Prediction of topsoil properties at field-scale by using C-band SAR data
Designing and validating digital soil mapping (DSM) techniques can facilitate precision agriculture implementation. This study generates and validates a technique for the spatial prediction of soil properties based on C-band radar data. To this end, (i) we focused on working at farm-field scale and...
| Autores principales: | , , , |
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| Formato: | Artículo |
| Lenguaje: | Inglés |
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Elsevier
2021
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| Acceso en línea: | http://hdl.handle.net/20.500.12123/8888 https://www.sciencedirect.com/science/article/pii/S0303243419311353 https://doi.org/10.1016/j.jag.2020.102197 |
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| author | Domenech, Marisa Amiottia, Nilda Costa, José Luis Castro Franco, Mauricio |
| author_browse | Amiottia, Nilda Castro Franco, Mauricio Costa, José Luis Domenech, Marisa |
| author_facet | Domenech, Marisa Amiottia, Nilda Costa, José Luis Castro Franco, Mauricio |
| author_sort | Domenech, Marisa |
| collection | INTA Digital |
| description | Designing and validating digital soil mapping (DSM) techniques can facilitate precision agriculture implementation. This study generates and validates a technique for the spatial prediction of soil properties based on C-band radar data. To this end, (i) we focused on working at farm-field scale and conditions, a fact scarcely reported; (ii) we validated the usefulness of Random Forest regression (RF) to predict soil properties based on C-band radar data; (iii) we validated the prediction accuracy of C-band radar data according to the coverage condition (for example: crop or fallow); and (iv) we aimed to find spatial relationship between soil apparent electrical conductivity and C-band radar. The experiment was conducted on two agricultural fields in the southern Argentine Pampas. Fifty one Sentinel 1 Level-1 GRD (Grid) products of C-band frequency (5.36 GHz) were processed. VH and VV polarizations and the dual polarization SAR vegetation index (DPSVI) were estimated. Soil information was obtained through regular-grid sample scheme and apparent soil electrical conductivity (ECa) measurements. Soil properties predicted were: texture, effective soil depth, ECa at 0-0.3m depth and ECa at 0-0.9m depth. The effect of water, vegetation and soil on the depolarization from SAR backscattering was analyzed. Complementary, spatial predictions of all soil properties from ordinary cokriging and Conditioned Latin hypercube sampling (cLHS) were evaluated using six different soil sample sizes: 20, 40, 60, 80, 100 and the total of the grid sampling scheme. The results demonstrate that the prediction accuracy of C-band SAR data for most of the soil properties evaluated varies considerably and is closely dependent on the coverage type and weather dynamics. The polarizations with high prediction accuracy of all soil properties showed low values of σVVo and σVHo, while those with low prediction accuracy showed high values of σVVo and low values of σVHo. The spatial patterns among maps of all soil properties using all samples and all sample sizes were similar. In conditions when summer crops demand large amount of water and there is soil water deficit backscattering showed higher prediction accuracy for most soil properties. During the fallow season, the prediction accuracy decreased and the spatial prediction accuracy was closely dependent on the number of validation samples. The findings of this study corroborates that DSM techniques at field scale can be achieved by using C-band SAR data. Extrapolation y applicability of this study to other areas remain to be tested. |
| format | Artículo |
| id | INTA8888 |
| institution | Instituto Nacional de Tecnología Agropecuaria (INTA -Argentina) |
| language | Inglés |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | Elsevier |
| publisherStr | Elsevier |
| record_format | dspace |
| spelling | INTA88882021-03-15T11:33:38Z Prediction of topsoil properties at field-scale by using C-band SAR data Domenech, Marisa Amiottia, Nilda Costa, José Luis Castro Franco, Mauricio Suelo Cartografía Agricultura de Precisión Conductividad Eléctrica Radar Muestreo del Suelo Soil Cartography Precision Agriculture Electrical Conductivity Soil Sampling Designing and validating digital soil mapping (DSM) techniques can facilitate precision agriculture implementation. This study generates and validates a technique for the spatial prediction of soil properties based on C-band radar data. To this end, (i) we focused on working at farm-field scale and conditions, a fact scarcely reported; (ii) we validated the usefulness of Random Forest regression (RF) to predict soil properties based on C-band radar data; (iii) we validated the prediction accuracy of C-band radar data according to the coverage condition (for example: crop or fallow); and (iv) we aimed to find spatial relationship between soil apparent electrical conductivity and C-band radar. The experiment was conducted on two agricultural fields in the southern Argentine Pampas. Fifty one Sentinel 1 Level-1 GRD (Grid) products of C-band frequency (5.36 GHz) were processed. VH and VV polarizations and the dual polarization SAR vegetation index (DPSVI) were estimated. Soil information was obtained through regular-grid sample scheme and apparent soil electrical conductivity (ECa) measurements. Soil properties predicted were: texture, effective soil depth, ECa at 0-0.3m depth and ECa at 0-0.9m depth. The effect of water, vegetation and soil on the depolarization from SAR backscattering was analyzed. Complementary, spatial predictions of all soil properties from ordinary cokriging and Conditioned Latin hypercube sampling (cLHS) were evaluated using six different soil sample sizes: 20, 40, 60, 80, 100 and the total of the grid sampling scheme. The results demonstrate that the prediction accuracy of C-band SAR data for most of the soil properties evaluated varies considerably and is closely dependent on the coverage type and weather dynamics. The polarizations with high prediction accuracy of all soil properties showed low values of σVVo and σVHo, while those with low prediction accuracy showed high values of σVVo and low values of σVHo. The spatial patterns among maps of all soil properties using all samples and all sample sizes were similar. In conditions when summer crops demand large amount of water and there is soil water deficit backscattering showed higher prediction accuracy for most soil properties. During the fallow season, the prediction accuracy decreased and the spatial prediction accuracy was closely dependent on the number of validation samples. The findings of this study corroborates that DSM techniques at field scale can be achieved by using C-band SAR data. Extrapolation y applicability of this study to other areas remain to be tested. EEA Balcarce Fil: Domenech, Marisa. Universidad Nacional del Sur. Departamento de Agronomía; Argentina. Fil: Amiottia, Nilda. Universidad Nacional del Sur. Departamento de Agronomía; Argentina. Fil: Amiottia, Nilda. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Fil: Costa, José Luis. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentina. Fil: Castro-Franco, Mauricio. Centro de Investigaciones de la Caña de Azúcar de Colombia. Estación Experimental Estación Experimental vía Cali-Florida; Colombia. 2021-03-15T11:06:30Z 2021-03-15T11:06:30Z 2020-07-10 info:ar-repo/semantics/artículo info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://hdl.handle.net/20.500.12123/8888 https://www.sciencedirect.com/science/article/pii/S0303243419311353 0303-2434 https://doi.org/10.1016/j.jag.2020.102197 eng info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) application/pdf Elsevier International Journal of Applied Earth Observation and Geoinformation 93 : 102197 (December 2020) |
| spellingShingle | Suelo Cartografía Agricultura de Precisión Conductividad Eléctrica Radar Muestreo del Suelo Soil Cartography Precision Agriculture Electrical Conductivity Soil Sampling Domenech, Marisa Amiottia, Nilda Costa, José Luis Castro Franco, Mauricio Prediction of topsoil properties at field-scale by using C-band SAR data |
| title | Prediction of topsoil properties at field-scale by using C-band SAR data |
| title_full | Prediction of topsoil properties at field-scale by using C-band SAR data |
| title_fullStr | Prediction of topsoil properties at field-scale by using C-band SAR data |
| title_full_unstemmed | Prediction of topsoil properties at field-scale by using C-band SAR data |
| title_short | Prediction of topsoil properties at field-scale by using C-band SAR data |
| title_sort | prediction of topsoil properties at field scale by using c band sar data |
| topic | Suelo Cartografía Agricultura de Precisión Conductividad Eléctrica Radar Muestreo del Suelo Soil Cartography Precision Agriculture Electrical Conductivity Soil Sampling |
| url | http://hdl.handle.net/20.500.12123/8888 https://www.sciencedirect.com/science/article/pii/S0303243419311353 https://doi.org/10.1016/j.jag.2020.102197 |
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