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Nowadays there is an increasing effort for raising global awareness for the importance of soils to ensure food security, to improve agricultural and environmental planning and monitoring, and to establish effective and sustainable land management policies to counteract soil degradation. This study presents the INFOSOLO legacy database as the first effort to develop a soil information system in Portugal, suitable to compile soil data produced in the country, and to support stakeholders and land managers in decision-making. The database currently includes soil data from a set of 9934 horizons/layers studied in 3461 soil profiles across the country between 1966 and 2014. Data was extracted from scattered soil surveys, research projects, and academic studies carried out by public Portuguese and other European institutions, with a series of validation tests and harmonization procedures being implemented in order to access and improve the quality of the data. The importance of the INFOSOLO legacy dataset was discussed and exemplified with the analysis of the spatial and temporal distribution of selected soil properties, namely the organic carbon content, pH, and cation exchange capacity. For these properties, 1 km grid maps were also developed for the topsoil horizons/layers in Portugal using different spatial modelling approaches. To highlight the importance of using INFOSOLO for soil characterization, the EU-wide soil database LUCAS was used to compare both datasets in terms of data distributions, spatial continuity and accuracy of modelling outputs. The comparison also included the digital soil maps provided by the SoilGrids product for Portugal. The comparison results highlighted specific areas in the country for which INFOSOLO is capable to deliver accurate but also more reliable predictions when compared with the LUCAS and SoilGrids results. Thus, INFOSOLO provides the basis for improving soil information in the country and for raising national awareness of the importance of soil resources to the country's development. [ABSTRACT FROM AUTHOR]

Abstract: Soil data acquisition and assessment are crucial phases in the evaluation of soil degradation scenarios. To overcome the lack of field data, flexible sampling approaches can be used to complement conventional soil sampling. For the assessment of soil quality, it is necessary to integrate different soil support data and to provide a coherent spatial characterization of soil properties. This study proposes a new model to combine soil data from two different supports: “point” data, which refers to the concentration measured in the topsoil layer, and “bulk” data, which refers to the concentration measured for the whole soil depth sampled. The method developed uses a geostatistical co-simulation algorithm based on the experimental bi-distribution between both types of soil supports to compute co-simulated values. This new approach was applied to assess Soil Organic Carbon (SOC) availability in the topsoil. The results were used to identify critical areas in the Left Margin of the Guadiana River; an area in the South of Portugal with a high susceptibility to desertification. [ABSTRACT FROM AUTHOR]