Digital Soil Mapping of Soil Properties in the “Mar de Morros” Environment Using Spectral Data
ABSTRACT Quantification of soil properties is essential for better understanding of the environment and better soil management. The conventional techniques of laboratory analysis are sometimes costly and detrimental to the environment. Thus, development of new techniques for soil analysis that do no...
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| Format: | Article |
| Language: | English |
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Sociedade Brasileira de Ciência do Solo
2019-01-01
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| Series: | Revista Brasileira de Ciência do Solo |
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| Online Access: | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06832018000100314&lng=en&tlng=en |
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| author | Patrícia Morais da Matta Campbell Elpídio Inácio Fernandes Filho Márcio Rocha Francelino José Alexandre Melo Demattê Marcos Gervasio Pereira Clécia Cristina Barbosa Guimarães and Luiz Alberto da Silva Rodrigues Pinto |
| author_facet | Patrícia Morais da Matta Campbell Elpídio Inácio Fernandes Filho Márcio Rocha Francelino José Alexandre Melo Demattê Marcos Gervasio Pereira Clécia Cristina Barbosa Guimarães and Luiz Alberto da Silva Rodrigues Pinto |
| author_sort | Patrícia Morais da Matta Campbell |
| collection | DOAJ |
| description | ABSTRACT Quantification of soil properties is essential for better understanding of the environment and better soil management. The conventional techniques of laboratory analysis are sometimes costly and detrimental to the environment. Thus, development of new techniques for soil analysis that do not generate residues, such as spectroscopy, is increasingly necessary as a viable way to estimate a wide range of soil properties. The objective of this study was to predict the levels of organic carbon (OC), clay, and extractable phosphorus (P), from the spectral responses of soil samples in the visible and near infrared (Vis-NIR), medium infrared (MIR), and Vis-NIR-MIR using different preprocessing methods combined with five prediction models. Soil samples were collected in Iconha, Espírito Santo State, Brazil, in the Ribeirão Inhaúma basin. A total of 184 samples were collected from 92 sites at two depths (0.00-0.10 and 0.10-0.30 m). Physical, chemical, and spectral analyses were performed according to routine soil laboratory methods. Random selection was made of 70 % of total samples for training and 30 % for validation of the models. The coefficient of determination (R2) and root mean square error (RMSE) were calculated in order to assess model performance. The standardized indexes of prediction error RPD and RPIQ were also calculated. For clay and OC, the best R2 was found in the MIR spectrum, at 0.69 and 0.65, respectively, and for P, it was 0.57 in Vis-NIR. The MSC (Multiplicative Scatter Correction), CR (Continuum removal), and SNV (Standard Normal Variate) preprocesses were most efficient for predicting clay, OC, and P, respectively, while the PLSR - Partial Least Squares Regression (OC and P) and SVM - Support Vector Machine (clay) gave the best predictions and are therefore recommended for modeling these properties in the study area. The models identified in this study can be used to discriminate soils according to a critical test value for clay, OC, and P. |
| first_indexed | 2024-12-20T09:34:28Z |
| format | Article |
| id | doaj.art-0aceccf8ca764c0eb350afc34e4472f9 |
| institution | Directory Open Access Journal |
| issn | 1806-9657 |
| language | English |
| last_indexed | 2024-12-20T09:34:28Z |
| publishDate | 2019-01-01 |
| publisher | Sociedade Brasileira de Ciência do Solo |
| record_format | Article |
| series | Revista Brasileira de Ciência do Solo |
| spelling | doaj.art-0aceccf8ca764c0eb350afc34e4472f92022-12-21T19:45:02ZengSociedade Brasileira de Ciência do SoloRevista Brasileira de Ciência do Solo1806-96572019-01-0142010.1590/18069657rbcs20170413S0100-06832018000100314Digital Soil Mapping of Soil Properties in the “Mar de Morros” Environment Using Spectral DataPatrícia Morais da Matta CampbellElpídio Inácio Fernandes FilhoMárcio Rocha FrancelinoJosé Alexandre Melo DemattêMarcos Gervasio PereiraClécia Cristina Barbosa Guimarães andLuiz Alberto da Silva Rodrigues PintoABSTRACT Quantification of soil properties is essential for better understanding of the environment and better soil management. The conventional techniques of laboratory analysis are sometimes costly and detrimental to the environment. Thus, development of new techniques for soil analysis that do not generate residues, such as spectroscopy, is increasingly necessary as a viable way to estimate a wide range of soil properties. The objective of this study was to predict the levels of organic carbon (OC), clay, and extractable phosphorus (P), from the spectral responses of soil samples in the visible and near infrared (Vis-NIR), medium infrared (MIR), and Vis-NIR-MIR using different preprocessing methods combined with five prediction models. Soil samples were collected in Iconha, Espírito Santo State, Brazil, in the Ribeirão Inhaúma basin. A total of 184 samples were collected from 92 sites at two depths (0.00-0.10 and 0.10-0.30 m). Physical, chemical, and spectral analyses were performed according to routine soil laboratory methods. Random selection was made of 70 % of total samples for training and 30 % for validation of the models. The coefficient of determination (R2) and root mean square error (RMSE) were calculated in order to assess model performance. The standardized indexes of prediction error RPD and RPIQ were also calculated. For clay and OC, the best R2 was found in the MIR spectrum, at 0.69 and 0.65, respectively, and for P, it was 0.57 in Vis-NIR. The MSC (Multiplicative Scatter Correction), CR (Continuum removal), and SNV (Standard Normal Variate) preprocesses were most efficient for predicting clay, OC, and P, respectively, while the PLSR - Partial Least Squares Regression (OC and P) and SVM - Support Vector Machine (clay) gave the best predictions and are therefore recommended for modeling these properties in the study area. The models identified in this study can be used to discriminate soils according to a critical test value for clay, OC, and P.http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06832018000100314&lng=en&tlng=enspectral analysisreflectancechemometrics |
| spellingShingle | Patrícia Morais da Matta Campbell Elpídio Inácio Fernandes Filho Márcio Rocha Francelino José Alexandre Melo Demattê Marcos Gervasio Pereira Clécia Cristina Barbosa Guimarães and Luiz Alberto da Silva Rodrigues Pinto Digital Soil Mapping of Soil Properties in the “Mar de Morros” Environment Using Spectral Data Revista Brasileira de Ciência do Solo spectral analysis reflectance chemometrics |
| title | Digital Soil Mapping of Soil Properties in the “Mar de Morros” Environment Using Spectral Data |
| title_full | Digital Soil Mapping of Soil Properties in the “Mar de Morros” Environment Using Spectral Data |
| title_fullStr | Digital Soil Mapping of Soil Properties in the “Mar de Morros” Environment Using Spectral Data |
| title_full_unstemmed | Digital Soil Mapping of Soil Properties in the “Mar de Morros” Environment Using Spectral Data |
| title_short | Digital Soil Mapping of Soil Properties in the “Mar de Morros” Environment Using Spectral Data |
| title_sort | digital soil mapping of soil properties in the mar de morros environment using spectral data |
| topic | spectral analysis reflectance chemometrics |
| url | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06832018000100314&lng=en&tlng=en |
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