Discrimination of geomorphic surfaces with multivariate analysis of soil attributes in sandstone - basalt lithosequence
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Data
2012-09-01
Autores
Campos, Milton César Costa
Marques Júnior, José [UNESP]
Souza, Zigomar Menezes de
Siqueira, Diego Silva [UNESP]
Pereira, Gener Tadeu [UNESP]
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Universidade Federal do Ceará (UFC)
Resumo
O conceito de superfície geomórfica permite uma interligação entre os diferentes ramos da ciência do solo, tais como geologia, geomorfologia e pedologia. Esta associação favorece a compreensão da distribuição espacial dos solos na paisagem, e torna possível compreender o comportamento dos atributos do solo, que estão principalmente relacionadas com a estratigrafia e formas do relevo. Assim, este estudo visa à aplicação da estatística multivariada para categorizar superfícies geomórficas em uma litossequência arenito-basalto, de modo a fornecer uma base para a avaliação do solo em áreas afins. A área de estudo está localizada no município de Pereira Barreto, São Paulo, Brasil. A área escolhida possui 530 hectares, onde foram localizadas e mapeadas três superfícies geomórficas (I, II e III). Na área, 134 amostras foram coletadas nas profundidades de 0,0-0,2 m e 0,8-1,0 m, foram determinados os conteúdos de areia, silte e argila, pH em CaCl2, conteúdo de MO, P, Ca, Mg, K, Al e H+Al. Com base nos resultados, foram realizadas a análise univariada e multivariada de variância, clusters e principal componente, a fim de comparar as três superfícies geomórficas. A análise estatística univariada dos atributos do solo não foi eficiente na identificação das três superfícies geomórficas. Utilizando-se os atributos físicos e químicos do solo, as técnicas estatísticas multivariada permitiram à separação dos três grupos de corpos naturais do solo que foram equivalentes as três superfícies geomórficas mapeadas. Estes resultados são interessantes, pois demonstram a viabilidade da utilização de classificação numérica das superfícies geomórficas para ajudar no mapeamento de solo.
The geomorphic surface concept allows interrelationship among various branches of soil sciences, such as geology, geomorphology and pedology. This association enhances the understanding of spatial soil distribution through landscape, pointing out the soil attributes behavior, which are mainly related to stratigraphy and relief forms. Therefore, this study aims to apply multivariate statistics to categorize geomorphic surfaces in sandstone - basalt lithosequence, so as to provide a basis for soil assessment in similar areas. The study area is located in Pereira Barreto County, SP, Brazil. An area of 530 hectare was selected, where three geomorphic surfaces (I, II and III) were located and mapped. In this area, 134 soil samples were collected at depths of 0.0-0.2 m and 0.8-1.0 m below ground surface. Sand, silt and clay contents were determined, pH in CaCl2 solution, OM, P, Ca, Mg, K, Al and H+Al contents were also evaluated. Based on the results, univariate, multivariate analysis of variance, cluster and principal-component analysis were performed in order to compare the three geomorphic surfaces. The univariate statistical analysis of soil attributes was not efficient enough to categorize the three geomorphic surfaces. By using the physical and chemical soil properties, the multivariate statistical techniques enabled the differentiation of the three groups of soil natural bodies which were equivalent to the same three mapped geomorphic surfaces (GS). These results are interestingin order to demonstrate the feasibility of the numerical classification use on geomorphic surfaces to assist the soil mapping.
The geomorphic surface concept allows interrelationship among various branches of soil sciences, such as geology, geomorphology and pedology. This association enhances the understanding of spatial soil distribution through landscape, pointing out the soil attributes behavior, which are mainly related to stratigraphy and relief forms. Therefore, this study aims to apply multivariate statistics to categorize geomorphic surfaces in sandstone - basalt lithosequence, so as to provide a basis for soil assessment in similar areas. The study area is located in Pereira Barreto County, SP, Brazil. An area of 530 hectare was selected, where three geomorphic surfaces (I, II and III) were located and mapped. In this area, 134 soil samples were collected at depths of 0.0-0.2 m and 0.8-1.0 m below ground surface. Sand, silt and clay contents were determined, pH in CaCl2 solution, OM, P, Ca, Mg, K, Al and H+Al contents were also evaluated. Based on the results, univariate, multivariate analysis of variance, cluster and principal-component analysis were performed in order to compare the three geomorphic surfaces. The univariate statistical analysis of soil attributes was not efficient enough to categorize the three geomorphic surfaces. By using the physical and chemical soil properties, the multivariate statistical techniques enabled the differentiation of the three groups of soil natural bodies which were equivalent to the same three mapped geomorphic surfaces (GS). These results are interestingin order to demonstrate the feasibility of the numerical classification use on geomorphic surfaces to assist the soil mapping.
Descrição
Palavras-chave
Soil Science, Geomorphology, Multivariate analysis, Ciência do Solo, Geomorfologia, Análise multivariada
Como citar
Revista Ciência Agronômica. Universidade Federal do Ceará (UFC), v. 43, n. 3, p. 429-438, 2012.