Journal of Experimental Agriculture International

Monitoring crop growth is crucial for sustainable food production, land use efficiency, and agricultural policy. Remote sensing approaches using radar and optical sensors have become significant for obtaining crop-related information. Among remote sensing technologies, Synthetic Aperture Radar (SAR) has emerged as a transformative tool for agricultural monitoring and decision support, owing to its unique ability to provide high-resolution, all-weather, day-and-night imaging. The SAR technology enables precise crop assessment, acreage mapping, disaster damage evaluation, land classification, and soil quality estimation, regardless of cloud cover or lighting conditions. The research on SAR satellite systems has demonstrated the potential for agricultural applications. This is achieved by utilizing the distinct polarimetric signature of different scatterers, as SAR is highly sensitive to agricultural targets' geometric designs and dielectric characteristics. Additionally, SAR possesses the unique ability to penetrate specific agricultural targets, but some areas that require improvement include the temporal and spatial resolution of SAR sensors. Recently, there have been notable improvements in SAR remote sensing devices, leading to a considerable increase in the available SAR data sources (Sentinel series, RADARSAT series, NISAR). The accuracy of crop classification and the extraction of parameters using SAR data has shown steady advancements. Integrating deep learning with SAR data has improved the accuracy of soil moisture and yield estimation. Also, an ensemble of SAR and ORYZA2000 has proven to increase the accuracy of yield prediction. Nevertheless, the progress of modern agriculture has required more significant standards for SAR remote sensing. This study presents a comprehensive examination of recent SAR technology developments, current applications, and ongoing challenges in agricultural monitoring, with an emphasis on the future integration of SAR and optical remote sensing systems for next-generation precision agriculture.