Quantitative of surface water pollution in Hoi An city using remote sensing data and machine learning model
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Keywords

Ô nhiễm nước mặt
Viễn thám
Chất lượng nước
Mô hình ANFIS
Thành phố Hội An Surface water pollution
Remote sensing
Water quality
ANFIS model
Hoi An city

Working Languages

How to Cite

Do, T. N., Nguyen, T. D. M., Tran, Q. T., Nghiem, V. T., & Pham, V. M. (2022). Quantitative of surface water pollution in Hoi An city using remote sensing data and machine learning model. Journal of Geodesy and Cartography, (52), 54–64. https://doi.org/10.54491/jgac.2022.52.598

Abstract

The situation of surface water in Hoi An city has been facing challenges in terms of pollution levels for more than a decade. In order to estimate three water quality parameters, such as TSS, COD, and BOD, this study introduces the integration of a machine learning model with an adaptive network-based fuzzy inference system (ANFIS), paired with optical and radar remote sensing data. The RMSE, R2, and MAE parameters were used to assess the model's performance. With RMSE ranging from 3.52 mg/l to 4.59 mg/l, R2 ranging from 0.69-0.82, and MAE ranging from 2.39 mg/l to 3.16 mg/l, the predictive indices produced significant findings. The results show that the concentrations of three high water quality assessment parameters are distributed in the area of ​​Hoi An Ancient Town, Hoai River. This method can be used to assess surface water quality parameters, to quickly monitor the status of the water environment, to provide a method of monitoring water surface quality, which can be the foundation for providing solutions to protect and use clean water sources in Heritage cities

https://doi.org/10.54491/jgac.2022.52.598
PDF (Tiếng Việt) | Download: 323

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