Progress in Remote Sensing of Heavy Metals in Water

Abstract

This review article details the advancements in detecting heavy metals in aquatic environments using remote sensing methodologies. Heavy metals are significant pollutants in aquatic environment, and their detection and monitoring are crucial for predicting water quality. Traditional in situ water sampling methods are time-consuming and costly, highlighting the advantages of remote sensing techniques. Analysis of the reflectance and absorption characteristics of heavy metals has identified the red and near-infrared bands as the sensitive wavelengths for heavy metal detection in aquatic environments. Several studies have demonstrated a correlation between total suspended matter and heavy metals, which forms the basis for retrieving heavy metal content from TSM data. Recent developments in hyperspectral remote sensing and machine (deep) learning technologies may pave the way for developing more effective heavy metal detection algorithms.

Keywords

• heavy metal
• remote sensing algorithm
• hyperspectral remote sensing
• machine learning method