Work

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

Year: 2025

Type: article

Abstract: Organic pollution poses a significant threat to water security, making the monitoring of organic pollutants in water environments essential for the protection of water resources. Remote sensing technology, with its wide coverage, continuous monitoring capability, and cost-efficiency, overcomes the limitations of traditional methods, which are often time-consuming, labor-intensive, and spatially restricted. As a result, it has become an effective tool for monitoring organic pollution in water environments. In this study, we propose a physically constrained remote sensing algorithm for the quantitative estimation of organic pollution in inland waters based on radiative transfer theory. The algorithm was applied to the Feilaixia Basin using Sentinel-2 data. Accuracy assessment results demonstrate good performance in the quantitative assessment of organic pollution, with a coefficient of determination (R2) of 0.79, a mean absolute percentage error (MAPE) of 13.03%, and a root mean square error (RMSE) of 0.39 mg/L. Additionally, a seasonal variation map of organic pollutant concentrations in the Feilaixia Basin was generated, providing valuable scientific support for regional water quality monitoring and management.

Source: Sensors

DOI: 10.3390/s25092737

Authors: Jiayi Li, Ruru Deng, Yu Guo, Cong Lei, Zhenqun Hua, Junying Yang

Institutions: Sun Yat-sen University, Key Laboratory of Guangdong Province, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai)

Language: English

Topic: Water Quality Monitoring and Analysis

Subfield: Waste Management and Disposal

Field: Environmental Science

Domain: Physical Sciences

SDG: Clean water and sanitation

Open Access status: gold

Estimated APC paid: $3,137