Abstract
In Brazil, soil surveys in more detailed scale are still scarce and necessary to more adequately support the decision makers for planning soil and environment activities in small areas. Hence, this review addresses some digital soil mapping techniques that enable faster production of soil surveys, beyond fitting continuous spatial distribution of soil properties into discrete soil categories, in accordance with the inherent complexity of soil variation, increasing the accuracy of spatial information. The technique focused here is knowledge-based in expert systems, under fuzzy logic and vector of similarity. For that, a contextualization of each tool in the soil types and properties prediction is provided, as well as some options of knowledge extraction techniques. Such tools have reduced the inconsistency and costs associated with the traditional manual processes, relying on a relatively low density of soil samples. On the other hand, knowledge-based technique is not automatic, and just as the traditional soil survey, the knowledge of soil-landscape relationships is irreplaceable.
Highlights
In Brazil, soil surveys in more detailed scale are still necessary because the lack of information or the smallscale existing maps do not adequately support planning and management of agricultural and environmental projects
Since the traditional soil maps are manually produced, even on a GIS basis, and have as limitation the low speed and high production cost (ZHU et al, 2001), digital soil mapping is viewed as an opportunity to optimize soil mapping, employing more quantitative techniques for spatial prediction (MCBRATNEY; SANTOS; MINASNY, 2003), in which the accuracy or uncertainty has been measured and discussed, and that makes the pedologist mental model more explicit
According to Dale, McBratney, Russell (1989), expert systems consist of ways to harvesting and engineering knowledge, which allow exploiting the information of soil surveyor acquired through experience
Summary
In Brazil, soil surveys in more detailed scale are still necessary because the lack of information or the smallscale existing maps do not adequately support planning and management of agricultural and environmental projects. Soil survey is a paradigm-based science that is based on the application of conceptual soil-landscape models, in which the hypothesis is that the location and distribution of soils in the landscape is predictable (HUDSON; HEUVELINK; ROSSITER, 1992) Such models rely on tacit pedological knowledge, generally acquired by systematic field observation of repeating relationships between soils types or properties and landform position (MACMILLAN; PETTAPIECE; bRIERLEY, 2005). Expert systems allow the use of existing data or expert knowledge of the pedologist in conjunction with statistical and mathematical approaches to generate soil information They allow fitting continuous spatial distribution of soil properties into discrete soil categories, in accordance with the inherent complexity of soil variation, increasing the accuracy of spatial information (ZHU et al, 2001)
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