Satellite Spectral Data on the Quantification of Soil Particle Size from Different Geographic Regions
The study of soils, including their physical and chemical properties, is essential for agricultural management. Soil quality must be maintained to ensure sustainable production of food and conservation of natural resources. In this context, soil mapping is important to provide spatial information, w...
| Main Authors: | , , , , , , |
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| Format: | Journal Article |
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Sociedade Brasileira de Ciência do Solo
2018
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| Online Access: | http://hdl.handle.net/20.500.11937/76328 |
| _version_ | 1848763669072052224 |
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| author | Demattê, J. Guimarães, C. Fongaro, C. Vidoy, E. Sayão, V. Dotto, Andre C. dos Santos, N. |
| author_facet | Demattê, J. Guimarães, C. Fongaro, C. Vidoy, E. Sayão, V. Dotto, Andre C. dos Santos, N. |
| author_sort | Demattê, J. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | The study of soils, including their physical and chemical properties, is essential for agricultural management. Soil quality must be maintained to ensure sustainable production of food and conservation of natural resources. In this context, soil mapping is important to provide spatial information, which can be performed using remote sensing (RS) techniques. Modeling through use of satellite data is uncertain regarding the amplitude of replicability of the models. The aim of this study was to develop a quantification model for soil texture based on reflectance information from a continuum of bare soils, obtained by overlapping multi-temporal satellite images, and apply this model to an unknown region to evaluate its applicability. Spectral data were extracted from two Landsat TM 7 satellite images containing only bare soil, representing two distinct regions in Brazil (Area 1 and Area 2). The spectral data (obtained from six bands) and laboratory data (particle size from the 0.00-0.20 m layer) of Area 1 were modeled and extrapolated to Area 2. The bare soil images differentiated textural classes as sandy, sandy loam, clayey loam, clayey, and very clayey soil. The coefficients of determination between the determined and estimated values were higher than 0.5 and errors lower than 13 % for Area 1 and 30 % for Area 2, indicating applicability of the model to unknown areas. |
| first_indexed | 2025-11-14T11:07:08Z |
| format | Journal Article |
| id | curtin-20.500.11937-76328 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T11:07:08Z |
| publishDate | 2018 |
| publisher | Sociedade Brasileira de Ciência do Solo |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-763282021-01-05T08:07:08Z Satellite Spectral Data on the Quantification of Soil Particle Size from Different Geographic Regions Demattê, J. Guimarães, C. Fongaro, C. Vidoy, E. Sayão, V. Dotto, Andre C. dos Santos, N. The study of soils, including their physical and chemical properties, is essential for agricultural management. Soil quality must be maintained to ensure sustainable production of food and conservation of natural resources. In this context, soil mapping is important to provide spatial information, which can be performed using remote sensing (RS) techniques. Modeling through use of satellite data is uncertain regarding the amplitude of replicability of the models. The aim of this study was to develop a quantification model for soil texture based on reflectance information from a continuum of bare soils, obtained by overlapping multi-temporal satellite images, and apply this model to an unknown region to evaluate its applicability. Spectral data were extracted from two Landsat TM 7 satellite images containing only bare soil, representing two distinct regions in Brazil (Area 1 and Area 2). The spectral data (obtained from six bands) and laboratory data (particle size from the 0.00-0.20 m layer) of Area 1 were modeled and extrapolated to Area 2. The bare soil images differentiated textural classes as sandy, sandy loam, clayey loam, clayey, and very clayey soil. The coefficients of determination between the determined and estimated values were higher than 0.5 and errors lower than 13 % for Area 1 and 30 % for Area 2, indicating applicability of the model to unknown areas. 2018 Journal Article http://hdl.handle.net/20.500.11937/76328 10.1590/18069657rbcs20170392 http://creativecommons.org/licenses/by/4.0/ Sociedade Brasileira de Ciência do Solo fulltext |
| spellingShingle | Demattê, J. Guimarães, C. Fongaro, C. Vidoy, E. Sayão, V. Dotto, Andre C. dos Santos, N. Satellite Spectral Data on the Quantification of Soil Particle Size from Different Geographic Regions |
| title | Satellite Spectral Data on the Quantification of Soil Particle Size from Different Geographic Regions |
| title_full | Satellite Spectral Data on the Quantification of Soil Particle Size from Different Geographic Regions |
| title_fullStr | Satellite Spectral Data on the Quantification of Soil Particle Size from Different Geographic Regions |
| title_full_unstemmed | Satellite Spectral Data on the Quantification of Soil Particle Size from Different Geographic Regions |
| title_short | Satellite Spectral Data on the Quantification of Soil Particle Size from Different Geographic Regions |
| title_sort | satellite spectral data on the quantification of soil particle size from different geographic regions |
| url | http://hdl.handle.net/20.500.11937/76328 |