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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

Soil classification using visible/near-infrared diffuse reflectance spectra from multiple depths

Texto completo
Vasques, G. M. [1] ; Dematte, J. A. M. [2] ; Viscarra Rossel, Raphael A. [3] ; Ramirez-Lopez, L. [4, 5, 6] ; Terra, F. S. [2]
Número total de Autores: 5
Afiliação do(s) autor(es):
[1] Embrapa Solos, BR-22460000 Rio De Janeiro, RJ - Brazil
[2] Univ Sao Paulo, Coll Agr Luiz de Queiroz, Dept Soil Sci, BR-13418900 Piracicaba, SP - Brazil
[3] CSIRO Land & Water, Canberra, ACT 2601 - Australia
[4] Swiss Fed Inst Forest Snow & Landscape Res WSL, CH-8903 Birmensdorf - Switzerland
[5] ETH, Inst Terr Ecosyst, CH-8092 Zurich - Switzerland
[6] Univ Tubingen, Inst Geog Phys Geog & Soil Sci, D-72070 Tubingen - Germany
Número total de Afiliações: 6
Tipo de documento: Artigo Científico
Fonte: Geoderma; v. 223, p. 73-78, JUL 2014.
Citações Web of Science: 46

Visible/near-infrared diffuse reflectance spectroscopy (VNIRDRS) offers an alternative to conventional analytical methods to estimate various soil attributes. However, the use of VNIRDRS in soil survey and taxonomic classification is still underexplored. We investigated the potential use of VNIRDRS to classify soils in a region with variable soils, geology, and topography in southeastern Brazil. Soils were classified in the field according to the Brazilian Soil Classification System, and visible/near-infrared (400-2500 nm) spectra were collected from three depth intervals (0-20,40-60 and 80-100 cm) and combined in sequence to compose a pseudo multi-depth spectral curve, which was used to derive the classification models. Principal component (PC) analysis and multinomial logistic regression were used to classify 291 soils (202 in calibration and 89 in validation mode) at the levels of order (highest), suborder (second highest) and suborder plus textural classification (STC). Based on the validation results, best classification was obtained at the order level (67% agreement rate), followed by suborder (48% agreement) and STC (24% agreement). The inherent complexity and variability within soil taxonomic groups and in contrast the strong similarity among different groups in terms of soil spectra and other attributes cause confusion in the classification model. This novel approach combining spectral data from different depths in multivariate classification can improve soil classification and survey in a cost-efficient manner, supporting sustainable use and management of tropical soils. (C) 2014 Elsevier B.V. All rights reserved. (AU)

Processo FAPESP: 09/10711-6 - Estratégias tecnológicas em mapeamento de solos: uma nova metodologia aplicada
Beneficiário:José Alexandre Melo Demattê
Linha de fomento: Bolsas no Exterior - Pesquisa