Harmful cyanobacterial blooms, detrimental to both environmental health and human well-being, are a growing global concern. Addressing this challenge, the present study adopts a dual approach, combining in situ measurements with satellite remote sensing imagery for effective monitoring. The primary objective of this research is to initiate the development of a semi-empirical algorithm specifically designed to quantify cyanobacteria chlorophyll-a concentration in San Roque Lake, Córdoba, Argentina. Notably, this represents the first algorithm of its kind to be developed for this specific water body, which frequently experiences severe blooms. The methodology involved leveraging satellite images from Landsat 8 and 9, acquired concurrently with comprehensive in situ field campaigns. During these campaigns, chlorophyll-a concentration was directly measured, radiometric data were collected, and microscopic algal abundance counts were performed to validate cyanobacteria presence. Among the various relationships explored, the most promising model emerged from the B3/B4 band ratio, yielding a strong coefficient of determination (R2 of 0.6). This developed model was subsequently applied to a satellite image captured during a significant algal bloom event on February 20, 2025. The results demonstrated a clear consistency between the model's chlorophyll predictions and the visual representation of the bloom in the RGB satellite composite. For future work, it is essential to further calibrate and refine this model using a more extensive and diverse dataset, ensuring its robustness and broader applicability for routine monitoring and management of San Roque Lake.