Mediterranean agricultural areas of Italy, beyond hosting an extraordinary wealth of biodiversity, are the source of income for a large population that often lives below the average economic conditions of the advanced regions of Europe. In these areas, the semiarid climates and the impact of climate change, the extreme fragmentation of productive areas, the low carbon content of soils, contribute to lead to an increasingly low profitability of agricultural areas. This combination of drivers results in land abandonment phenomena and in a consequent increased hydrogeological risk due mainly to lack of land maintenance. Estimating the productivity of these agricultural areas represents a key information to help land planners and public bodies to tailor ad hoc measures able to increase productivity, maintain ecosystem services, and reduce potential migration fluxes. In this work, the adopted procedure involves the use of GIS-based geospatial information related to climate and vegetation, which includes both direct observational data (temperature, rainfall, productivity, etc.) and a spectral index derived from multispectral satellite data (Sentinel-2). For the climatic component, we exploited a database of daily temperature and rainfall data (2000–2020) acquired by the agrometeorological network of ALSIA (Agency for Development and Innovation in Agriculture of Basilicata) to produce a bioclimatic index able to classify the study areas in different climatic zones. We tested this procedure in a specialized agricultural district of Basilicata (Southern Italy): the Metapontum Plain which plays a central role in the economy of the region. © 2024 Elsevier Inc. All rights reserved.

Development of algorithms based on the integration of vegetation indices and meteorological data for the identification of low productivity agricultural areas

Lanfredi M.;Coluzzi R.;D'Emilio M.;Imbrenda V.;Pace L.;Samela C.;Simoniello T.;
2024

Abstract

Mediterranean agricultural areas of Italy, beyond hosting an extraordinary wealth of biodiversity, are the source of income for a large population that often lives below the average economic conditions of the advanced regions of Europe. In these areas, the semiarid climates and the impact of climate change, the extreme fragmentation of productive areas, the low carbon content of soils, contribute to lead to an increasingly low profitability of agricultural areas. This combination of drivers results in land abandonment phenomena and in a consequent increased hydrogeological risk due mainly to lack of land maintenance. Estimating the productivity of these agricultural areas represents a key information to help land planners and public bodies to tailor ad hoc measures able to increase productivity, maintain ecosystem services, and reduce potential migration fluxes. In this work, the adopted procedure involves the use of GIS-based geospatial information related to climate and vegetation, which includes both direct observational data (temperature, rainfall, productivity, etc.) and a spectral index derived from multispectral satellite data (Sentinel-2). For the climatic component, we exploited a database of daily temperature and rainfall data (2000–2020) acquired by the agrometeorological network of ALSIA (Agency for Development and Innovation in Agriculture of Basilicata) to produce a bioclimatic index able to classify the study areas in different climatic zones. We tested this procedure in a specialized agricultural district of Basilicata (Southern Italy): the Metapontum Plain which plays a central role in the economy of the region. © 2024 Elsevier Inc. All rights reserved.
2024
Istituto di Metodologie per l'Analisi Ambientale - IMAA
978-0-443-13605-4
Aridity index; Land degradation; Mediterranean areas; Rainfall; Sentinel-2
File in questo prodotto:
File Dimensione Formato  
Chalkias_Petrouplulos_capitolo_IMAA.pdf

solo utenti autorizzati

Tipologia: Versione Editoriale (PDF)
Licenza: NON PUBBLICO - Accesso privato/ristretto
Dimensione 388.04 kB
Formato Adobe PDF
388.04 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/516726
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? ND
social impact