In spatial analysis buffer impact areas are called hotspots and are determined by means of density clustering methods. In a previous work, we found these hotspots in the context of a Geographic Information System (GIS) by using the Extended Fuzzy C-Means (EFCM). Here we show how the spatial distribution of the hotspots can evolve temporally and like applicational example, we present the spatial-temporal evolution in the period 2000 2006 of the fire point-events data of the Santa Fè district (NM) (downloaded from URL: www.fs.fed.us/r3/gis/sfe_gis.shtml).
The Extended Fuzzy C-Means Algorithm for hotspots in spatio-temporal GIS / Di Martino, F.; Sessa, Salvatore. - In: EXPERT SYSTEMS WITH APPLICATIONS. - ISSN 0957-4174. - 38:9(2011), pp. 11829-11836. [10.1016/j.eswa.2011.03.071]
The Extended Fuzzy C-Means Algorithm for hotspots in spatio-temporal GIS
F. Di Martino;SESSA, SALVATORE
2011
Abstract
In spatial analysis buffer impact areas are called hotspots and are determined by means of density clustering methods. In a previous work, we found these hotspots in the context of a Geographic Information System (GIS) by using the Extended Fuzzy C-Means (EFCM). Here we show how the spatial distribution of the hotspots can evolve temporally and like applicational example, we present the spatial-temporal evolution in the period 2000 2006 of the fire point-events data of the Santa Fè district (NM) (downloaded from URL: www.fs.fed.us/r3/gis/sfe_gis.shtml).I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
