Brazil stands as the world's leading coffee producer and exporter, playing a crucial role in global supply. Considering its importance in the national agricultural scenario, this study aims to evaluate the potential of features derived from C-band Synthetic Aperture Radar (C-SAR) Sentinel-1 imagery in detecting structural variations in coffee-growing plots of different cultivars and ages. The research conducts a comparative analysis of SAR polarimetric attributes and the Normalized Difference Vegetation Index (NDVI), utilizing optical imagery from the Multispectral Instrument (MSI) aboard Sentinel-2B. The experimental area is situated within a commercial coffee plantation owned by Fazenda Juliana, near the municipality of Monte Carmelo, Minas Gerais. The farm has supplied precise delimitation of coffee plots, along with detailed records on planting age and cultivars. C-SAR Sentinel-1B were preprocessing using the Sentinel Application Platform (SNAP), generating backscatter coefficients (𝜎⁰) in VH and VV polarizations and key polarimetric indices Cross Ratio (CR), Normalization Ratio (NL), Radar Gap Index (RGI), and Radar Vegetation Index (RVI), were calculated. SAR features and NDVI were segmented by the defined coffee plot boundaries, and for each segmented plot, the mean values of 𝜎⁰ VH, 𝜎⁰ VV, SAR indices, and NDVI were extracted for analysis. The findings demonstrate a strong correlation (>0.9) between NDVI fluctuations and 𝜎⁰ VH and NL variations, underscoring their effectiveness in detecting structural differences across coffee plantations. This approach offers a robust alternative for monitoring crop variability, particularly in areas where optical sensing is constrained.