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Spazio rurale e Land use quality: una proposta per un sistema di indicatori a scala comunale in Italia

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Listed:
  • Luca Salvati

    (Italian National Institute of Statistics)

  • Marco Zitti

    (Cra-Cma)

  • Luigi Perini

    (Cra-Cma)

Abstract

Land degradation is a global problem which involves different climatic, soil, vegetation, agricultural and population conditions. Originally attributed to the most arid regions of the world, desertification risk has been rapidly increased also in temperate regions. In Mediterranean Europe, high human pressure, climatic changes, and the intense agricultural development combine to produce land consumption, a key factors to start desertification processes. Unfortunately, the effect of agriculture on land degradation was poorly considered as far as the agro-environmental indicators are concerned. The aim of this paper is to design a system of environmental indicators contributing to improve a simplified model of land use quality assessment especially focusing on landscape, farm management, and the impact of the agricultural practices on soil quality. Thirty-two indicators were included in a Environmentally Sensitive Area (ESA) scheme in order to define the contribution of the agriculture to land use quality in Latium, central Italy. Finally, we discussed on the use of agro-environmental indicators as a tool to quantify the agricultural impact on the environment as an original contribution to the study of land degradation.

Suggested Citation

  • Luca Salvati & Marco Zitti & Luigi Perini, 2009. "Spazio rurale e Land use quality: una proposta per un sistema di indicatori a scala comunale in Italia," Rivista di statistica ufficiale, ISTAT - Italian National Institute of Statistics - (Rome, ITALY), vol. 11(2-3), pages 101-131, January.
    • Handle: RePEc:isa:journl:v:11:y:2009:i:2-3:p:101-131
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    References listed on IDEAS

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    1. Lillard, Lee & Smith, James P & Welch, Finis, 1986. "What Do We Really Know about Wages? The Importance of Nonreporting and Census Imputation," Journal of Political Economy, University of Chicago Press, vol. 94(3), pages 489-506, June.
    2. Little, Roderick J A, 1985. "A Note about Models for Selectivity Bias," Econometrica, Econometric Society, vol. 53(6), pages 1469-1474, November.
    3. Schenker, Nathaniel & Raghunathan, Trivellore E. & Chiu, Pei-Lu & Makuc, Diane M. & Zhang, Guangyu & Cohen, Alan J., 2006. "Multiple Imputation of Missing Income Data in the National Health Interview Survey," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 924-933, September.
    4. He, Yulei & Raghunathan, Trivellore E., 2006. "Tukey's gh Distribution for Multiple Imputation," The American Statistician, American Statistical Association, vol. 60, pages 251-256, August.
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