Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/12990

TitleAdvanced clustering analysis for environmental indicators
Author(s)Iurgel, Ido
Santos, Maribel Yasmina
KeywordsClustering
Data mining
Environmental indicators
Space models
Issue date2009
PublisherSpringer
JournalNato Science for Peace and Security Series C-Environmental Security
Abstract(s)Maps are used in many application areas to support the visualization and analysis of geo-referenced data. The geometry used in those maps is usually associated with the administrative subdivisions of the regions, disregarding the purpose of the analysis. Another common drawback is that traditional classification methods for data analysis, used for example in Geographic Information Systems, divide the data in a pre-defined number of classes. This can lead to a situation where a class integrates values that are very different from each other and that do not allow the identification of the main differences that can exist between regions. This paper presents a different approach for geo-referenced data analysis that is based on clustering analysis. Through a clustering process it is possible to analyse a specific data set with a map, employing a Space Model, which suits the purposes of such an analysis. Space Models are new geometries of the space that are created to emphasize particularities of the analysed data.
TypeConference paper
URIhttp://hdl.handle.net/1822/12990
ISBN978-90-481-2898-3
ISSN1871-4668
Peer-Reviewedyes
AccessRestricted access (UMinho)
Appears in Collections:DSI - Engenharia da Programação e dos Sistemas Informáticos

Files in This Item:
File Description SizeFormat 
Paper_Nato_PrePrint2009.pdf
  Restricted access
Pre-Print393,06 kBAdobe PDFView/Open    Request a copy!

Partilhe no FacebookPartilhe no TwitterPartilhe no DeliciousPartilhe no LinkedInPartilhe no DiggAdicionar ao Google BookmarksPartilhe no MySpacePartilhe no Orkut
Exporte no formato BibTex mendeley Exporte no formato Endnote Adicione ao seu ORCID