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.

Artificial neural network for multifunctional areas

RICCIOLI, FRANCESCO
;
2016

Abstract

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.
Riccioli, Francesco; EL ASMAR, Toufic; El Asmar, Jean Pierre; Fagarazzi, Claudio; Casini, Leonardo
File in questo prodotto:
File Dimensione Formato  
55 LCM_Chianti.pdf

solo utenti autorizzati

Tipologia: Versione finale editoriale
Licenza: NON PUBBLICO - Accesso privato/ristretto
Dimensione 2.28 MB
Formato Adobe PDF
2.28 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
08_LCM.pdf

accesso aperto

Tipologia: Documento in Post-print
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 437.78 kB
Formato Adobe PDF
437.78 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11568/936763
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 17
  • ???jsp.display-item.citation.isi??? 15
social impact