Predictive soil mapping: a review

Abstract

Predictive soil mapping (PSM) can be defined as the development of a numerical or statistical model of the relationship among environmental variables and soil properties, which is then applied to a geographic data base to create a predictive map. PSM is made possible by geocomputational technologies developed over the past few decades. For example, advances in geographic information science, digital terrain modeling, remote sensing, fuzzy logic has created a tremendous potential for improvement in the way that soil maps are produced. The State Factor soil-forming model, which was introduced to the western world by one of the early Presidents of the American Association of Geographers (C.F. Marbut), forms the theoretical basis of PSM. PSM research is being driven by a need to understand the role soil plays in the biophysical and biogeochemical functioning of the planet. Much research has been published on the subject in the last 20 years (mostly outside of geographic journals) and methods have varied widely from statistical approaches (including geostatistics) to more complex methods, such as decision tree analysis, and expert systems. A geographic perspective is needed because of the inherently geographic nature of PSM.

Random Forests Applied as a Soil Spatial Predictive Model in Arid Utah

“…Both McBratney et al (2003) and Scull et al (2003) extensively reviewed digital (predictive) soil mapping studies. Scull et al (2003) generalized predictive soil mapping approaches into four categories: geostatistical methods (e.g., kriging), statistical methods (e.g., generalized linear models), decision tree analysis (e.g., classification and regression tree analysis), and expert systems (e.g., SoLIM [Shi et al, 2004]).…”

“…Typically, soils are represented on a thematic map made up of polygons representing individual map units (Soil Survey Division Staff, 1993;Scull et al, 2003;). Each map unit represents the generalized distribution of soils in the landscape as an association, complex, consociation, or as undifferentiated (Moran and Bui, 2002).…”

“…Ongoing research in digital soil mapping has demonstrated that reasonably accurate soil maps can be produced using quantitative predictive models. Digital soil mapping may also expedite soil survey (Lagacherie and Holmes, 1997;Dobos et al, 2000;Zhu, 2000;Moran and Bui, 2002;McBratney et al, 2003;Scull et al, 2003;Cole, 2004;Shi et al, 2004;Henderson et al, 2005;Saunders, 2005;Scull et al, 2005;Cole and Boettinger, 2007;Saunders and Boettinger, 2007;Brungard, 2009).…”

“…The incorporation of topographic and remotely sensed (RS) data into the study of soil systems has increased our ability to predict the spatial distribution of soils across the landscape (McBratney et al, 2003;Scull et al 2003).…”

Digital soil mapping: strategy for data pre-processing

“…Among the studies that consider the observations used in the DSM are those that seek to define the best sampling density (Moran & Bui, 2002;Scull et al, 2003;Grinand et al, 2008;Schmidt et al, 2008), although studies that are concerned with patterns of the observations within each soil class to be predicted are rare (Qi & Zhu, 2003;Qi, 2004).…”