<p>The Marine Atmospheric Boundary Layer (MABL) is the lowest part of the troposphere over the ocean, where atmospheric and sea interactions drive air-sea exchange and pollutant dispersion, particularly near coastal regions. The MABL roll, or longitudinal roll vortex, is an important feature of the MABL. The MABL rolls enhance turbulent exchange within the boundary layer and affect storm development and intensification, particularly in tropical regions such as the Indian Ocean. Satellite-based Synthetic Aperture Radar (SAR) imagery is an effective tool for detecting and analyzing the MABL by sensing wind-induced variations in sea-surface roughness. This review paper synthesizes past and present studies on MABL roll detection and characterization using SAR imagery. The two-dimensional fast Fourier transform (2D-FFT), wavelet-based spectral analyses, backscatter (NRCS) modelling, Doppler centroid shift techniques alongside emerging artificial intelligence (AI) and machine learning (ML) approaches, including convolutional neural networks (CNNs) for automated feature extraction, are examined. NASA-ISRO NISAR data provide an excellent opportunity to monitor MABL rolls over the Indian Ocean using dual-frequency (L- and S-band) polarimetric SAR data at 3–10&#xa0;m resolution. This review covers NISAR’s key developments and their advantages for roll studies. This review also discusses the challenges and future directions of operational monitoring strategies, including theoretical and AI/ML-based MABL dynamics models for air-sea interaction forecasting using satellite imagery data.</p>