Spectral Based Modeling and Spatiotemporal Monitoring of Physical and Chemical Water Quality Parameters of Inland Lakes an Integrated Remote Sensing and Deep Learning Techniques

Abstract

Monitoring water quality is of great importance due to its close connection newlineto both human health and the vitality of ecosystems. The efficient and effective water newlineresources management has posed a significant difficulty, particularly considering the newlinemounting demands stemming from population expansion, industrial development, and newlinealterations in climatic patterns. Historically, conventional techniques for monitoring newlinewater quality have depended on laborious sampling and analysis conducted in a newlinelaboratory setting. This methodology has the potential to incur significant temporal and newlinefinancial costs, and may also be restricted by spatial constraints. Remote sensing newlinemethodologies offer significant insights for water quality surveillance at a broad scope. newlineThe precision and timeliness of monitoring water quality have been significantly newlineimproved by applying deep-learning models to data obtained through Remote Sensing newline