The Capabilities of Optical and C-Band Radar Satellite Data to Detect and Understand Faba Bean Phenology over a 6-Year Period

This study analyzes the potential of optical and radar satellite data to monitor faba bean (<i>Vicia faba</i> L.) phenology over six years (2016–2021) in southwestern France. Using Sentinel-1, Sentinel-2, and Landsat-8 data, temporal variations in NDVI and radar backscatter coefficients...

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Bibliographic Details
Main Authors: Frédéric Baup, Rémy Fieuzal, Clément Battista, Herivanona Ramiakatrarivony, Louis Tournier, Serigne-Fallou Diarra, Serge Riazanoff, Frédéric Frappart
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Remote Sensing
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Online Access:https://www.mdpi.com/2072-4292/17/11/1933
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Summary:This study analyzes the potential of optical and radar satellite data to monitor faba bean (<i>Vicia faba</i> L.) phenology over six years (2016–2021) in southwestern France. Using Sentinel-1, Sentinel-2, and Landsat-8 data, temporal variations in NDVI and radar backscatter coefficients (γ<sup>0</sup><sub>VV</sub>, γ<sup>0</sup><sub>VH</sub>, and γ<sup>0</sup><sub>VH/VV</sub>) are examined to assess crop growth, detect anomalies, and evaluate the impact of climatic conditions and sowing strategies. The results show that NDVI and the radar ratio (γ<sup>0</sup><sub>VH/VV</sub>) were suited to monitor faba bean phenology, with distinct growth phases observed annually. NDVI provides a clear seasonal pattern but is affected by cloud cover, while radar backscatter offers continuous monitoring, making their combination highly beneficial. The signal γ<sup>0</sup><sub>VH/VV</sub> exhibits well-marked correlations with NDVI (r = 0.81) and LAI (r = 0.83), particularly in orbit 30, which provides greater sensitivity to vegetation changes. The analysis of individual fields (inter-field approach) reveals variations in sowing strategies, with both autumn and spring plantings detected. Fields sown in autumn show early NDVI (and γ<sup>0</sup><sub>VH/VV</sub>) increases, while spring-sown fields display delayed growth patterns. This study also highlights the impact of climatic factors, such as precipitation and temperature, on inter-annual variability. Moreover, faba beans used as an intercropping species exhibit a shorter and more intense growth cycle, with a rapid NDVI (and γ<sup>0</sup><sub>VH/VV</sub>) increase and an earlier end of the vegetative cycle compared to standard rotations. Double logistic modeling successfully reconstructs temporal trends, achieving high accuracy (r > 0.95 and rRMSE < 9% for γ<sup>0</sup><sub>VH/VV</sub> signals and r > 0.89 and rRMSE < 15% for NDVI). These double logistic functions are capable of reproducing the differences in phenological development observed between fields and years, providing a reference set of functions that can be used to monitor the phenological development of faba beans in real time. Future applications could extend this methodology to other crops and explore alternative radar systems for improved monitoring (such as TerraSAR-X, Cosmos-SkyMed, ALOS-2/PALSAR, NISAR, ROSE-L…).
ISSN:2072-4292