Use este identificador para citar ou linkar para este item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1112779
Título: Proximal soil sensing platform for effective mapping of soil attributes in Brazil.
Autoria: OLIVEIRA, R. P. de
RODRIGUES, H. M.
VASQUES, G. de M.
TAVARES, S. R. de L.
HERNANI, L. C.
BACA, J. F. M.
COELHO, M. R.
Afiliação: RONALDO PEREIRA DE OLIVEIRA, CNPS; HUGO M. RODRIGUES, UFRRJ; GUSTAVO DE MATTOS VASQUES, CNPS; SILVIO ROBERTO DE LUCENA TAVARES, CNPS; LUIS CARLOS HERNANI, CNPS; JESUS FERNANDO MANSILLA BACA, CNPS; MAURICIO RIZZATO COELHO, CNPS.
Ano de publicação: 2019
Referência: In: GLOBAL WORKSHOP ON PROXIMAL SOIL SENSING, 5., 2019, Columbia, MO. Program and proceedings. Columbia, MO: University of Missouri, 2019. p. 273-278.
Conteúdo: Sustainable management of agricultural lands requires detailed information on soil properties. Although the literature has shown the potential of PSS data integration to predict spatial variations of soil properties, most of these studies were done in temperate soils considering up to three sensors. Study cases here introduced to contribute in applying PSS to: (i) assess the spatial variation of tropical soil chemical and physical attributes; (ii) understand processes controlling spatial soil variations; and (iii) compare spatial dependence and patterns among proximally-sensed and laboratory-measured soil attributes. In three preliminary study cases PSS was applied for digital soil mapping, soil salinity mapping, and within-field crop variations. Hand held and "on-the-go" sensors, respectively, for point-based and continuous monitoring readings, include apparent electrical conductivity and magnetic susceptibility meters; gamma ray, X-ray fluorescence and near infrared spectrometers; and mechanical resistance meters among others. Variables were significantly correlated (p < 0.05), and their spatial dependence structure (i.e: variogram analysis) and the spatial distribution patterns (i.e.: kriging) were all-similar. In addition, combined PSS datasets have shown improved predictions of soil properties (i.e.: R2adj. from 0.21 to 0.94). Results have indicated the potential of PSS to assess the spatial variation of soil attributes that are more difficult to collect and analyze, supporting detailed soil mapping for precision agriculture and related activities.
Thesagro: Sensoriamento Remoto
Solo Tropical
Mapa
NAL Thesaurus: Remote sensing
Tropical soils
Digital images
Soil map
Palavras-chave: Sensoriamento Proximal
Atributos do Solo
Mapeamento Digital do Solo
Tipo do material: Artigo em anais e proceedings
Acesso: openAccess
Aparece nas coleções:Artigo em anais de congresso (CNPS)

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