Assessing the economic marginality of agricultural lands in Italy to support land use planning. (July 2018)

• Record Type: Journal Article
• Authors: Sallustio, Lorenzo; Pettenella, Davide; Merlini, Paolo; Romano, Raoul; Salvati, Luca; Marchetti, Marco; Corona, Piermaria
• Is Part Of: Land use policy. Volume 76(2018)
• Page Start: 526
• Page End: 534
• Publication Date: 2018-07
• Subjects: Land values -- Farmland profitability -- Land abandonment -- Economic marginality; Land use -- Periodicals; Land use -- Government policy -- Periodicals; Sol, Utilisation du -- Périodiques; Sol, Utilisation du -- Politique gouvernementale -- Périodiques; Electronic journals; 333.7305
• DOI: 10.1016/j.landusepol.2018.02.033
• Languages: English
• ISSNs: 0264-8377

Abstract

Highlights: We evaluated the degree of economic marginality of agricultural land in Italy. Marginal land was identified using a spatial analysis of farmland profitability. 39% of the agricultural land in Italy can be considered as marginal. Such spatially-explicit information is fundamental to support future green growth. Abstract: Agricultural marginality is a multifaceted issue, being related to place-specific socioeconomic contexts and highly-variable technological conditions. The coexistence of different classification systems of these variables makes hard any attempt to have a general definition of agricultural marginality. Moreover, the spatially explicit identification of marginal lands is still challenging mostly due to the lack of reliable data sources at both country and regional scale. Accordingly, this paper evaluates the degree of economic marginality of agricultural land, using Italy as a representative case study for southern Europe. A spatial analysis of farmland profitability and constraints for agricultural activities (topography and biodiversity conservation) is proposed to identify three classes of agricultural land, namely 'unsuitable', 'supramarginal' and 'marginal' lands. Results show that almost 39% of agricultural land in Italy can be classified as 'marginal'; its spatial distribution and characteristics are also analyzed and discussed in relation to different background conditions. The proposed approach provides a valuable methodology supporting land-use planning and decision-making under restricted geo-spatial data availability.