The traditional sampling method for environmental monitoring of aerosols is time consuming and expensive. Remote sensing data have been widely used in environmental studies like land cover change, flood observation, environmental pollution monitoring. This study is dealing with obtaining water pollution using Landsat TM data over Penang Strait, Malaysia. With the availability of remotely sensed and in situ data sets the derivable geophysical parameters is sediment (suspended matter) concentration. The proposed algorithm is based on the reflectance model that is a function of the inherent optical properties of water, which can be related to its constituent's concentrations. Regression and accuracy analysis is performed using SPSS analysis software. Water samples locations were determined using a handheld GPS. The digital numbers were extracted corresponding to the ground-truth locations for each band was converted into radiance and reflectance and later used for the calibration of the developed algorithm. The efficiency of the present proposed algorithm, in comparison to other forms of algorithm, was also investigated. Based on the values of the correlation coefficient (R) and root-mean-square deviation (RMS), the proposed algorithm is considered superior. The proposed algorithm is considered superior to other tested algorithms based on the values of the correlation coefficient, R=0.94 and root-mean-square error, RMS=5 mg/l. The calibrated TSS algorithm was used to generate the water quality map. The TSS map was color-coded and geometrically corrected for visual interpretation.