Solum depth spatial prediction comparing conventional with knowledge-based digital soil mapping approaches

Authors

  • Michele Duarte de Menezes Federal Rural University of Rio de Janeiro; Soil Dept.
  • Sérgio Henrique Godinho Silva Federal University of Lavras; Soil Science Dept.
  • Carlos Rogério de Mello Federal University of Lavras; Engineering Dept
  • Phillip Ray Owens Purdue University; Dept. of Agronomy; Lilly Hall of Life Sciences
  • Nilton Curi Federal University of Lavras; Soil Science Dept.

DOI:

https://doi.org/10.1590/0103-9016-2013-0416

Abstract

Solum depth and its spatial distribution play an important role in different types of environmental studies. Several approaches have been used for fitting quantitative relationships between soil properties and their environment in order to predict them spatially. This work aimed to present the steps required for solum depth spatial prediction from knowledge-based digital soil mapping, comparing the prediction to the conventional soil mapping approach through field validation, in a watershed located at Mantiqueira Range region, in the state of Minas Gerais, Brazil. Conventional soil mapping had aerial photo-interpretation as a basis. The knowledge-based digital soil mapping applied fuzzy logic and similarity vectors in an expert system. The knowledge-based digital soil mapping approach showed the advantages over the conventional soil mapping approach by applying the field expert-knowledge in order to enhance the quality of final results, predicting solum depth with suited accuracy in a continuous way, making the soil-landscape relationship explicit.

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Published

2014-08-01

How to Cite

Menezes, M. D. de, Silva, S. H. G., Mello, C. R. de, Owens, P. R., & Curi, N. (2014). Solum depth spatial prediction comparing conventional with knowledge-based digital soil mapping approaches . Scientia Agricola, 71(4), 316-323. https://doi.org/10.1590/0103-9016-2013-0416

Issue

Section

Soils and Plant Nutrition