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Progressive spatial clustering of content-based satellite imagery retrieval results

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3 Author(s)
Matt Klaric ; Center for Geospatial Intelligence, University of Missouri-Columbia, USA ; Grant Scott ; Chi-Ren Shyu

The ProgressiveDBSCAN algorithm allows for the progressive clustering of results from a geospatial information retrieval system. Results can be clustered by a combination of both their spatial and non-spatial attributes. The benefit of this clustering is that users are able to sort through the results returned from a geospatial information retrieval system in a spatial context. No longer are results from disparate locations presented to the user, but instead compact spatial clusters are displayed. There is a 98% reduction in the spatial distance between consecutive CBIR results and the spatial distance between the compact clusters; this leads to more efficient analysis of results by reducing the amount of time users spend context switching while on average only adding a few seconds to the query time.

Published in:

Geoscience and Remote Sensing Symposium (IGARSS), 2010 IEEE International

Date of Conference:

25-30 July 2010