The agri-environmental footprint: A method for the identification and classification of peri-urban areas

Irene Diti, Patrizia Tassinari, Daniele Torreggiani

Risultato della ricerca: Contributo in rivistaArticolo in rivista

6 Citazioni (Scopus)

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.
Lingua originaleEnglish
pagine (da-a)250-262
Numero di pagine13
RivistaJournal of Environmental Management
Volume162
DOI
Stato di pubblicazionePubblicato - 2015

Keywords

  • Agri-environmental footprint
  • Agriculture
  • Algorithms
  • Cluster Analysis
  • Cluster analysis
  • Conservation of Natural Resources
  • Countryside classification
  • Environment
  • Environmental Engineering
  • GIS model
  • Geographic Information Systems
  • Italy
  • Likelihood Functions
  • Management, Monitoring, Policy and Law
  • Peri-urban agricultural areas
  • Principal Component Analysis
  • Waste Management and Disposal

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