The aim of this research is to define and test a methodology for an articulated and systematic analysis of the countryside, which can lend support to urban and landscape planning processes in addition to improving knowledge of the landscape, and for the implementation of agricultural and rural development policies. We have conceived a multi-criteria and multilevel methodology that was integrated into a geographic information system (GIS) and is based on clustering and maximum likelihood classification algorithms. The proposed method focuses on various agri-environmental and socio-economic components, whose synthesis is performed by means of an interpretative key that was developed by the authors, the "Agri-Environmental Footprint", to quantify the impact of rural areas on urban systems. In particular, this paper presents the general framework of the methodology, a set of indexes that are defined for its first-level analyses, and the results of their implementation through a case study in the Emilia-Romagna Region (Italy). The method is based on the IsoCluster technique, which is associated with statistical analyses of criteria, such as the Principal Component Analysis and different data standardisation algorithms (min-max and z-score). The case study has allowed an iterative calibration of both the methodological framework and indexes.
Diti, I., Tassinari, P., Torreggiani, D., The agri-environmental footprint: A method for the identification and classification of peri-urban areas, <<JOURNAL OF ENVIRONMENTAL MANAGEMENT>>, 2015; 162 (N/A): 250-262. [doi:10.1016/j.jenvman.2015.07.058] [http://hdl.handle.net/10807/100985]
The agri-environmental footprint: A method for the identification and classification of peri-urban areas
Diti, IrenePrimo
;
2015
Abstract
The aim of this research is to define and test a methodology for an articulated and systematic analysis of the countryside, which can lend support to urban and landscape planning processes in addition to improving knowledge of the landscape, and for the implementation of agricultural and rural development policies. We have conceived a multi-criteria and multilevel methodology that was integrated into a geographic information system (GIS) and is based on clustering and maximum likelihood classification algorithms. The proposed method focuses on various agri-environmental and socio-economic components, whose synthesis is performed by means of an interpretative key that was developed by the authors, the "Agri-Environmental Footprint", to quantify the impact of rural areas on urban systems. In particular, this paper presents the general framework of the methodology, a set of indexes that are defined for its first-level analyses, and the results of their implementation through a case study in the Emilia-Romagna Region (Italy). The method is based on the IsoCluster technique, which is associated with statistical analyses of criteria, such as the Principal Component Analysis and different data standardisation algorithms (min-max and z-score). The case study has allowed an iterative calibration of both the methodological framework and indexes.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.