Download PDFOpen PDF in browserSatellite Image Based Monitoring System for Water QualityEasyChair Preprint 1006410 pages•Date: May 10, 2023AbstractMonitoring water quality is crucial for preserving the natural balance and protecting public health. Traditional approaches to water quality monitoring, however, can take a long time, cost a lot of money, and need a lot of fieldwork. Due to its capacity to provide extensive and regular observations, satellite remote sensing has lately become a potential technique for water quality monitoring. We describe a satellite image-based water quality monitoring system in this study that makes use of the most recent developments in remote sensing technology. To calculate water quality measures including turbidity, chlorophyll-a, and total suspended solids, the method leverages multispectral satellite images. Real-time data on water quality will be made available via the proposed system, which may be utilised for early warning, decision-making, and resource management. According to our first findings, the system is capable of reliably estimating water quality metrics and spotting irregularities in water bodies. The suggested technology might completely alter how water quality is monitored and contribute to the preservation of water bodies' quality. The ability of satellite image-based water quality monitoring systems to deliver continuous spatial and temporal information on water quality parameters has attracted growing attention in recent years. This study describes the creation and assessment of a satellite-based water quality monitoring system based on Landsat 8 imagery. The system was created to keep track of the turbidity, total suspended solids (TSS), and chlorophyll-a (Chl-a) levels in a reservoir. Using empirical models, the methodology involved gathering and processing Landsat 8 imagery to extract water quality parameters. The findings demonstrated that TSS, Chl-a, and turbidity in the study area were accurately estimated by the satellite image-based monitoring system (R2 = 0.80, 0.74, and 0.64, respectively). Keyphrases: Environmental Monitoring., image processing, remote sensing, satellite imagery, water pollution, water quality monitoring
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