Assessment of the Impact of Long Integration Time in Geosynchronous SAR Imagery of Agricultural Fields by Means of GB-SAR Data
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Título: | Assessment of the Impact of Long Integration Time in Geosynchronous SAR Imagery of Agricultural Fields by Means of GB-SAR Data |
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Autor/es: | Aguasca, Albert | Broquetas, Antoni | Lopez-Sanchez, Juan M. | Fàbregas, Xavier | Mallorquí Franquet, Jordi J. | Mas, Mireia |
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: | Geosynchronous Synthetic Aperture Radar | Backscattering | Integration Time | Coherence Amplitude | Scene Decorrelation |
Fecha de publicación: | 1-dic-2023 |
Editor: | IEEE |
Cita bibliográfica: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2024, 17: 1338-1347. https://doi.org/10.1109/JSTARS.2023.3338468 |
Resumen: | Geosynchronous Synthetic Aperture Radar (GeoSAR) missions offer the advantage of near-continuous monitoring of specific regions on Earth, making them essential for applications that require continuous information. However, wind induced motion along the inherent long integration time can result in image defocusing, with potential degradation of retrieved information. This paper aims to investigate the impact of GEOSAR long integration time in Synthetic Aperture Radar (SAR) imaging and derived products (time series of backscatter and coherence) required to extract agriculture relevant soil or crop parameters of interest. The study is based on the extensive HydroSoil data acquisition campaign carried out over barley and corn crops, funded by the European Space Agency (ESA). The collected raw data are used to synthesize equivalent apertures with integration times of up to 4 hours, similar to those acquired with a GeoSAR. These Ultra Slow apertures facilitate the assessment of the impact of agricultural scene decorrelation on the generation of images with extended integration times. |
Patrocinador/es: | This work was funded by the European Space Agency (ESA Contract No. 4000132509/20/NL/FF/ab with UPC), supported by the Spanish MCINN funds Unidad de Excelencia Maria de Maeztu MDM-2016-0600 and under projects PID2020-117303GB-C21/AEI/10.13039/501100011033 and PID2020-117303GB-C22/AEI/10.13039/501100011033. |
URI: | http://hdl.handle.net/10045/139130 |
ISSN: | 1939-1404 (Print) | 2151-1535 (Online) |
DOI: | 10.1109/JSTARS.2023.3338468 |
Idioma: | eng |
Tipo: | info:eu-repo/semantics/article |
Derechos: | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. For more information, see https://creativecommons.org/licenses/by-nc-nd/4.0/ |
Revisión científica: | si |
Versión del editor: | https://doi.org/10.1109/JSTARS.2023.3338468 |
Aparece en las colecciones: | INV - SST - Artículos de Revistas |
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Archivo | Descripción | Tamaño | Formato | |
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Aguasca_etal_2024_IEEE-JSTARS.pdf.pdf | 9,78 MB | Adobe PDF | Abrir Vista previa | |
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