The agri-environmental footprint: A method for the identification and classification of peri-urban areas.
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 devel...
| Publicado en: | Journal of Environmental Management Vol. 162; pp. 250 - 263 |
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| Autores principales: | , , |
| Formato: | Artículo |
| Publicado: |
Academic Press Inc.
Oct2015
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=109044696&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 109044696 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 03014797 EMJ jtl: Journal of Environmental Management issn: 03014797 maglogo: N pubinfo: dt: Oct2015 vid: 162 pid: 735 pub: Academic Press Inc. artinfo: ui: 109044696 10.1016/j.jenvman.2015.07.058 ppf: 250 ppct: 13 formats: tig: atl: The agri-environmental footprint: A method for the identification and classification of peri-urban areas. aug: au: Diti, Irene Tassinari, Patrizia Torreggiani, Daniele affil: University of Bologna, Department of Agricultural Sciences, Viale Giuseppe Fanin 48, 40127 Bologna, Italy su: Metropolitan areas Socioeconomics Environmental management Geographic information systems Cluster analysis (Statistics) sug: subj: Metropolitan areas Socioeconomics Environmental management Geographic information systems Cluster analysis (Statistics) keyword: Agri-environmental footprint Cluster analysis Countryside classification GIS model Peri-urban agricultural areas Agri-environmental footprint Cluster analysis Countryside classification GIS model Peri-urban agricultural areas ab: 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. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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