## 4 Conclusions  
The main intention of this study monitors spatiotemporal TSS concentration over Teluk Lipat Malaysia utilizing Landsat 8 datasets. The three earlier stated objectives were successfully achieved. In this study, the regional TSS algorithm with regression coefficient, R\({}^{2}\) = 0.79 utilizing three Landsat 8 channels (Green, NIR, and SWIR), was successfully developed and validated. The regression statistics model between laboratory-derived in situ value and model-fitted TSS concentration value of the validation points revealed a strong correlation with R\({}^{2}\) = 0.8406, RMSE of 1.50 mg/L, and MRE = 9.14%. The TSS map is constructed using the developed algorithm. Analyses of the map suggested that most of the suspended sediment was distributed along the coastal line and over the river mouth. It is suggested that the TSS in this area are mostly transported by the river and induced by the wave. Others identified that the suspended, induced factors are sand dredging activities and embarkment projects. This study successfully and clearly determined the direction of sediment transport. Thus, these variables ought to be considered in future studies to make strides in the adaptiveness of the demonstrated assistance. TSS in coastal waters continuously and significantly shifts in the daytime due to water runoff, diurnal tidal periodicity, human exercises, and coming within the deficient, worldly determination of these sensors. This issue postures one of the restrictions in giving a high-accuracy strategy for checking TSS concentration in coastal ranges. Therefore, the researchers suggest that a similar study needs to be conducted in a different location for comparison. This study suggests that a similar study in Penang, Malaysia, would be useful as it is currently active in the reclamation activities and has higher effects on coastline changes, socio-economic and development issues. The basic comparison may provide a better understanding of the aptness of the assessment method of models.  
**Author Contributions:** Formal analysis, A.R.M.A.; Funding acquisition, M.S.T.; Methodology, F.N.A.S.; Resources, N.H.B.J. and A.R.M.A.; Supervision, A.A. and A.R.M.A.; Validation, F.N.A.S.; Visualization, M.S.T. and A.A.; Writing--original draft, F.N.A.S.; Writing--review & editing, F.N.A.S., N.H.B.J. and A.R.M.A. All authors have read and agreed to the published version of the manuscript.  
This project was funded by Prime Minister Department through Socio Economy Grant Project No.100-IRMI/GOV 16/6/2 (001/2017) and the Ministry of Higher Education (MOHE) Malaysia through the Fundamental Research Grant Scheme (FRGS) Project No. FRGS/1/2017/STG09 /UITM/02/1.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** Not applicable.  
**Acknowledgments:** We would like to thank UiTM management for their support and encouragement. Our appreciation also goes to the Landsat team for all the valuable data provided. We also like to thank staff of Central of Research and Field Service (CRAFS) Laboratory UMT for their valuable contribution.  
**Conflicts of Interest:** The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.