Enhancing the accuracy of retrieving quantities of turbidity and total suspended solids using Landsat-8-based-principal component analysis technique

Estimation of surface water quality parameters (SWQPs) from satellite imagery is a cost-effective method. Remote sensing algorithms are developed to map the relationship between satellite reflectance and concentrations of SWQPs. This study exploited principal component analysis (PCA) to decorrelate multispectral bands prior to developing algorithms for SWQPs. Landsat-8 surface reflectances are first achieved, then, principal components are extracted to develop algorithms for turbidity and total suspended solids (TSS). The developed Landsat-8-based-PCA technique enhanced the accuracy of retrieving concentrations of turbidity and TSS by 12.585% and 12.626%, respectively. These findings demonstrated the significant use of Landsat-8-based-PCA technique to consider/estimate other SWQPs.