Combination of Time Series of L-, C- and X-Band SAR Images for Land Cover and Crop Classification
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Título: | Combination of Time Series of L-, C- and X-Band SAR Images for Land Cover and Crop Classification |
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Autor/es: | Busquier, Mario | Lopez-Sanchez, Juan M. | Ticconi, Francesca | Floury, Nicolas |
Grupo/s de investigación o GITE: | Señales, Sistemas y Telecomunicación |
Centro, Departamento o Servicio: | Universidad de Alicante. Departamento de Física, Ingeniería de Sistemas y Teoría de la Señal | Universidad de Alicante. Instituto Universitario de Investigación Informática |
Palabras clave: | Synthetic Aperture Radar (SAR) | Land cover classification | Crop classification | Interferometry | Time series |
Fecha de publicación: | 19-sep-2022 |
Editor: | IEEE |
Cita bibliográfica: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2022, 15: 8266-8286. https://doi.org/10.1109/JSTARS.2022.3207574 |
Resumen: | The availability of new Earth observation satellites operating radar sensors at different frequencies enables the combination of multiple dimensions of the data (time, frequency, polarimetry and interferometry) in many applications. Image classification is expected to benefit from the diversity of observation. This work illustrates classification experiments carried out with series of images acquired by ALOS-2 PALSAR (L-band), Sentinel-1 (C-band) and TanDEM-X (X-band) in two application domains: land cover classification and crop-type mapping. Their usage, both separately and in combination, serves to identify the complementarity of information. In this work we propose a new colour representation of the pair-wise class separability in the case of using three frequency bands, which help identify which bands (or combinations of them) provide the best performance. Results in terms of accuracy scores (overall and class-specific) show that the use of the three frequency bands always outperforms the individual bands and their pairs. In addition, for both land classification and crop-type mapping the accuracy of using coherence time series is lower than the one obtained with the intensity time series, but there is complementarity in terms of sensitivity when both coherence and intensity time series are used together. The classes which are most benefited at each particular case of study have been identified. Finally, a partial trade-off has been found between the use of multiple frequency bands and the length of the available time series. |
Patrocinador/es: | This work was supported in part by the European Space Agency under Contract 4000133590/20/NL/AS/hh, and in part by the Spanish Ministry of Science and Innovation (State Agency of Research, AEI) and the European Funds for Regional Development under Project PID2020-117303GB-C22. |
URI: | http://hdl.handle.net/10045/127505 |
ISSN: | 1939-1404 (Print) | 2151-1535 (Online) |
DOI: | 10.1109/JSTARS.2022.3207574 |
Idioma: | eng |
Tipo: | info:eu-repo/semantics/article |
Derechos: | This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/ |
Revisión científica: | si |
Versión del editor: | https://doi.org/10.1109/JSTARS.2022.3207574 |
Aparece en las colecciones: | INV - SST - Artículos de Revistas |
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