DETECTION OF TOTAL SUSPENDED SOLIDS DISTRIBUTION USING EMPIRICAL AND SEMI-ANALYTICAL MODELS IN BEKASI
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Bekasi, Google Earth Engine, Landsat 8, TTS, water quality
Abstract
One of the parameters in water quality is total suspended solids (TSS). TSS consists of mud and microorganisms caused by erosion of soil flowed into water bodies. This study aimed to detect suspended sediments in Bekasi coastal water by comparing empirical and semi-analytic models. Landsat 8 was used for analysis of suspended solids using the Google Earth Engine platform. The workflow of this study consisted of land masking by area delineation using surface reflectance image data, TSS analysis, and visualization. Then validation was done with in situ data, model selection and time series implementation. TSS detection results were displayed with a different color display according to the concentration. Validation test results with in situ data showed that the value of the Semi-Analytical Absolute Error (NMAE) model was closer to the minimum requirement of 66.8%, far different from the empirical model of 43768%. The value of Root Mean Square Error (RMSE) also showed that the semi-analytic model produced a much smaller value of 51.4 and the empirical model of 58577.2. This showed that the semi-analytic model has a better value in detecting the distribution of TSS. Time series analysis showed that the distribution of MPT in 2015 - 2019 in coastal waters had a very high TSS distribution, due to the number of ponds and river estuaries. Therefore, semi-analytical model was more recommended for estimating TSS concentrations than empirical model.
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