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| Registros recuperados : 297 | |
| 36. |  | COSTA, J. M.; PIETROBOM, M. R. Samambaias e licófitas do Parque Ecológico do Gunma, município de Santa Bárbara do Pará, estado do Pará, Brasil. Rodriguésia, Rio de Janeiro, RJ, v. 61, n. 2, p. 223-232, abr./jun. 2010.| Biblioteca(s): Epagri-Sede. |
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| 37. | | COSTA, J. M.; PIETROBOM, M. R. Pteridófitas (Lycophyta e Monilophyta) da Ilha de Mosqueiro, município de Belém, Estado do Pará, Brasil. Boletim do Museu Paraense Emilio Goeldi: Ciências Naturais, Belém, v. 2, n. 3, p. 45-56, set./dez. 2007.| Biblioteca(s): Epagri-Sede. |
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| Registros recuperados : 297 | |
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Registro Completo
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Biblioteca(s): |
Epagri-Sede. |
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Data corrente: |
14/10/2019 |
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Data da última atualização: |
14/10/2019 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
Nacional - B |
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Autoria: |
COSTA, J. J. F.; GIASSON, E.; SILVA, E. B.; CAMPOS, A. R.; MACHADO, I. R.; BONFATTI, B. R.; BACIC, I. L. Z. |
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Título: |
Individualization of soil classes by disaggregation of physiographic map polygons. |
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Ano de publicação: |
2019 |
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Fonte/Imprenta: |
Pesquisa Agropecuária Brasileira, Brasília, v. 54, p. 1-11, 2019. |
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Idioma: |
Inglês |
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Conteúdo: |
The objective of this work was to disaggregate the polygons of
physiographic map units in order to individualize the soil classes in each one,
representing them as simple soil map units and generating a more detailed soil
map than the original one, making these data more useful for future reference.
A physiographic map, on a 1:25,000 scale, of the Tarumãzinho watershed,
located in the municipality of Águas Frias, in the state of Santa Catarina,
Brazil, was used. For disaggregation, three geomorphometric parameters were
applied: slope and landforms, both derived from the digital terrain model; and
an elevation map. The boundaries of the physiographic units and the elevation,
slope, and landform maps were subjected to cross tabulation to identify the
existing combinations between the soil classes of each physiographic unit.
Based on these combinations, rules were established to select typical areas of
occurrence of each soil type in order to train a decision tree model to predict
the occurrence of soil classes. The model was trained using the Weka software
and was validated with a set of georeferenced soil profiles. Disaggregation
enables the individualization and spatialization of soil classes and is useful in
producing detailed soil maps. |
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Palavras-Chave: |
decision trees; digital soil mapping; pedology; soil class prediction. |
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Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
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Marc: |
LEADER 01971naa a2200241 a 4500
001 1128927
005 2019-10-14
008 2019 bl uuuu u00u1 u #d
100 1 $aCOSTA, J. J. F.
245 $aIndividualization of soil classes by disaggregation of physiographic map polygons.$h[electronic resource]
260 $c2019
520 $aThe objective of this work was to disaggregate the polygons of physiographic map units in order to individualize the soil classes in each one, representing them as simple soil map units and generating a more detailed soil map than the original one, making these data more useful for future reference. A physiographic map, on a 1:25,000 scale, of the Tarumãzinho watershed, located in the municipality of Águas Frias, in the state of Santa Catarina, Brazil, was used. For disaggregation, three geomorphometric parameters were applied: slope and landforms, both derived from the digital terrain model; and an elevation map. The boundaries of the physiographic units and the elevation, slope, and landform maps were subjected to cross tabulation to identify the existing combinations between the soil classes of each physiographic unit. Based on these combinations, rules were established to select typical areas of occurrence of each soil type in order to train a decision tree model to predict the occurrence of soil classes. The model was trained using the Weka software and was validated with a set of georeferenced soil profiles. Disaggregation enables the individualization and spatialization of soil classes and is useful in producing detailed soil maps.
653 $adecision trees
653 $adigital soil mapping
653 $apedology
653 $asoil class prediction
700 1 $aGIASSON, E.
700 1 $aSILVA, E. B.
700 1 $aCAMPOS, A. R.
700 1 $aMACHADO, I. R.
700 1 $aBONFATTI, B. R.
700 1 $aBACIC, I. L. Z.
773 $tPesquisa Agropecuária Brasileira, Brasília$gv. 54, p. 1-11, 2019.
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