SATELLITE-DRIVEN ASSESSMENT OF TOTAL ORGANIC CARBON AND DISSOLVED SOLIDS USING ARTIFICIAL INTELLIGENCE: CODE DEVELOPMENT AND IMPLEMENTATION

Water is a fundamental resource for life and the progression of human civilization.The escalating global population and its growing demand for clean water are posing significant challenges to the existing water resources.Regular monitoring of water bodies and large-scale estimation of Surface Water Quality Parameters (SWQPs) is crucial; conversely, remote sensing provides extensive spatial and temporal coverage.This study integrates satellite data, Artificial Neural Networks (ANNs), and ground truth water quality data for modelling SWQPs.Initially, atmospheric correction algorithms, including Fast Line of Sight Atmospheric Analysis of Hypercubes (FLAASH)