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Title: | Digital soil mapping approach based on fuzzy logic and field expert knowledge |
Other Titles: | Abordagem de mapeamento digital de solos baseado em lógica fuzzy e conhecimento de campo de especialista |
Keywords: | Digital soil mapping Soil prediction Conditioned Latin hypercube sampling Knowledge miner Mapeamento digital de solos Predição de solos Amostragem em hipercubo latino condicionado Mineração do conhecimento |
Issue Date: | Jul-2013 |
Publisher: | Editora da Universidade Federal de Lavras |
Citation: | MENEZES, M. D. de et al. Digital soil mapping approach based on fuzzy logic and field expert knowledge. Ciência e Agrotecnologia, Lavras, v. 37, n. 4, p. 287-298, jul./ago. 2013. |
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. |
URI: | http://repositorio.ufla.br/jspui/handle/1/41952 |
Appears in Collections: | DCS - Artigos publicados em periódicos |
Files in This Item:
File | Description | Size | Format | |
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ARTIGO_Digital soil mapping approach based on fuzzy logic and field expert knowledge.pdf | 497,89 kB | Adobe PDF | View/Open |
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