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Provedor de dados:  Scientia Agricola
País:  Brazil
Título:  Solum depth spatial prediction comparing conventional with knowledge-based digital soil mapping approaches
Autores:  Menezes,Michele Duarte de
Silva,Sérgio Henrique Godinho
Mello,Carlos Rogério de
Owens,Phillip Ray
Curi,Nilton
Data:  2014-08-01
Ano:  2014
Palavras-chave:  Soil survey
Fuzzy logic
Similarity vectors
Resumo:  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.
Tipo:  Info:eu-repo/semantics/article
Idioma:  Inglês
Identificador:  http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162014000400009
Editor:  São Paulo - Escola Superior de Agricultura "Luiz de Queiroz"
Relação:  10.1590/0103-9016-2013-0416
Formato:  text/html
Fonte:  Scientia Agricola v.71 n.4 2014
Direitos:  info:eu-repo/semantics/openAccess
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