In recent years, people around the world are living in better and better conditions, and people are demanding more and more from their environment, and pollution of the water environment has become the most serious environmental hazard. In many areas, due to the strong development of agriculture and industry, their pollutants are discharged directly into nearby river basins, leading to eutrophication of water bodies. Failure to carry out river water pollution (WP) prevention and control not only poses a major threat to the health of the people in society, but also has a serious impact on the harmonious and stable development of society. Therefore, this paper uses 3D remote sensing technology (RST) to collect images of river basins, generate remote sensing maps of river basins, extract features of remote sensing images using spectrum classification, and establish river water quality monitoring stations to obtain water quality data of each basin section. The application of spectrum classification and 3D RST provides technical support for the construction of river WP prevention and early warning system (EWS), helps to monitor the water quality in river basins and early warning WP accidents, is conducive to promoting the development of WP prevention, and improves the current crisis of river WP prevention in China.

Baiming Liu. Optimization Method of River Water Pollution Prevention and Early Warning System Supporting Spectrum Classification and 3D Remote Sensing Technology. Water Pollution Prevention and Control Project (2023), Vol. 4, Issue 1: 10-18. https://doi.org/10.38007/WPPCP.2023.040102.

[1] Alfred Homere Ngandam Mfondoum, Sofia Hakdaoui, Roseline Batcha. Landsat 8Bands' 1 to 7 spectral vectors plus machine learning to improve land use/cover classification using Google Earth Engine. Ann. GIS. (2022) 28(3): 401-424. https://doi.org/10.1080/19475683.2022.2026475

[2] Anil B. Gavade, Vijay S. Rajpurohit. Sparse-FCM and deep learning for effective classification of land area in multi-spectral satellite images. Evol. Intell. (2022) 15(2): 1185-1201. https://doi.org/10.1007/s12065-020-00362-3

[3] Diganta Kumar Pathak, Sanjib Kumar Kalita, Dhruba Kumar Bhattacharya. Hyperspectral image classification using support vector machine: a spectral spatial feature based approach. Evol. Intell. (2022) 15(3): 1809-1823. https://doi.org/10.1007/s12065-021-00591-0

[4] Laurent Polidori. Words as tracers in the history of science and technology: the case of photogrammetry and remote sensing. Geo spatial Inf. Sci. (2021) 24(1): 167-177. https://doi.org/10.1080/10095020.2020.1843375

[5] Swati Chopade, Hari Prabhat Gupta, Rahul Mishra, Preti Kumari, Tanima Dutta. An Energy-Efficient River WP Monitoring System in Internet of Things. IEEE Trans. Green Commun. Netw. (2021) 5(2): 693-702. https://doi.org/10.1109/TGCN.2021.3062470

[6] Amal Agarwal, Lingzhou Xue. Model-Based Clustering of Nonparametric Weighted Networks With Application to Water Pollution Analysis. Technometrics. (2020) 62(2): 161-172. https://doi.org/10.1080/00401706.2019.1623076

[7] Artem A. Sedakov, Han Qiao, Shouyang Wang. A model of river pollution as a dynamic game with network externalities. Eur. J. Oper. Res. (2021) 290(3): 1136-1153. https://doi.org/10.1016/j.ejor.2020.08.053

[8] Swati Chopade, Hari Prabhat Gupta, Rahul Mishra, Preti Kumari, Tanima Dutta. An Energy-Efficient River Water Pollution Monitoring System in Internet of Things. IEEE Trans. Green Commun. Netw. (2021) 5(2): 693- 702. https://doi.org/10.1109/TGCN.2021.3062470

[9] Priyanka, N. Sravya, Shyam Lal , J. Nalini, Chintala Sudhakar Reddy, Fabio DellAcqua: DIResUNet. Architecture for multiclass semantic segmentation of high resolution RSIry data. Appl. Intell. (2022) 52(13): 15462-1 5482. https://doi.org/10.1007/s10489-022-03310-z

[10] Sawas D. Apostolidis, Pavlos Ch. Kapoutsis, Athanasios Ch. Kapoutsis, Elias B. Kosmatopoulos. Cooperative multi-UAV coverage mission planning platform for remote sensing applications. Auton. Robots. (2022) 46(2): 373-400. https://doi.org/10.1007/s10514-021-10028-3

[11] Mustafizur Rahaman, Md. Monsur Hillas, Jannatul Tuba, Jannatul Ferdous Ruma, Nahian Ahmed, Rashedur M. Rahman. Effects of Label Noise on Performance of Remote Sensing and Deep Learning-Based Water Body Segmentation Models. Cybern. Syst. (2022) 53(6): 581-606. https://doi.org/10.1080/01969722.2021.1989171

[12] Fowzia Akhter, Hasin R. Siddiquei, Md Eshrat E. Alahi, Krishanthi P. Jayasundera, Subhas Chandra Mukhopadhyay. An IoT-Enabled Portable Water Quality Monitoring System With MWCNT/PDMS Multifunctional Sensor for Agricultural Applications. IEEE Internet Things J. (2022) 9(16):14307-14316. https://doi.org/10.1109/JIOT.2021.3069894

[13] Haider A. H. Alobaidy, Rosdiadee Nordin, Mandeep Jit Singh, Nor Fadzilah Abdullah, Azril Haniz, Kentaro Ishizu, Takeshi Matsumura, Fumihide Kojima, Nordin Bin Ramli. Low-Altitude-Platform-Based Airborne IoT Network (LAP-AIN) for Water Quality Monitoring in Harsh Tropical Environment. IEEE Internet Things J. (2022) 9(20): 20034-20054. https://doi.org/10.1109/JIOT.2022.3171294

[14] Harish H. Kenchannavar, Prasad M. Pujar, Raviraj M. Kukarni, Umakant P. Kulkarni. Evaluation and Analysis of Goodness of Fit for Water Quality Parameters Using Linear Regression through the Internet-of-Things-Based Water Quality Monitoring System. IEEE Internet Things J. (2022) 9(16): 14400-14407. https://doi.org/10.1109/JIOT.2021.3094724

[15] R. Vijay Anandh, S. Rukmani Devi. Visual Enhancement of Underwater Images Using Transmission Estimation and Multi-Scale Fusion. Comput. Syst. Sci. Eng. (2023) 44(3): 1897-1910. https://doi.org/10.32604/csse.2023.027187

[16] Yujae Song o, Huicheol Shin, Sungmin Koo, Seungjae Baek, Jungmin Seo, Hyoun Kang, Yongjae Kim. Internet of Maritime Things Platform for Remote Marine Water Quality Monitoring. IEEE Internet Things J. (2022) 9(16): 14355-14365. https://doi.org/10.1109/JIOT.2021.3079931

[17] Kasyap Suresh, Varun Jeoti, Micheal Drieberg, Socheatra Soeung, Asif Iqbal, Goran M. Stojanovic, Sohail Sarang. Simultaneous Detection of Multiple Surface Acoustic Wave Sensor Tags for Water Quality Monitoring Utilizing Cellular Code-Reuse Approach. IEEE Internet Things. (2022) 9(16): 14385-14399. https://doi.org/10.1109/JIOT.2021.3082141

[18] Fouzi Lezzar, Djamel Benmerzoug, Iham Kitouni. IoT for Monitoring and Control of Water Quality Parameters. Int. J. Interact. Mob. Technol. (2020) 14(16): 4-19. https://doi.org/10.3991/ijim.v14i16.15783