The concepts of soil quality and soil health are widely used as soils receive more attention in the worldwide policy arena. So far, however, the distinction between the two concepts is unclear, and operational procedures for measurement are still being developed. A proposal is made to focus soil health on actual soil conditions, as determined by a limited set of indicators that reflect favourable rooting conditions. In addition, soil quality can express inherent soil conditions in a given soil type (genoform), reflecting the effects of past and present soil management (expressed by various phenoforms). Soils contribute to ecosystem services that, in turn, contribute to the UN Sustainable Development Goals (SDGs) and, more recently, to the EU Green Deal. Relevant soil ecosystem services are biomass production (SDG 2 – zero hunger), providing clean water (SDG 6), climate mitigation by carbon capture and reduction of greenhouse gas emissions (SDG 13 – climate action), and biodiversity preservation (SDG 15 – life on land). The use of simulation models for the soil–water–atmosphere–plant system is proposed as a quantitative and reproducible procedure to derive single values for soil health and soil quality for current and future climate conditions. Crop production parameters from the international yield gap programme are used in combination with soil-specific parameters expressing the effects of phenoforms. These procedures focus on the ecosystem service, namely biomass production. Other ecosystem services are determined by soil-specific management and are to be based on experiences obtained in similar soils elsewhere or by new research. A case study, covering three Italian soil series, illustrates the application of the proposed concepts, showing that soil types (soil series) acted significantly differently to the effects of management and also in terms of their reaction to climate change.

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.