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Quantitative Estimation of Organic Pollution in Inland Water Using Sentinel-2 Multispectral Imager.

Jiayi Li1,2,3,4, Ruru Deng1,2,3,4, Yu Guo1,2,3,4

  • 1School of Geography and Planning, Sun Yat-sen University, Guangzhou 510006, China.

Sensors (Basel, Switzerland)
|May 14, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a new remote sensing algorithm to monitor organic pollution in inland waters. The method accurately estimates pollutant levels, aiding water resource protection and management.

Keywords:
Feilaixia basinSentinel-2organic pollutionradiative transfer modelwater quality remote sensing

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Area of Science:

  • Environmental Science
  • Remote Sensing
  • Water Quality Monitoring

Background:

  • Organic pollution is a major threat to water security.
  • Traditional monitoring methods are limited in scope and efficiency.
  • Remote sensing offers a cost-effective, large-scale solution for water pollution assessment.

Purpose of the Study:

  • To develop and validate a physically constrained remote sensing algorithm for quantitative estimation of organic pollution in inland waters.
  • To apply the algorithm to the Feilaixia Basin using Sentinel-2 data.
  • To generate seasonal variation maps of organic pollutant concentrations.

Main Methods:

  • Development of a physically constrained remote sensing algorithm based on radiative transfer theory.
  • Application of the algorithm to Sentinel-2 satellite imagery of the Feilaixia Basin.
  • Accuracy assessment using statistical metrics (R², MAPE, RMSE).

Main Results:

  • The algorithm demonstrated good performance in quantitatively assessing organic pollution.
  • High accuracy was achieved with R² = 0.79, MAPE = 13.03%, and RMSE = 0.39 mg/L.
  • Seasonal variation maps of organic pollutant concentrations were successfully generated for the study area.

Conclusions:

  • The proposed remote sensing algorithm is effective for monitoring organic pollution in inland waters.
  • The findings provide valuable scientific support for regional water quality management and protection efforts.
  • Remote sensing technology is a powerful tool for overcoming limitations of traditional water quality monitoring.