New Technique for Monitoring High Nature Value Farmland (HNVF) in Basilicata

Costanza Fiorentino (), Paola D’Antonio, Francesco Toscano, Angelo Donvito and Felice Modugno
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Costanza Fiorentino: School of Agricultural, Forestry, Environmental and Food Sciences, University of Basilicata, 85100 Potenza, Italy
Paola D’Antonio: School of Agricultural, Forestry, Environmental and Food Sciences, University of Basilicata, 85100 Potenza, Italy
Francesco Toscano: School of Agricultural, Forestry, Environmental and Food Sciences, University of Basilicata, 85100 Potenza, Italy
Angelo Donvito: DIGIMAT S.P.A., 75100 Matera, Italy
Felice Modugno: School of Agricultural, Forestry, Environmental and Food Sciences, University of Basilicata, 85100 Potenza, Italy

Sustainability, 2023, vol. 15, issue 10, 1-13

Abstract: The definition of High Nature Value Farmland Areas (HNVF) was provided by Andersen in 2003: “HNVF comprises those areas in Europe where agriculture is the major (usually the dominant) land use and where that agriculture supports or is associated with either a high species and habitat diversity, or the presence of species of European conservation concern or both”. The present work focuses on an overview of the techniques used to produce HNVF maps at different spatio-temporal resolutions. The proposed approach is based on the statistical approach. The study area is the Basilicata region (southern Italy) in 2012, mapped at municipal spatial resolution. The HNVF areas were identified by applying a threshold to the sum of the contributions of the main characterizing indicators. Three indicators contribute to the calculation of the HNVF areas: crop variability (CD Index), extensive practices (EP Index), and the presence of natural elements (Index Ne). Good agreement was found between our HNVF map and the results of the literature, although the analysis approaches were different. The main advantages of the proposed methodology derive from only free input data being used, and include remote sensing images and the adaptability to different spatial resolutions (local, regional, and national).

Keywords: biodiversity; sustainability; MODIS; GIS; bioeconomic; big-data (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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