 conference (2000) | |
| − | * [http://www.geocomputation.org/2000/GC015/Gc015.htm Using Genetic Algorithms in Clustering Problems]: paper from [http://www.geocomputation.org/ GeoComputation] 2000 conference | + | * [http://www.geocomputation.org/2000/GC024/Gc024.htm Automatic clustering via boundary extraction for mining massive point-data sets]: paper from [http://www.geocomputation.org/ GeoComputation] 2000 conference (2000) |
| − | * [http://www.geocomputation.org/2000/GC024/Gc024.htm Automatic clustering via boundary extraction for mining massive point-data sets]: paper from [http://www.geocomputation.org/ GeoComputation] 2000 conference | + | * <s>[http://www.nabble.com/%27clustering%27-of-points-t1261780.html#a3347923 PostGIS Mailing List] thread on clustering points</s> |
| + | * <s>[http://www.nabble.com/clustering-points-t1404935.html#a3781371 Here] & [http://www.nabble.com/Visualizing-Point-Data-t1052056.html#a2741608 here]: Mapserver Mailing List threads on clustering points</s> | ||
Latest revision as of 15:16, 12 October 2014
Point Clustering: Various Approaches
Please fill this in with any approaches that you have tried for Point Clustering along with code snippets. Please include discussion on why a particular method worked well or didn't work well and what circumstances it may be good for.
Possible Approaches
- Coordinate interleaving (i.e. 1. rounding input coordinates, 2. grouping/aggregating them, and then 3. averaging their original coordinates so that the cluster position is at the weighted coordinate of all input geometries).
- K-means Clustering
- Hierarchical Clustering
- Distance calculation for each coordinate pair
Input Parameters
Depending on algorithm...
Partitioning methods
- Map grid width ("quare / manhattan world", see coordinate interleaving/rounding)
- Some self-correlation threshold (see e.g. k-means)
- Predefined irregular polygons (e.g. zip code boundaries)
Implementations
References
- Wikipedia Article on Data Clustering
- PyCluster: Python Cluster Functions (2013)
- Point Clustering Utility Trigger enhancement idea reported as ticket to PostGIS Trac (2012).
- "Spatial Clustering with PostGIS from gis.stackexchange.com (2011)
- Using Genetic Algorithms in Clustering Problems: paper from GeoComputation 2000 conference (2000)
- Automatic clustering via boundary extraction for mining massive point-data sets: paper from GeoComputation 2000 conference (2000)
PostGIS Mailing List thread on clustering pointsHere & here: Mapserver Mailing List threads on clustering points