Spatio-temporal Evolution of Total Nitrogen in Xixi River Based on Sentinel-2 Remote Sensing Images
Remote sensing technology holds significant advantages in the analysis of aquatic ecological environments, including rapid processing speed, abundant information, extensive spatial coverage, and high reliability. Total nitrogen, as a key indicator for assessing the eutrophication state of water bodi...
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Published in | Journal of physics. Conference series Vol. 2863; no. 1; pp. 12003 - 12008 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Bristol
IOP Publishing
01.10.2024
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Subjects | |
Online Access | Get full text |
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Summary: | Remote sensing technology holds significant advantages in the analysis of aquatic ecological environments, including rapid processing speed, abundant information, extensive spatial coverage, and high reliability. Total nitrogen, as a key indicator for assessing the eutrophication state of water bodies, has important application value in evaluating aquatic ecological environments and water quality monitoring. By analyzing the spatiotemporal changes in the concentration of total nitrogen, the dynamic changes in water quality can be effectively reflected. This study selected the Xixi River in Tong’an District, Xiamen City, as the research subject, using six Sentinel-2 satellite remote sensing image data from 2018 to 2023 to construct an empirical regression model for remote sensing inversion of the total nitrogen concentration in the study area. The spatiotemporal evolution of the research results was analyzed, to achieve real-time monitoring and assessment of water quality. The study results indicate that from 2018 to 2023, the total nitrogen concentration in the Xixi River showed a cyclical fluctuation pattern of first increasing, then decreasing and increasing again. The concentration reached its lowest in 2021, at 2.415 mg/L, and the research findings can provide important support for the sustainable development of the river. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
ISSN: | 1742-6588 1742-6596 |
DOI: | 10.1088/1742-6596/2863/1/012003 |