Development of Total Suspended Solid (TSS) Estimation Algorithm Using Landsat 9 Satellite Imagery in Cacaban Reservoir Waters

Abdi Sukmono, Arwan Putra Wijaya, Arief Laila Nugraha, Resi Ahdtyas

Abstract


Landsat 9 imagery is an advanced development of the Landsat satellite imagery program. Since it began operating, the Landsat satellite program has been able to map areas both on land and water. The use of remote sensing methods is an efficient method for monitoring water areas. Various approaches have been made to obtain a more accurate method for extracting information about the waters by utilizing satellite imagery. One of the parameters that is often extracted is the distribution of Total Suspended Solid (TSS) parameters in waters. Dynamic changes and different water characteristics cause several available water TSS parameter algorithms to have less than optimal results in other water areas. This study aims to develop an empirical TSS algorithm model that is suitable for the waters of the Cacaban Reservoir by utilizing the correlation between image spectral values and in situ TSS values. The best regression model developed for estimating TSS values is found in the linear regression model with channel ratios 3 and 4. The coefficient of determination for the model is 0.819, RMSE 1.793 mg/L and NMAE 13.1%. The TSS distribution results in the Cacaban Reservoir on 24 May 2022 had a TSS range from 1.13 mg/L to 69.53 mg/L.

Keywords


Algorithm, Landsat 9 imagery, Reservoir Waters, Total Suspended Solid

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References


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DOI: http://dx.doi.org/10.52155/ijpsat.v38.1.5226

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