Rapid unplanned industrialization and urbanization in Bangladesh have led to significant pollution and degradation of freshwater sources, highlighting the need for preservation as a fundamental human right. Untreated wastewater discharged from industries contributes to heavy metal toxicity, posing a significant risk to aquatic organisms, wildlife, and human health. The Meghna River, a potential source of freshwater for the capital city, Dhaka, and the sustainer of diverse aquatic ecosystems and habitats, also serves as a sink for untreated industrial effluents containing heavy metal contaminants. Hence, to mitigate heavy metal contamination and preserve the ecosystem and human health, it is crucial to regularly monitor the water quality and heavy metal concentration of the river. However, using conventional techniques to evaluate heavy metal pollution in large areas like rivers comes with challenges, including inaccessibility, time, and cost. With the advent of advanced remote sensing technologies, using Satellite Earth Observation Data (EO) and correlating high-resolution satellite images and in-situ data offers the potential to assess the pollution level of the study area effectively. In this study, sentinel-2 satellite images were utilized to assess the heavy metal concentration of the Meghna River. Samples were collected during the Monsoon and Post Monsoon period within the proximity of industrial areas near Meghna Bridge, Narayanganj. The laboratory analysis of heavy metal concentration was conducted using the ICP mass spectrometer. Multiple linear regression (MLR) models were established between measured heavy metal concentrations and spectral reflectances of different bands or band ratios at the corresponding sampling points. The equations generated using the MLR were further applied to the satellite images for zoning the concentration level of heavy metal in the study area. The accuracy of the developed models was examined by Pearson correlation coefficients, and the estimated values generated from the model were further compared with the observed values. The results indicated a significant correlation for Hg, Co, Zn, and As with the spectral reflectance data.
                    Previous Article in event
            
                            
    
                    Next Article in event
            
                            Next Article in session
            
                    
                                                    
        
                    Evaluation of Heavy Metal Concentrations in the Vicinity of Industrial Zones along the Meghna River Using Advanced Remote Sensing and Spatial Analysis Techniques
                
                                    
                
                
                    Published:
16 May 2024
by MDPI
in OHOW 2023 – The 2nd International Symposium on One Health, One World
session Climate change and green recovery
                
                
                
                    Abstract: 
                                    
                        Keywords: Heavy Metal, Remote sensing, Sentinel-2, Meghna River, spatial analysis, statistical analysis
                    
                
                
                
                                    Comments on this paper
                                                                            
                                                                                
                                        
                                                                    
                                                    
                                    Free Stein
                            
            
                14 December 2024
            
        
                                    Elianna Gray
                            
            
                6 May 2025
            
        
                With millions of downloads, Geometry Dash Lite is one of the top-rated rhythm games on both Android and iOS platforms.
            
        
                                    Jeffree Star
                            
            
                24 June 2025
            
        
                great i like it
            
        
        
            