Time Series of Sentinel-1 Interferometric Coherence and Backscatter for Crop-Type Mapping
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Título: | Time Series of Sentinel-1 Interferometric Coherence and Backscatter for Crop-Type Mapping |
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Autor/es: | Mestre-Quereda, Alejandro | Lopez-Sanchez, Juan M. | Vicente-Guijalba, Fernando | Jacob, Alexander W. | Engdahl, Marcus E. |
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: | Crop classification | Synthetic aperture radar | Interferometry | Agriculture |
Área/s de conocimiento: | Teoría de la Señal y Comunicaciones |
Fecha de publicación: | 9-jul-2020 |
Editor: | IEEE |
Cita bibliográfica: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2020, 13: 4070-4084. doi:10.1109/JSTARS.2020.3008096 |
Resumen: | The potential use of the interferometric coherence measured with Sentinel-1 satellites as input feature for crop classification is explored in this study. A one-year time series of Sentinel-1 images acquired over an agricultural area in Spain, in which 17 crop species are present, is exploited for this purpose. Different options regarding temporal baselines, polarisation, and combination with radiometric data (backscattering coefficient) are analysed. Results show that both radiometric and interferometric features provide notable classification accuracy when used individually (overall accuracy lies between 70% and 80%). It is found that the shortest temporal baseline coherences (6 days) and the use of all available intensity images perform best, hence proving the advantage of the 6-day revisit time provided by the Sentinel-1 constellation with respect to longer revisit times. It is also shown that dual-pol data always provide better classification results than single-pol ones. More importantly, when both coherence and backscattering coefficient are jointly used, a significant increase of accuracy is obtained (greater than 7% in overall accuracy). Individual accuracies of all crop types are increased, and an overall accuracy above 86% is reached. This proves that both features provide complementary information, and that the combination of interferometric and radiometric radar data constitute a solid information source for this application. |
Patrocinador/es: | This work was supported in part by the European Space Agency via the ESA SEOM Program ITT under Grant AO/1-8306/15/I-NB “SEOM-S14SCI Land,” and in part by the Spanish Ministry of Science, Innovation and Universities, the State Agency of Research (AEI), and the European Funds for Regional Development (EFRD) under Project TEC2017-85244-C2-1-P. |
URI: | http://hdl.handle.net/10045/108080 |
ISSN: | 1939-1404 (Print) | 2151-1535 (Online) |
DOI: | 10.1109/JSTARS.2020.3008096 |
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.2020.3008096 |
Aparece en las colecciones: | INV - SST - Artículos de Revistas |
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Archivo | Descripción | Tamaño | Formato | |
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Mestre-Quereda_etal_2020_IEEE-JSTAEORS.pdf | 11,06 MB | Adobe PDF | Abrir Vista previa | |
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