Environmental Variables in Predictive Soil Mapping

Abstract

In the well-known conceptual model SCORPAN, given soil property is considered as dependent on the following environmental factors: soil, climate, organisms, topography, time and space. Predictive mapping of soils in digital soil mapping is based on similar ideas, but environmental factors may include not only factors of soils formation, but also, for example, remote sensing data, and have found a wide distribution not only in soil science, but also in ecology, agriculture and geomorphology. This paper provides a review of environmental factors that are used in predictive mapping with a special attention to situations when wide sets of environmental factors may be used and a part of them is not quantitative, such as vegetation types. Most developed are systems of quantitative variables for topography and climate description, so that a special attention is paid to them. Land surface description is performed using both local and non-local variables that need integration. In climate description variables are essential that estimate dry or wet terrain features, such as moisture ratio or water deficit. They need evaluation of potential evapotranspiration that is not measured by meteo-stations, but may be calculated. Possibilities of accounting these and other environmental factors including non-quantitative ones in quantitative statistical models of predictive mapping are described together with principles of their construction, verification, comparison, choice of appropriate models. Examples of soil predictive mapping applications are given for various scales, their specifics for different scales is outlined. Some aspects of remote sensing data usage are discussed.