The issues related to the appropriate planning of the territory are particularly pronounced in highly inhabited areas (urban areas), where in addition to protecting the environment, it is important to consider an anthropogenic (urban) development placed in the context of sustainable growth. This work aims at math- ematically simulating the changes in the land use, by implementing an artificial neural network (ANN) mod- el. More specifically, it will analyze how the increase of urban areas will develop and whether this development would impact on areas with particular socioeconomic and environmental value, defined as multifunctional areas. The simulation is applied to the Chianti Area, located in the province of Florence, in Italy. Chianti is an area with a unique landscape, and its territorial plan- ning requires a careful examination of the territory in which it is inserted.
|Autori:||Riccioli, Francesco; El Asmar, Toufic; El Asmar, Jean Pierre; Fagarazzi, Claudio; Casini, Leonardo|
|Titolo:||Artificial neural network for multifunctional areas|
|Anno del prodotto:||2016|
|Digital Object Identifier (DOI):||10.1007/s10661-015-5072-7|
|Appare nelle tipologie:||1.1 Articolo in rivista|