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.

Clay minerals from soils of a red-black soil complex developed from basaltic parent material in Sardinia are formed along a short toposequence (200 m). At the foot of the sequence, a clay-rich, black Vertisol forms, whereas at the summit, the soil is a dark reddish-brown Inceptisol. X-ray diffraction, infrared spectroscopy (FTIR), cation exchange capacity (CEC) and permanent and variable charges analyses were used, and the data show that clay minerals varied according to soil horizon and topographic position of the soil. Clay minerals in the Inceptisol are dominated by kaolinite and mixed-layer kaolinitesmectite (K-S, K:S >0.5), whereas the Vertisol contains smectites and K-S with K:S proportions <0.5. In the Vertisol, the proportion of kaolinitic layers in the K-S increases from the C horizon (K:S ∼0.35–0.40) to the Ap horizon (K:S ∼0.40–0.45). This soil clay-mineral distribution, in relation to topography, is similar to that reported for other (kaolinitic) red-black (smectitic) soil associations in subtropical and tropical areas. The sequence forms by downward drainage on summits and slopes, and buildup of ions in ‘lows’ produces smectites. Fourier transform infrared spectra indicate that two types of smectite are formed in the C horizon of the Vertisol; one is more ferric (Fe-beidellite, nontronite), the other more aluminous. Mineralogical evolution in the soil profile (from C to Ap horizon) shows a decreasing proportion of ferric smectite layers (compared to the more aluminous smectite layers). This would indicate that ferric smectite layers are preferentially transformed (or dissolved) to give kaolinite layers, with Fe precipitating as oxides and/or oxy-hydroxides or retained partly in kaolinite layers. Because the surface properties of clay minerals are related to mineralogy, the CEC (33–41 cmol kg⁻¹) in the brown Inceptisol is ∼50% pH-dependent charge while in the Vertisol up to ∼75% of the CEC (48–61 cmol kg⁻¹) comes from accessible permanent charges.