Landscape as we perceive it is the product of many different interacting factors: macro- and topoclimate, lithology, geomorphology, land use and human activities. The evaluation of the relative influence of each one of these factors on vegetation pattern and landscape is strongly dependent from the scale of observation. Hierarchical classification (Blasi et al. 2000) makes scale-related use of these factors as diagnostic attributes: macroclimate (over 1:250,000 scale) defines landscape regions, lithology (1:250,000 scale) defines systems and lithomorphology (1:50,000 scale) defines subsystems. At a finer scale (less than 1:10,000), land forms and land-use are the predominant landscape makers and control landscape dynamics. This work investigates the influence of land forms on land-use and vegetation pattern. Sicily has been choosen as a case of study. Detailed data for an area of large extent was used to perform a fine scale, statistically significant analysis. The tridimensional model of Sicily, from which slope data is derived, has a 10 meters resolution. Land-use data used for processing is constituted by more than 125,000 polygons and the minimum spatial unit covers 2000 sq.m. The overlay of slope data and land-use data allowed to perform accurate geostatistical analysis aimed at comprehending the relationships that shape landscape. Land cover data has also been regrouped into naturalness classes to evaluate the possible link between land forms, human impact and landscape conservation. Resulting data demonstrated certain relationships between land forms and land-use. For instance, agricultural systems are all distributed within the 20 degrees slope limit; 97% of crops are concentrated within 10 degrees, due to the limit of mechanized cultivation and harvesting. Woods are distributed on steeper slopes than crops, with a small overlap range corresponding to marginal agricultural areas. The proposed modelling process produces a valuable database to perform analisys on potential natural vegetation; moreover it allows to identify marginal agricultural systems, particularly prone to potential land-use change.
|Number of pages||1|
|Publication status||Published - 2009|