Olive cultivation is a very important activity which performs several important ecological functions in many inland areas. Recent progress in modelling and Decision Support Systems (DSS) applied to agriculture promises to deliver important positive changes. However, most of this progress regards agriculture systems other than olive growing, so failing to challenge the environmental dimension of the olive grove and the landscape, which is a key issue in the planning and management of olive cultivation. This paper aims to demonstrate that a new type of DSS developed upon the open-source Geospatial Cyberinfrastructure (GCI) platform (named GeOlive) can provide a very important web-based operational tool for olive growing as it better connects productivity and environmental sustainability. This GCI platform supports the acquisition, management, and processing of both static and dynamic data (e.g. pedology, daily climate), data visualization, and computer on-the-fly applications in order to perform simulation modelling (e.g. evaluation of bioclimatic indices), all potentially accessible via the Web. The DSS tool, applied to an area of 20,000 ha in southern Italy, is designed to assist olive grove planning and management and provide operational support for farmers, farmer associations and decision makers involved in olive grove landscape. DSS outputs include olive grove planning and management scenario analysis and maps, together with evaluation of potential and current plant water stress. A short selection of practical case studies is presented to show the different use cases of the proposed DSS.

A geospatial decision support system to assist olive growing at the landscape scale

Manna, Piero;Bonfante, Antonello;Basile, Angelo.
2020

Abstract

Olive cultivation is a very important activity which performs several important ecological functions in many inland areas. Recent progress in modelling and Decision Support Systems (DSS) applied to agriculture promises to deliver important positive changes. However, most of this progress regards agriculture systems other than olive growing, so failing to challenge the environmental dimension of the olive grove and the landscape, which is a key issue in the planning and management of olive cultivation. This paper aims to demonstrate that a new type of DSS developed upon the open-source Geospatial Cyberinfrastructure (GCI) platform (named GeOlive) can provide a very important web-based operational tool for olive growing as it better connects productivity and environmental sustainability. This GCI platform supports the acquisition, management, and processing of both static and dynamic data (e.g. pedology, daily climate), data visualization, and computer on-the-fly applications in order to perform simulation modelling (e.g. evaluation of bioclimatic indices), all potentially accessible via the Web. The DSS tool, applied to an area of 20,000 ha in southern Italy, is designed to assist olive grove planning and management and provide operational support for farmers, farmer associations and decision makers involved in olive grove landscape. DSS outputs include olive grove planning and management scenario analysis and maps, together with evaluation of potential and current plant water stress. A short selection of practical case studies is presented to show the different use cases of the proposed DSS.
2020
Istituto per i Sistemi Agricoli e Forestali del Mediterraneo - ISAFOM
Modelling
Olive grove
Simulation
Spatial decision support system
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/409173
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