Hotspots Detection in Spatial Analysis via the Extended Gustafson-Kessel Algorithm | Zendy

Ferdinando Di Martino | Zendy; Salvatore Sessa | Zendy

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Hotspots Detection in Spatial Analysis via the Extended Gustafson-Kessel Algorithm

Author(s) -

Ferdinando Di Martino,

Salvatore Sessa

Publication year - 2013

Publication title -

advances in fuzzy systems

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.38

H-Index - 19

eISSN - 1687-711X

pISSN - 1687-7101

DOI - 10.1155/2013/876073

Subject(s) - hotspot (geology) , georeference , ellipse , centroid , cluster analysis , geography , cluster (spacecraft) , computer science , cartography , algorithm , data mining , geology , artificial intelligence , mathematics , physical geography , geometry , geophysics , programming language

We show a new approach for detecting hotspots in spatial analysis based on the extended Gustafson-Kessel clustering method encapsulated in a Geographic Information System (GIS) tool. This algorithm gives (in the bidimensional case) ellipses as cluster prototypes to be considered as hotspots on the geographic map and we study their spatiotemporal evolution. The data consist of georeferenced patterns corresponding to positions of Taliban’s attacks against civilians and soldiers in Afghanistan that happened during the period 2004–2010. We analyze the formation through time of new hotspots, the movement of the related centroids, the variation of the surface covered, the inclination angle, and the eccentricity of each hotspot

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