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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.

Today it is evident that there are many contrasting demands on our landscape (e.g. food security, more sustainable agriculture, higher income in rural areas, etc.) as well as many land degradation problems. It has been proved that providing operational answers to these demands and problems is extremely difficult. Here we aim to demonstrate that a spatial decision support system based on geospatial cyberinfrastructure (GCI) can address all of the above, so producing a smart system for supporting decision making for agriculture, forestry, and urban planning with respect to the landscape. In this paper, we discuss methods and results of a special kind of GCI architecture, one that is highly focused on land management and soil conservation. The system allows us to obtain dynamic, multidisciplinary, multiscale, and multifunctional answers to agriculture, forestry, and urban planning issues through the Web. The system has been applied to and tested in an area of about 20 000 ha in the south of Italy, within the framework of a European LIFE+ project (SOILCONSWEB). The paper reports – as a case study – results from two different applications dealing with agriculture (olive growth tool) and environmental protection (soil capability to protect groundwater). Developed with the help of end users, the system is starting to be adopted by local communities. The system indirectly explores a change of paradigm for soil and landscape scientists. Indeed, the potential benefit is shown of overcoming current disciplinary fragmentation over landscape issues by offering – through a smart Web-based system – truly integrated geospatial knowledge that may be directly and freely used by any end user (www.landconsultingweb.eu). This may help bridge the last very important divide between scientists working on the landscape and end users.