ABSTRACT Particulate organic carbon (POC) plays a crucial role in the carbon cycle of inland lake ecosystems. The utilization of remote sensing satellite data provides an effective approach for monitoring the temporal and spatial variations in POC concentration within inland water. However, Erhai Lake, situated in the unique natural environment of the Yunnan-Kweichow Plateau, poses distinct challenges due to the complex and diverse origin of its water quality elements. Existing methods face difficulties in accurately detecting POC concentration in Erhai Lake. In this study, 112 water samples and 574 in-situ remote sensing reflectance curves were collected from Erhai Lake during April, May, and June 2023. The analysis of the optical characteristics of the water in Erhai Lake revealed the closest relationship between the concentration of total particulate matter and POC. Consequently, a POC concentration inversion algorithm was developed, utilizing bands 8, 12, and 16 of Sentinel-3 Ocean and Land Colour Instrument (OLCI). Various POC concentration inversion algorithms were evaluated utilizing a separate dataset. The results indicate that the three-band method offers superior accuracy in POC concentration inversion for Erhai Lake, with a root mean square error (RMSE) of 0.13 mg/L and a mean absolute percentage error (MAPE) of 28.80%. The three-band method was effectively applied to OLCI images from April, May, and June 2023, enabling the analysis of the spatiotemporal distribution of POC in Erhai Lake.