Using the surface scattering mechanism from dual-pol SAR data to estimate topsoil particle-sizefractions
Data extracted from Synthetic Aperture Radar (SAR) have been widely employed to estimate soil properties. However, these studies are typically constrained to bare soil conditions, as soil information retrieval in vegetated areas remains challenging. Polarimetric decomposition has emerged as a potent...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-04-01
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| Series: | International Journal of Applied Earth Observations and Geoinformation |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1569843224000967 |
| _version_ | 1797224345814171648 |
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| author | Sandra Cristina Deodoro Rafael de Andrade Moral Réamonn Fealy Tim McCarthy Rowan Fealy |
| author_facet | Sandra Cristina Deodoro Rafael de Andrade Moral Réamonn Fealy Tim McCarthy Rowan Fealy |
| author_sort | Sandra Cristina Deodoro |
| collection | DOAJ |
| description | Data extracted from Synthetic Aperture Radar (SAR) have been widely employed to estimate soil properties. However, these studies are typically constrained to bare soil conditions, as soil information retrieval in vegetated areas remains challenging. Polarimetric decomposition has emerged as a potentially useful method to separate the scattering contributions of different targets (e.g. canopy/leaves and the underlying soil), which is of significance for areas that are near-permanently covered in low-lying vegetation (e.g. grass) like Ireland – the study area for this investigation. Here, we test the surface scattering mechanism, derived from H-alpha dual-pol decomposition, together with other covariates, to estimate percentages of sand, silt, and clay, over vegetated terrain, using Sentinel 1 data (dual-pol C-band SAR). The statistical modelling approaches evaluated – linear regression (LRM) and tree-based regression models (machine learning) – explicitly consider the compositional nature of soil texture. When compared to the models fitted without surface scattering data, results showed that the inclusion of the surface scattering data improved estimates of silt and clay, with the compositional linear regression model, and estimates of sand and silt fractions with different tree-based models. While not without limitations, our study demonstrated that the polarimetric decomposition method, which is typically used for classification and segmentation purposes, could also be used for soil property estimation, broadening the application of this technique in microwave remote sensing studies. |
| first_indexed | 2024-03-07T15:47:37Z |
| format | Article |
| id | doaj.art-89fb24603ab84a30a0cda075acd8a71e |
| institution | Directory Open Access Journal |
| issn | 1569-8432 |
| language | English |
| last_indexed | 2024-04-24T13:51:39Z |
| publishDate | 2024-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Applied Earth Observations and Geoinformation |
| spelling | doaj.art-89fb24603ab84a30a0cda075acd8a71e2024-04-04T05:03:42ZengElsevierInternational Journal of Applied Earth Observations and Geoinformation1569-84322024-04-01128103742Using the surface scattering mechanism from dual-pol SAR data to estimate topsoil particle-sizefractionsSandra Cristina Deodoro0Rafael de Andrade Moral1Réamonn Fealy2Tim McCarthy3Rowan Fealy4Irish Climate Analysis and Research Units (ICARUS), Department of Geography, Maynooth University, Co. Kildare, Ireland; Corresponding author at: Irish Climate Analysis and Research Units-ICARUS, Laraghbryan House, North Campus, Maynooth University, Maynooth, Co. Kildare, Ireland.Department of Mathematics & Statistics, Maynooth University, Co. Kildare, IrelandTeagasc Agrifood Business and Spatial Analysis Department, Ashtown, Co. Dublin, IrelandNational Centre for Geocomputation, Maynooth University, Co. Kildare, IrelandIrish Climate Analysis and Research Units (ICARUS), Department of Geography, Maynooth University, Co. Kildare, IrelandData extracted from Synthetic Aperture Radar (SAR) have been widely employed to estimate soil properties. However, these studies are typically constrained to bare soil conditions, as soil information retrieval in vegetated areas remains challenging. Polarimetric decomposition has emerged as a potentially useful method to separate the scattering contributions of different targets (e.g. canopy/leaves and the underlying soil), which is of significance for areas that are near-permanently covered in low-lying vegetation (e.g. grass) like Ireland – the study area for this investigation. Here, we test the surface scattering mechanism, derived from H-alpha dual-pol decomposition, together with other covariates, to estimate percentages of sand, silt, and clay, over vegetated terrain, using Sentinel 1 data (dual-pol C-band SAR). The statistical modelling approaches evaluated – linear regression (LRM) and tree-based regression models (machine learning) – explicitly consider the compositional nature of soil texture. When compared to the models fitted without surface scattering data, results showed that the inclusion of the surface scattering data improved estimates of silt and clay, with the compositional linear regression model, and estimates of sand and silt fractions with different tree-based models. While not without limitations, our study demonstrated that the polarimetric decomposition method, which is typically used for classification and segmentation purposes, could also be used for soil property estimation, broadening the application of this technique in microwave remote sensing studies.http://www.sciencedirect.com/science/article/pii/S1569843224000967Dual-polarimetric decompositionH-alpha decompositionSentinel 1SandSiltClay |
| spellingShingle | Sandra Cristina Deodoro Rafael de Andrade Moral Réamonn Fealy Tim McCarthy Rowan Fealy Using the surface scattering mechanism from dual-pol SAR data to estimate topsoil particle-sizefractions International Journal of Applied Earth Observations and Geoinformation Dual-polarimetric decomposition H-alpha decomposition Sentinel 1 Sand Silt Clay |
| title | Using the surface scattering mechanism from dual-pol SAR data to estimate topsoil particle-sizefractions |
| title_full | Using the surface scattering mechanism from dual-pol SAR data to estimate topsoil particle-sizefractions |
| title_fullStr | Using the surface scattering mechanism from dual-pol SAR data to estimate topsoil particle-sizefractions |
| title_full_unstemmed | Using the surface scattering mechanism from dual-pol SAR data to estimate topsoil particle-sizefractions |
| title_short | Using the surface scattering mechanism from dual-pol SAR data to estimate topsoil particle-sizefractions |
| title_sort | using the surface scattering mechanism from dual pol sar data to estimate topsoil particle sizefractions |
| topic | Dual-polarimetric decomposition H-alpha decomposition Sentinel 1 Sand Silt Clay |
| url | http://www.sciencedirect.com/science/article/pii/S1569843224000967 |
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