Magnetic susceptibility to identify landscape segments on a detailed scale in the region of Jaboticabal, São Paulo, Brazil

• Autor(a) principal: Barrios,Mariana dos Reis
• Data de Publicação: 2012
• Outros Autores: Marques Junior,José, Panosso,Alan Rodrigo, Siqueira,Diego Silva, La Scala Junior,Newton
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Revista Brasileira de Ciência do Solo (Online)
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06832012000400002
• topic: landforms; principal component analysis; cluster analysis

The agricultural potential is generally assessed and managed based on a one-dimensional vision of the soil profile, however, the increased appreciation of sustainable production has stimulated studies on faster and more accurate evaluation techniques and methods of the agricultural potential on detailed scales. The objective of this study was to investigate the possibility of using soil magnetic susceptibility for the identification of landscape segments on a detailed scale in the region of Jaboticabal, São Paulo State. The studied area has two slope curvatures: linear and concave, subdivided into three landscape segments: upper slope (US, concave), middle slope (MS, linear) and lower slope (LS, linear). In each of these segments, 20 points were randomly sampled from a database with 207 samples forming a regular grid installed in each landscape segment. The soil physical and chemical properties, CO2 emissions (FCO2) and magnetic susceptibility (MS) of the samples were evaluated represented by: magnetic susceptibility of air-dried fine earth (MS ADFE), magnetic susceptibility of the total sand fraction (MS TS) and magnetic susceptibility of the clay fraction (MS Cl) in the 0.00 - 0.15 m layer. The principal component analysis showed that MS is an important property that can be used to identify landscape segments, because the correlation of this property within the first principal component was high. The hierarchical cluster analysis method identified two groups based on the variables selected by principal component analysis; of the six selected variables, three were related to magnetic susceptibility. The landscape segments were differentiated similarly by the principal component analysis and by the cluster analysis using only the properties with higher discriminatory power. The cluster analysis of MS ADFE, MS TS and MS Cl allowed the formation of three groups that agree with the segment division established in the field. The grouping by cluster analysis indicated MS as a tool that could facilitate the identification of landscape segments and enable the mapping of more homogeneous areas at similar locations.