الگوریتم ابزار-C فازی توسعه یافته برای نقاط مهم در GIS های فضایی - زمانی

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)

Usually hotspots in GIS environment are determined by using density clustering methods which have an elevated computational complexity. Indeed, in accordance to the previous our works, the usage of the EFCM method seems more successful because of its linear computational complexity and robustness to noises and outliers. It derives hotspots as hyperspheres which become circles in the case of bi-dimensional pattern data like in the case of fire point-events in the Santa Fè district (NM). Here we have studied the spatio-temporal evolution of the hotspots by partitioning the fire point-events per year in the period 2000–2006 and by comparing them for each pair of consecutives years.