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We review historical soil maps from a geographical perspective, in contrast to the more traditional temporal–historical perspective. Our geographical approach examines and compares soil maps based on their scale and classification system. To analyze the connection between scale in historical soil maps and their associated classification systems, we place soil maps into three categories of cartographic scale. We then examine how categories of cartographic scale correspond to the selection of environmental soil predictors used to initially create the maps, as reflected by the maps' legend. Previous analyses of soil mapping from the temporal perspective have concluded that soil classification systems have co-evolved with gains in soil knowledge. We conclude that paradigm shifts in soil mapping and classification can be better explained by not only their correlation to historical improvements in scientific understanding, but also by differences in purpose for mapping, and due to advancements in geographic technology. We observe that, throughout history, small cartographic scale maps have tended to emphasize climate–vegetation zonation. Medium cartographic scale maps have put more emphasis on parent material as a variable to explain soil distributions. And finally, soil maps at large cartographic scales have relied more on topography as a predictive factor. Importantly, a key characteristic of modern soil classification systems is their multi-scale approach, which incorporates these phenomena scales within their classification hierarchies. Although most modern soil classification systems are based on soil properties, the soil map remains a model, the purpose of which is to predict the spatial distributions of those properties. Hence, multi-scale classification systems still tend to be organized, at least in part, by this observed spatial hierarchy. Although the hierarchy observed in this study is generally known in pedology today, it also represents a new view on the evolution of soil science. Increased recognition of this hierarchy may also help to more holistically combine soil formation factors with soil geography and pattern, particularly in the context of digital soil mapping. [ABSTRACT FROM AUTHOR]

Abstract: Soil mapping is a major goal of soil science. Soil maps rely upon accurate base maps, both for positional reference and to provide environmental data that can assist in the prediction of soil properties. This paper reviews the historical development of base maps used for soil mapping, and evaluates the dependence of soil mapping on base maps. The availability of geographic technology for producing base maps has both constrained and directed the geographic study of soil. The lack of accurate methods for determining location limited early geographic descriptions of soils to narratives, or to listings of attributes for property-based map units. The first real base maps available for soil mapping were outline maps produced in the late 18th century, fueled by governments' interests in documenting national boundaries and popular interest in world atlases. These early soil maps primarily used outline maps as a positional reference onto which soil-related thematic detail was added. Eventually, additional spatial information, in the form of topographic maps and later aerial photographs, increased the predictive role of base maps in soil mapping. In the current digital, geospatial revolution, global positioning systems and geographic information systems have nearly replaced the positional reference function of base maps. Today, base maps are more likely to be used as parameters in soil-landscape models for predicting the spatial distribution of soil properties and classes. Formerly, as a reference for spatial position, paper base maps controlled the cartographic scale of soil maps. However, this relationship is no longer true in geographic information systems. Today, as parameters for digital soil maps, base maps constitute the library of predictive variables and constrain the supported resolution of the soil map. [Copyright &y& Elsevier]

This research analyzes the relationships between "soil" and "organisms" within the framework of the Jenny equation, a fundamental expression in soil science that is the theoretical basis for modeling the complex occurrence of soils on landscapes. This analysis is based on the interpretation of the indeterminate function "f" of the equation as "statistical dependence between categorical variables". The categories of the "soil" component of the equation have been defined as "diagnostic horizons", and those of the "organisms" factor as synthetic types of "land cover". After applying these criteria to 424 soil profiles studied in a region with an oceanic climate in northern Spain, a multiple correspondence analysis showed pedologically consistent groupings between diagnostic horizons and categories of climate, land cover, relief, and parent material factors. Subsequently, a bivariate analysis detailed pedologically consistent relationships between diagnostic horizons and land cover categories. In the context the scarcity of quantitative information on soil and forming factor relationships, this work provides criteria to statistically assess the role of land cover in such relationships. This soil forming factor is the one whose spatial representation is more generalized and detailed, hence its interest in the development of soil mapping models. [ABSTRACT FROM AUTHOR]

To cope with the challenges in forest management that are contemporarily caused by climate change, data on current chemical and physical soil properties are more and more necessary. For this purpose, we present a further amalgam of depth functions and SCORPAN modelling to provide data at arbitrary depth layers. In this concept, regionalisation is split up into the modelling of plot totals and the estimation of vertical distributions. The intended benefits by splitting up are: consistency between estimates on plot level and depth layer level, avoidance of artificial depth gradients, straightforward interpretation of covariates in the sense of pedogenetic processes, and circumnavigation of the propagation of uncertainties associated with separation between horizons during field sampling. The methodology was tailored to the circumstances within the north-eastern lowlands and the utilisation of current inventory data of the National Forest Soil Inventory (NFSI) in Brandenburg (Germany). Using the regionalisation of soil organic carbon (SOC) as an example, the application is demonstrated and discussed in detail. The depth to groundwater table and terrain parameters related to the catchment area were the main factors in SOC storage. The use of kriging did not improve the model performance. The relative depth gradients of SOC were especially distinguished by tree species composition and stand age. We suppose that interesting fields of application may be found in scenario-based modelling of SOC and when SOC serves as a basis for hydrological modelling. [ABSTRACT FROM AUTHOR]