Sentinel-1 interferometric coherence as a vegetation index for agriculture
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Título: | Sentinel-1 interferometric coherence as a vegetation index for agriculture |
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Autor/es: | Villarroya-Carpio, Arturo | Lopez-Sanchez, Juan M. | 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: | Agriculture | Sentinel-1 | Synthetic aperture radar (SAR) | Interferometry | Coherence | Vegetation index | NDVI |
Fecha de publicación: | 16-ago-2022 |
Editor: | Elsevier |
Cita bibliográfica: | Remote Sensing of Environment. 2022, 280: 113208. https://doi.org/10.1016/j.rse.2022.113208 |
Resumen: | In this study, the use of Sentinel-1 interferometric coherence data as a tool for crop monitoring has been explored. For this purpose, time series of images acquired by Sentinel-1 and 2 spanning 2017 have been analysed. The study site is an agricultural area in Sevilla, Spain, where 16 different crop species were cultivated during that year. The time series of 6-day repeat-pass coherence measured at each polarimetric channel (VV and VH), as well as their difference, have been compared to the NDVI and to the backscattering ratio (VH/VV) and other indices based on backscatter. The contribution of different decorrelation sources and the effect of the bias from the space-averaged sample coherence magnitude estimation have been evaluated. Likewise, the usage of 12 days as temporal baseline was tested. The study has been carried for three different orbits, characterised by different incidence angles and acquisition times. All results support using coherence as a measure for monitoring the crop growing season, as it shows good correlations with the NDVI (R2>0.7), and its temporal evolution fits well the main phenological stages of the crops. Although each crop shows its own evolution, the performance of coherence as a vegetation index is high for most of them. VV is generally more correlated with the NDVI than VH. For crop types characterised by low plant density, this difference decreases, with VH even showing higher correlation values in some cases. For a few crop types, such as rice, the backscattering ratio outperforms the coherence in following the growth stages of the plants. Since both coherence and backscattering are directly computed from the radar images, they could be used as complementary sources of information for this purpose. Notably, the measured coherence performs well without the need of compensating the thermal noise decorrelation or the bias due to the finite equivalent number of looks. |
Patrocinador/es: | This work was supported in part by the European Space Agency under Project SEOM-S14SCI-Land (SInCohMap), 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/10045/126178 |
ISSN: | 0034-4257 (Print) | 1879-0704 (Online) |
DOI: | 10.1016/j.rse.2022.113208 |
Idioma: | eng |
Tipo: | info:eu-repo/semantics/article |
Derechos: | © 2022 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
Revisión científica: | si |
Versión del editor: | https://doi.org/10.1016/j.rse.2022.113208 |
Aparece en las colecciones: | INV - SST - Artículos de Revistas |
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Villarroya-Carpio_etal_2022_RemoteSensingEnviron.pdf | 4,81 MB | Adobe PDF | Abrir Vista previa | |
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