2015
DOI: 10.5935/1806-6690.20150001
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Hyperspectral remote sensing as an alternative to estimate soil attributes

Abstract: -Minimizing environmental impacts and increasing crop productivity depend mainly on the knowledge of chemical, physical and mineralogical characteristics of the soil attributes. However, traditional methods are timeconsuming and costly. The objective of this study was to determine and validate a method to quantify soil attributes using UV-Vis-NIR Spectroscopy as an alternative to conventional methods of soil analyses. The work comprised two main phases: (1) creation and calibration of statistical models to det… Show more

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Cited by 23 publications
(17 citation statements)
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“…There are already portable versions of these equipment that are suitable for in situ applications [ 12 , 13 ]. The vis-NIR diffuse reflectance spectroscopy is a widespread technique in soil science [ 14 , 15 ], with extensive research reporting its potential to predict mineralogical and organic attributes successfully [ 9 , 16 , 17 , 18 ]. Regarding soil fertility, in some cases, good results can be extended for extractable (ex-) nutrients (e.g., ex-K, ex-Ca, and ex-Mg) [ 7 , 19 , 20 ], cation exchange capacity (CEC) [ 19 , 21 ], base saturation (V), soil potential acidity (H + Al 3+ ), and pH [ 19 , 22 ], which are few to mention among others.…”
Section: Introductionmentioning
confidence: 99%
“…There are already portable versions of these equipment that are suitable for in situ applications [ 12 , 13 ]. The vis-NIR diffuse reflectance spectroscopy is a widespread technique in soil science [ 14 , 15 ], with extensive research reporting its potential to predict mineralogical and organic attributes successfully [ 9 , 16 , 17 , 18 ]. Regarding soil fertility, in some cases, good results can be extended for extractable (ex-) nutrients (e.g., ex-K, ex-Ca, and ex-Mg) [ 7 , 19 , 20 ], cation exchange capacity (CEC) [ 19 , 21 ], base saturation (V), soil potential acidity (H + Al 3+ ), and pH [ 19 , 22 ], which are few to mention among others.…”
Section: Introductionmentioning
confidence: 99%
“…Studies on spectroradiometry show a strong relationship between spectral responses and soil properties, such as cation exchange capacity, organic carbon, Fe oxides, and clay (Chang et al, 2001;Shepherd and Walsh, 2002;Franceschini et al, 2013;Nanni and Demattê, 2006;Demattê et al, 2014a). In fact, this led Demattê et al (2004a) to use a spectroscopy information to aid in pedological mapping.…”
Section: Resumo: Múltiplas Ferramentas Tecnológicas No Mapeamento Digmentioning
confidence: 99%
“…Multiple regression equations were fitted to predict values of 19 soil properties from their spectral response (Table 1) Demattê et al (2004a), and Demattê et al (2014a). It is notable that high coefficients for the physical properties such as sand, clay, and Fe 2 O 3 were achieved, since these parameters have a significantly greater influence on the spectral response of the soil.…”
Section: Quantification Of Soil Propertiesmentioning
confidence: 99%
“…Em síntese, o uso de sensores na agricultura permite estimar de forma prática, barata e indestrutível parâmetros biofísicos de culturas agrícolas (ANDRADE et al, 2014) e atributos físicoquímicos do solo (DEMATTÊ et al, 2015;DEMATTÊ et al, 2016). Ao se associar estes dados a informações de posição geográfica, torna-se possível representar e avaliar a variabilidade espacial do campo agrícola, abrindo portas à aplicação de diferentes abordagens de AP.…”
Section: Sensoriamento Na Agriculturaunclassified
“…A partir de combinações entre estas novas variáveis, é gerado o modelo de regressão linear(VISCARRA ROSSEL;BEHRENS, 2010). Esta técnica supõe que algumas variáveis não contribuam de forma expressiva com a resposta de todo o conjunto(DARVISHZADEH et al, 2008).Desta forma, este método é útil em situações que apresentam grandes bancos de dados com um alto número de variáveis independentes, permitindo identificar pequenos subgrupos de variáveis as quais melhor se correlacionam e determinam o valor da variável dependente(DEMATTÊ et al, 2015).Outro método eficiente para a redução da dimensão de dados altamente correlacionados é a sparse Partial Least Square (sPLS). Ele, ao contrário do Stepwise, pode ser aplicado quando existem mais variáveis que observações.…”
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