Busquierand, M. ; Lopez-Sanchez, Juan M. ; Bargiel, D. (2019)
Added Value of Coherent Copolar Polarimetry at X-Band for Crop-Type Mapping.
In: IEEE Geoscience and Remote Sensing Letters
doi: 10.1109/LGRS.2019.2933738
Article, Bibliographie
Abstract
A set of six spotlight TerraSAR-X images acquired at HH and VV polarizations in 2009 over an agricultural site in Germany are employed to evaluate the potential contribution of polarimetric features derived from this copolar mode to crop-type mapping. Results show that the inclusion of the correlation between copolar channels in the set of input features of the classifier consistently improves the classification performance with respect to the use of only backscattering coefficients. An increase around 8-10 in overall accuracy, depending on the experiment setup, is achieved. Both user and producer accuracies are improved for all crop types, being the most noticeable contribution for barley, oat, and sugar beet. Different sets of input features, as well as classification and evaluation strategies, are tested in order to assess the robustness of this contribution.
| Item Type: | Article |
|---|---|
| Erschienen: | 2019 |
| Creators: | Busquierand, M. ; Lopez-Sanchez, Juan M. ; Bargiel, D. |
| Type of entry: | Bibliographie |
| Title: | Added Value of Coherent Copolar Polarimetry at X-Band for Crop-Type Mapping |
| Language: | English |
| Date: | 21 August 2019 |
| Publisher: | IEEE |
| Journal or Publication Title: | IEEE Geoscience and Remote Sensing Letters |
| DOI: | 10.1109/LGRS.2019.2933738 |
| URL / URN: | https://ieeexplore.ieee.org/abstract/document/8809193 |
| Corresponding Links: | |
| Abstract: | A set of six spotlight TerraSAR-X images acquired at HH and VV polarizations in 2009 over an agricultural site in Germany are employed to evaluate the potential contribution of polarimetric features derived from this copolar mode to crop-type mapping. Results show that the inclusion of the correlation between copolar channels in the set of input features of the classifier consistently improves the classification performance with respect to the use of only backscattering coefficients. An increase around 8-10 in overall accuracy, depending on the experiment setup, is achieved. Both user and producer accuracies are improved for all crop types, being the most noticeable contribution for barley, oat, and sugar beet. Different sets of input features, as well as classification and evaluation strategies, are tested in order to assess the robustness of this contribution. |
| Uncontrolled Keywords: | Agriculture, Correlation, Training, Backscatter, Testing, Polarimetry, Synthetic aperture radar, Agriculture, classification, polarimetry, synthetic aperture radar (SAR) |
| Divisions: | 13 Department of Civil and Environmental Engineering Sciences 13 Department of Civil and Environmental Engineering Sciences > Institute of Geodesy 13 Department of Civil and Environmental Engineering Sciences > Institute of Geodesy > Remote Sensing and Image Analysis |
| Date Deposited: | 04 Oct 2019 06:28 |
| Last Modified: | 04 Oct 2019 06:28 |
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