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We propose a normalized difference chlorophyll index (NDCI) to predict chlorophyll-a (chl-a) concentration from remote sensing data in estuarine and coastal turbid productive (case 2) waters. NDCI calibration and validation results derived from simulated and MEdium Resolution Imaging Spectrometer (MERIS) datasets show its potential application to widely varying water types and geographic regions. A quadratic function (R²=0.95, p<0.0001) accurately explained the variance in the simulated data for a chl-a range of 1–60mgm⁻³. Similarly a twofold calibration and validation of chl-a models using MERIS dataset, (chl-a range: 0.9–28.1mgm⁻³) yielded R² of 0.9, and RMSE of ~2mgm⁻³ respectively. NDCI was applied on images over the Chesapeake Bay and Delaware Bay, the Mobile Bay, and the Mississippi River delta region in the northern Gulf of Mexico. The newly developed algorithm was successful in …