<p>Marine plastic pollution significantly threatens marine ecosystems, particularly in the North Indian Ocean, where densely populated coastal regions and major rivers contribute substantial plastic waste. This study focused on the synergistic potential of optical and thermal remote sensing data to detect and map floating plastic debris in the North Indian Ocean. Using Sentinel-2 multispectral imagery and Landsat-8 Thermal Infrared Sensor (TIRS) data, we applied two spectral indices—the Floating Debris Index (FDI) and the Plastic Index (PI)—to differentiate plastic debris from water and vegetation. A total of 50 high-quality, cloud-free scenes from 2017 to 2024 were analysed, with temporal and spatial synchronisation between Sentinel-2 and Landsat-8 datasets. The FDI demonstrated superior performance in isolating floating plastics, effectively visualising filamentous structures indicative of high debris density. In contrast, the PI, while capable of detecting plastics, exhibited lower sensitivity, serving as a complementary tool. Additionally, the brightness temperature (BT) derived from Landsat-8 TIRS data revealed a strong correlation between thermal gradients and plastic accumulation, along with thermal gradients showing higher debris concentrations due to buoyancy effects. The integration of spectral and thermal data provided a robust framework for identifying plastic hotspots, offering valuable insights into environmental monitoring and pollution mitigation. This study highlights the potential of combining optical and thermal remote sensing for marine plastic detection, particularly in data-scarce regions like the Indian Ocean, and highlights the importance of temperature-driven ocean dynamics in debris distribution. As part of future research, ground-truth data will be used to validate results, and high-resolution satellite images and advanced machine learning algorithms will be used for marine plastic detection.</p>