Abstract

Water quality has a significant impact on aquaculture productivity. Water quality characteristics influence fishing production. This study employs numerous prior research techniques to assess air quality factors such as Total Suspend Solid (TSS), salinity, Sea Surface Temperature (SST), and dissolved oxygen. However, physical elements such as rainfall, which are separated into wet and dry months in this study, have an impact on water quality. The approach was developed using Landsat-8 OLI satellite images. The algorithm's output is validated for data accuracy using Pearson correlation, root mean square error (RMSE), and R-square. The findings suggest that the distribution of water quality in dry and rainy months is low in coastal areas and high in locations adjacent to open waters. Furthermore, it was discovered that the average value of the distribution of TSS in dry months was lower than in wet months, the mean value of the distribution of salinity in dry months was higher than in wet months, the average value of the SST distribution in dry months was higher than in wet months, and the mean value of the dissolved oxygen distribution in dry months was lower than in wet months.
 Keywords: Water suitability; Landsat-8; Water Quality; Remote Sensing

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