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Name: Spatial Clustering in Python
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Author(s):	Shane Grigsby
Location	Poster-4	10
Date	mar Sun 17	Days Raw Files
Start	09:17	First Raw Start	09:51
Duration	00:05:00	Offset	0:34:26
End	09:22	Last Raw End	09:53
Chapters	00:00 0:04:32
Total cuts_time	5 min.

https://us.pycon.org/2013/schedule/presentation/199/
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assets release.pdf Spatial_Clustering_in_Python.json
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Description:	Density-based clustering allows the identification of objects from unstructured data. The DBSCAN and OPTICS algorithms allow clustering and classification of remotely-sensed points into objects; however, current implementations have been unable to handle the data volume produced by LiDAR (Light Detection And Ranging). Using modified kd-trees as a spatial index allows for increased scalability. markdown
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