G. Metternicht1, J. Goetting2

1 - Department of Spatial Sciences, Curtin University of Technology, Perth, Australia

2 - University of Applied Science Munich, Germany


Most soil classification systems use, to a greater or lesser extent, soil textural composition as a basic component. Aspects of soil texture such as the relative percentages of sand, silt and clay are one of the many keys used to define taxonomic groupings for soils. National soil mapping organisations often use different soil taxonomic classification systems such as the USDA Soil Taxonomy, FAO system, Canadian Soil Taxonomy, French Soil Reference System or the Australian Soil Classification Scheme. While the bases for the taxonomic classification of soils are well documented, there is a lack of standards for the graphic visualisation of soil information in maps, whether hardcopy or digital.


Cartographic visualisation of soil types should be independent of the taxonomic classification system used, where soil names frequently adopt names of local places which are meaningful of the associated soils characteristics to a handful of trained soil scientists (e.g. Cambisols, Entisols, Avon soil series, Beverley soil series). Therefore, this paper extends on the proposition of Metternicht and Stott (2003) of using a triangular spectral encoding system to colour-code soil maps based on a linear relationship to the percentage of sand, clay and silt present in the soils (e.g. its textural composition). In this paper we incorporate a further development within Macromedia FreeHand which enables visualisation of other soil components such as rock fragment type and abundance, an important factor influencing land use and land management decisions.


With the increasing availability of spatial soil databases, a consistent approach for the representation of these data would greatly simplify the interpretation of soil maps, facilitating information exchange between different organisations and scientists. By using a spectral encoding where colours convey information regarding soil texture, based on the textural classes of the FAO soil textural triangle, a standard representation of soil mapping, independent of the soil taxonomic classification chosen, could be produced. Furthermore, a colour classification is developed for organic soils, based on field photographs of characteristic soil profiles. This graphic visualisation tool has the advantage of providing a simplified visual representation of soil types across the world. For instance a sandy clay soil of Australia (which can be called Avon soil series) will adopt the same colour as a sandy clay soil of Africa (e.g. that can be called Pretoria soil series) or Argentina, with an indication of rock fragment type and abundance within the soil matrix, if applicable.


Unlike previous studies adopting additive primary colours for spectral encoding and graphic visualisation of soil textural properties, the proposed scheme is based in the CYMK subtractive colour system. The reason for this selection is based on the fact that colours based on a RGB model do not reproduce faithfully when printed (e.g. what you see on screen is not what you get). It is well known that the most common method used by cartographers for disseminating multiple copies of paper maps is the four-colour process printing in which four colour separations are used. Three of these separations are based on the subtractive primaries (cyan, magenta, yellow), while the fourth is black. For this reason, our prototype is based on the use of subtractive primary colours, which do not vary so greatly between digital and analogue products.


The paper describes the approach adopted to estimate the percentage of YMC colours needed for characterising the polygons of the FAO soil textural triangle, as well as the matrix created for a user friendly selection of rock fragment types (e.g. gravel, stones and boulders) and percentage abundance within the soil matrix. This information is usually contained in soil survey reports as it constitutes an important factor to consider in land capability analysis. Graphic visualisations of soil maps at different scales are presented (e.g. world soil maps, regional and local soil maps) to show the adaptability of this approach to different levels of soil information.