Introduction
Gather information about Land Cover (LC) changes is fundamental for a better understanding
the relationships and interactions between humans and the natural environment. Remote
sensing (RS) data have been one of the most important data sources for studies of LC
spatial and temporal changes. In fact, multi-temporal RS datasets, opportunely processed
and elaborated, allow to map and identify landscape changes, giving an effective effort to
sustainable landscape planning and management [Dewan et al., 2009]. In particular, by
means of the integration of RS and GIS techniques, it is possible to analyse and to classify
the changing pattern of LC during a long time period and, as a result, to understand the
changes within the area of interest.
As a matter of fact, GIS techniques are efficiently exploited to analyse the effects of various
factors on LC changes: those factors include population density, terrain slope, proximity
to roads, and surrounding land use. The availability of time-series dataset is essential to