Paper
30 August 2023 Inversion and evaluation of water quality parameters of Yuehai Lake in Yinchuan based on satellite remote sensing
Yan Xiang, Guo Zhonghua, Wang Ying, Shi Tiantian, Li Qiang
Author Affiliations +
Proceedings Volume 12797, Second International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023); 127972M (2023) https://doi.org/10.1117/12.3007471
Event: 2nd International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023), 2023, Qingdao, China
Abstract
Taking Yuehai Lake Wetland in Yinchuan City, Ningxia as the research object, based on Landsat-8 image data, combined with the detection values of water quality parameters taken in the field, a remote sensing water quality parameter inversion model was established, and the concentrations of four water quality parameters of chemical oxygen demand, ammonia nitrogen, total phosphorus and total nitrogen were inverted, and the concentration of water quality parameters was comprehensively analyzed and evaluated by entropy weight fuzzy method. The results show that the established inversion model can reflect the parameter concentration distribution of Yuehai Lake water quality in different areas. The fitting degree R2 of the four water quality index inversion models of chemical oxygen demand, ammonia nitrogen, total phosphorus and total nitrogen were 0.88, 0.89, 0.87 and 0.9, respectively; spatially, the pollution of the parameters in the north of Yuehai Lake is more serious than that in the south. The comprehensive evaluation results of water quality showed that the water quality of Yuehai Lake was mainly Class II and Class III water quality.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Yan Xiang, Guo Zhonghua, Wang Ying, Shi Tiantian, and Li Qiang "Inversion and evaluation of water quality parameters of Yuehai Lake in Yinchuan based on satellite remote sensing", Proc. SPIE 12797, Second International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023), 127972M (30 August 2023); https://doi.org/10.1117/12.3007471
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Water quality

Remote sensing

Nitrogen

Earth observing sensors

Image quality

Satellites

Landsat

Back to Top