Colour space models for soil science

Abstract

Soil colour is an important soil property. It is frequently used by soil scientists for the identification and classification of soil. It is also used as an indicator of field soil physical, chemical and biological properties as well as of the occurrence of soil processes. Measurements of soil colour are commonly made using the Munsell soil colour charts. A number of other colour space models, that overcome some of the limitations of the Munsell HVC system exist and may be used to more aptly describe soil colour. We looked at nine colour space models and a redness index: Munsell HVC, RGB, decorrelated RGB (DRGB), CIE XYZ, CIE Yxy, CIELAB, CIELUV, CIELHC, and Helmoltz chromaticity coordinates. The aims of this paper are to (i) describe the algorithms used for transformations between these colour space models, (ii) compare their representational qualities and their relationships to the Munsell soil colour system, and (iii) in a case study, determine the model best suited to describe the relationship between soil colour and soil organic carbon. The type of colour model to use will depend on the purpose. For example, if soil colour is being used for merely descriptive purposes, then the Munsell HVC system will remain appropriate; if it is being used for numerical statistical or predictive analysis, as in our case study, then colour models that use Cartesian-type coordinate systems will be more useful. Of these, the CIELUV and CIELCH models appear to be more suitable for predictions of soil organic carbon.