Mirian Cristina Gomes Costa

Prof. Mirian Cristina Gomes Costa

Federal University of Ceará
orcid

Research Focus & Metrics

Academic Career Length

23Years (2004-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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28 June 2023 in Environmental Research
Verified
Journal Article
Closed access
ÍNÍcaro Vasconcelos Do Nascimento
Ícaro Vasconcelos Do Nascimento
LFLaís Gomes Fregolente
Laís Gomes Fregolente
APArthur Prudêncio De A. Pereira
Arthur Prudêncio De A. Pereira
CNCarla Danielle Vasconcelos Do Nascimento
Carla Danielle Vasconcelos Do Nascimento
JMJaedson Cláudio Anunciato Mota
Jaedson Cláudio Anunciato Mota
Mirian Cristina Gomes CostaMirian Cristina Gomes Costa
Mirian Cristina Gomes Costa

24 November 2021 in Remote Sensing
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Journal Article
Open access
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SRSharon Gomes Ribeiro
Sharon Gomes Ribeiro
ATADUNIAS TEIXEIRA
ADUNIAS TEIXEIRA
Marcio Regys OliveiraMarcio Regys Oliveira
Marcio Regys Oliveira
Mirian Cristina Gomes CostaMirian Cristina Gomes Costa
Mirian Cristina Gomes Costa
IAIsabel Cristina da Silva Araújo
Isabel Cristina da Silva Araújo
Fernando Bezerra LopesFernando Bezerra Lopes
Fernando Bezerra Lopes
Quantifying the organic carbon content of soil over large areas is essential for characterising the soil and the effects of its management. However, analytical methods can be laborious and costly. Reflectance spectroscopy is a well-established and widespread method for estimating the chemical-element content of soils. The aim of this study was to estimate the soil organic carbon (SOC) content using hyperspectral remote sensing. The data were from soils from two localities in the semi-arid region of Brazil. The spectral reflectance factors of the collected soil samples were recorded at wavelengths ranging from 350–2500 nm. Pre-processing techniques were employed, including normalisation, Savitzky–Golay smoothing and first-order derivative analysis. The data (n = 65) were examined both jointly and by soil class, and subdivided into calibration and validation to independently assess the performance of the linear methods. Two multivariate models were calibrated using the SOC content estimated in the laboratory by principal component regression (PCR) and partial least squares regression (PLSR). The study showed significant success in predicting the SOC with transformed and untransformed data, yielding acceptable-to-excellent predictions (with the performance-to-deviation ratio ranging from 1.40–3.38). In general, the spectral reflectance factors of the soils decreased with the increasing levels of SOC. PLSR was considered more robust than PCR, whose wavelengths from 354 to 380 nm, 1685, 1718, 1757, 1840, 1876, 1880, 2018, 2037, 2042, and 2057 nm showed outstanding absorption characteristics between the predicted models. The results found here are of significant practical value for estimating SOC in Neosols and Cambisols in the semi-arid region of Brazil using VIS-NIR-SWIR spectroscopy.

1 September 2015 in Ecological Engineering
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Journal Article
Closed access
FPFabio Perlatti
Fabio Perlatti
Tiago O. FerreiraTiago O. Ferreira
Tiago O. Ferreira
RRRicardo Espíndola Romero
Ricardo Espíndola Romero
Mirian Cristina Gomes CostaMirian Cristina Gomes Costa
Mirian Cristina Gomes Costa
Xosé Lois Otero-PérezXosé Lois Otero-Pérez
Xosé Lois Otero-Pérez


1 March 2018 in Geoderma
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Journal Article
Closed access
AMAdemir Silva Menezes
Ademir Silva Menezes
TAThiago Leite Alencar
Thiago Leite Alencar
RJRaimundo Nonato Assis Júnior
Raimundo Nonato Assis Júnior
RTRaul Shiso Toma
Raul Shiso Toma
RRRicardo Espíndola Romero
Ricardo Espíndola Romero
JMJaedson Cláudio Anunciato Mota
Jaedson Cláudio Anunciato Mota

1 February 2014 in Revista Brasileira de Engenharia Agrícola E Ambiental
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AAAdriana Guirado Artur
Adriana Guirado Artur
DODaniel P. Oliveira
Daniel P. Oliveira
Mirian Cristina Gomes CostaMirian Cristina Gomes Costa
Mirian Cristina Gomes Costa
RRRicardo E. Romero
Ricardo E. Romero
MSMarcus V. C. Silva
Marcus V. C. Silva
Tiago O. FerreiraTiago O. Ferreira
Tiago O. Ferreira
A variabilidade dos atributos químicos do solo é influenciada por complexas interações entre os fatores e os processos de formação do solo. Este trabalho partiu da hipótese de que os atributos químicos do solo variam com o microrrelevo a ponto de alterar as recomendações de manejo para uso agrícola. Com isto, o relevo foi separado em compartimentos e as superfícies estudadas com o objetivo de se determinar os atributos químicos do solo, avaliar a distribuição e a dependência espacial desses atributos. A grade amostral compreendeu uma área de 102 ha da Fazenda Agrícola Famosa, localizada na Chapada do Apodi, CE. O solo da área apresenta origem calcária e as amostras foram coletadas em 92 pontos distanciados 200 m na linha e 100 m entre linhas, nas profundidades de 0-20 e 20-40 cm. Com os dados, gerou-se um modelo de elevação do terreno e, com base nas formas de relevo identificadas, dividiu-se o local de estudo em superfícies. Os dados foram avaliados por estatística descritiva e análise de variabilidade espacial, com base no ajuste de semivariogramas e mapas de krigagem. Os atributos químicos do solo apresentaram variabilidade espacial nos microrrelevos convexo, retilíneo e côncavo, intensificada pelo fluxo de água nas profundidades.