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Winter Water Quality Modeling in Xiong’an New Area Supported by Hyperspectral Observation
Xiong’an New Area is defined as the future city of China, and the regulation of water resources is an important part of the scientific development of the city. Baiyang Lake, the main supplying water for the city, is selected as the study area, and the water quality extraction of four typical river s...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10144822/ https://www.ncbi.nlm.nih.gov/pubmed/37112430 http://dx.doi.org/10.3390/s23084089 |
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author | Yang, Yuechao Zhang, Donghui Li, Xusheng Wang, Daming Yang, Chunhua Wang, Jianhua |
author_facet | Yang, Yuechao Zhang, Donghui Li, Xusheng Wang, Daming Yang, Chunhua Wang, Jianhua |
author_sort | Yang, Yuechao |
collection | PubMed |
description | Xiong’an New Area is defined as the future city of China, and the regulation of water resources is an important part of the scientific development of the city. Baiyang Lake, the main supplying water for the city, is selected as the study area, and the water quality extraction of four typical river sections is taken as the research objective. The GaiaSky-mini2-VN hyperspectral imaging system was executed on the UAV to obtain the river hyperspectral data for four winter periods. Synchronously, water samples of COD, PI, AN, TP, and TN were collected on the ground, and the in situ data under the same coordinate were obtained. A total of 2 algorithms of band difference and band ratio are established, and the relatively optimal model is obtained based on 18 spectral transformations. The conclusion of the strength of water quality parameters’ content along the four regions is obtained. This study revealed four types of river self-purification, namely, uniform type, enhanced type, jitter type, and weakened type, which provided the scientific basis for water source traceability evaluation, water pollution source area analysis, and water environment comprehensive treatment. |
format | Online Article Text |
id | pubmed-10144822 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-101448222023-04-29 Winter Water Quality Modeling in Xiong’an New Area Supported by Hyperspectral Observation Yang, Yuechao Zhang, Donghui Li, Xusheng Wang, Daming Yang, Chunhua Wang, Jianhua Sensors (Basel) Article Xiong’an New Area is defined as the future city of China, and the regulation of water resources is an important part of the scientific development of the city. Baiyang Lake, the main supplying water for the city, is selected as the study area, and the water quality extraction of four typical river sections is taken as the research objective. The GaiaSky-mini2-VN hyperspectral imaging system was executed on the UAV to obtain the river hyperspectral data for four winter periods. Synchronously, water samples of COD, PI, AN, TP, and TN were collected on the ground, and the in situ data under the same coordinate were obtained. A total of 2 algorithms of band difference and band ratio are established, and the relatively optimal model is obtained based on 18 spectral transformations. The conclusion of the strength of water quality parameters’ content along the four regions is obtained. This study revealed four types of river self-purification, namely, uniform type, enhanced type, jitter type, and weakened type, which provided the scientific basis for water source traceability evaluation, water pollution source area analysis, and water environment comprehensive treatment. MDPI 2023-04-18 /pmc/articles/PMC10144822/ /pubmed/37112430 http://dx.doi.org/10.3390/s23084089 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Yang, Yuechao Zhang, Donghui Li, Xusheng Wang, Daming Yang, Chunhua Wang, Jianhua Winter Water Quality Modeling in Xiong’an New Area Supported by Hyperspectral Observation |
title | Winter Water Quality Modeling in Xiong’an New Area Supported by Hyperspectral Observation |
title_full | Winter Water Quality Modeling in Xiong’an New Area Supported by Hyperspectral Observation |
title_fullStr | Winter Water Quality Modeling in Xiong’an New Area Supported by Hyperspectral Observation |
title_full_unstemmed | Winter Water Quality Modeling in Xiong’an New Area Supported by Hyperspectral Observation |
title_short | Winter Water Quality Modeling in Xiong’an New Area Supported by Hyperspectral Observation |
title_sort | winter water quality modeling in xiong’an new area supported by hyperspectral observation |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10144822/ https://www.ncbi.nlm.nih.gov/pubmed/37112430 http://dx.doi.org/10.3390/s23084089 |
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