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.
Hotspots Detection in Spatial Analysis via the Extended Gustafson-Kessel Algorithm / Di Martino, F.; Sessa, Salvatore. - In: ADVANCES IN FUZZY SYSTEMS. - ISSN 1687-7101. - Volume 2013:2013(2013), pp. 1-7. [10.1155/2013/876073]
Hotspots Detection in Spatial Analysis via the Extended Gustafson-Kessel Algorithm
F. Di Martino;SESSA, SALVATORE
2013
Abstract
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.