A soil map (1:50,000 scale) was recently produced in Sardinia (Italy) using a cost-effective GIS approach. In this study we aimed to verify, in two pilot areas and by means of statistical analysis, the effectiveness of the adopted methodology in representing and predicting the spatial distribution of soil types and properties. We focused on evaluation of 1) the influence of landforms and parent materials on soil types (WRB Reference Soil Groups) and selected soil properties and 2) the suitability of the adopted methodology for calibrating a model to predict land unit composition in terms of different soil types.

Leptosols, Regosols and Cambisols were prevalent on slopes, with Leptosols being more frequent on convex slopes and Regosols and Cambisols on concave slopes. In flat areas, soil types mainly depended on the type and age of parent material, with Regosols and Cambisols prevailing on Holocene deposits and highly developed soils (mainly Luvisols) largely prevailing on Pleistocene deposits. On hard rock, Leptosols were very frequent on terrigenous metamorphic rock and frequent on granite. Besides Leptosols, Regosols occurred more frequently than Cambisols on both parent materials. Landforms strongly influenced soil depth and available water capacity. Soils on plains were deeper than those on slopes, where convex forms had shallower soils than concave forms. A similar trend applied to the available water capacity. The parent material had a significant effect on topsoil properties (thickness, texture, pH and organic carbon content) of soils belonging to the same WRB Reference Soil Group (analysis done on the most relevant WRB Reference Soil Groups, i.e. Leptosols, Regosols and Cambisols).

We calibrated and tested stepwise multiple linear regressions (MLR) and general linear models (GLM) to predict the composition of map units in terms of different WRB Reference Soil Groups. The two models gave very similar results, with distinct distribution patterns that were coherent with the relationships observed between soil groups and specific combination of terrain attributes and parent materials. Results showed that both models were more reliable in predicting the absence rather than presence of a given soil type.

最近，撒丁岛（意大利）采用了具有成本效益的GIS方法制作了土壤图（比例为1：50,000）。在这项研究中，我们旨在通过统计分析在两个试验区域中验证所采用方法在表示和预测土壤类型和特性的空间分布方面的有效性。我们着重评估以下方面：1）地形和母体材料对土壤类型（WRB参考土壤组）和所选土壤特性的影响，以及2）所采用方法的校正模型的适用性，该模型可根据不同土壤来预测土地单元组成类型。

斜坡上有上白垩统，雷戈溶胶和坎比索尔，而在凸面斜坡上有上白垩统和凹凹斜坡上的Regosol和Cambisol更为常见。在平坦地区，土壤类型主要取决于母体材料的类型和年龄，其中全新世沉积物中主要有雷哥溶胶和坎比索尔，而更新世沉积物中则主要是高度发达的土壤（主要是Luvisols）。在坚硬的岩石上，陆栖变质岩上的细小溶胶很常见，而在花岗岩上则很常见。在两种母体材料中，除钩端草酚外，雷哥sol尔的发生率均高于坎比索尔。地形强烈影响土壤深度和可用水量。平原上的土壤比斜坡上的土壤更深，在斜坡上，凸形的土壤比凹形的浅。可用水量也有类似趋势。

我们对逐步多元线性回归（MLR）和常规线性模型（GLM）进行了校准和测试，以根据不同的WRB参考土壤组预测地图单元的组成。这两个模型给出了非常相似的结果，具有不同的分布模式，这些分布模式与在土壤组与地形属性和母体材料的特定组合之间观察到的关系一致。结果表明，两种模型在预测给定土壤类型的缺席情况而非存在某种土壤类型方面均更为可靠。