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Yingxin Shang

Showing results (11-20 of 38) with videos related to

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Environmental Science and Pollution Research International|August 17, 2019
Estimation of K<sub>d</sub>(PAR) in inland waters across China in relation to the light absorption of optically active componentsZhidan Wen, Kaishan Song, Chong Fang, et al.
Water Research|December 17, 2018
Characterization of CDOM in saline and freshwater lakes across China using spectroscopic analysisKaishan Song, Yingxin Shang, Zhidan Wen, et al.
Scientific Reports|January 21, 2025
Spatiotemporal variation in biomass abundance of different algal species in Lake Hulun using machine learning and Sentinel-3 imagesZhaojiang Yan, Chong Fang, Kaishan Song, et al.
Environmental Science and Ecotechnology|December 18, 2023
Re-estimating China's lake CO<sub>2</sub> flux considering spatiotemporal variabilityZhidan Wen, Yingxin Shang, Lili Lyu, et al.
Environmental Science & Technology|February 17, 2021
Climatic versus Anthropogenic Controls of Decadal Trends (1983-2017) in Algal Blooms in Lakes and Reservoirs across ChinaKaishan Song, Chong Fang, Pierre-Andre Jacinthe, et al.
Environmental Research|May 13, 2021
Songhua River basin's improving water quality since 2005 based on Landsat observation of water clarityHui Tao, Kaishan Song, Ge Liu, et al.
Optics Express|April 27, 2022
Estimation of the lake trophic state index (TSI) using hyperspectral remote sensing in Northeast ChinaLili Lyu, Kaishan Song, Zhidan Wen, et al.
Environmental Research|January 6, 2020
Absorption characteristics of CDOM in treated and non-treated urban lakes in Changchun, ChinaLili Lyu, Zhidan Wen, Pierre-Andre Jacinthe, et al.
Water Research|February 1, 2024
Spatial variations of DOM in a diverse range of lakes across various frozen ground zones in China: Insights into molecular compositionZhidan Wen, Jiarui Han, Yingxin Shang, et al.
Environmental Research|October 22, 2023
A novel chlorophyll-a retrieval model based on suspended particulate matter classification and different machine learningChong Fang, Changchun Song, Zhidan Wen, et al.
Pageof 4

Showing results (11-20 of 38) with videos related to

Sort By:
Pageof 4
Environmental Science and Pollution Research International|August 17, 2019
Estimation of K<sub>d</sub>(PAR) in inland waters across China in relation to the light absorption of optically active componentsZhidan Wen, Kaishan Song, Chong Fang, et al.
Water Research|December 17, 2018
Characterization of CDOM in saline and freshwater lakes across China using spectroscopic analysisKaishan Song, Yingxin Shang, Zhidan Wen, et al.
Scientific Reports|January 21, 2025
Spatiotemporal variation in biomass abundance of different algal species in Lake Hulun using machine learning and Sentinel-3 imagesZhaojiang Yan, Chong Fang, Kaishan Song, et al.
Environmental Science and Ecotechnology|December 18, 2023
Re-estimating China's lake CO<sub>2</sub> flux considering spatiotemporal variabilityZhidan Wen, Yingxin Shang, Lili Lyu, et al.
Environmental Science & Technology|February 17, 2021
Climatic versus Anthropogenic Controls of Decadal Trends (1983-2017) in Algal Blooms in Lakes and Reservoirs across ChinaKaishan Song, Chong Fang, Pierre-Andre Jacinthe, et al.
Environmental Research|May 13, 2021
Songhua River basin's improving water quality since 2005 based on Landsat observation of water clarityHui Tao, Kaishan Song, Ge Liu, et al.
Optics Express|April 27, 2022
Estimation of the lake trophic state index (TSI) using hyperspectral remote sensing in Northeast ChinaLili Lyu, Kaishan Song, Zhidan Wen, et al.
Environmental Research|January 6, 2020
Absorption characteristics of CDOM in treated and non-treated urban lakes in Changchun, ChinaLili Lyu, Zhidan Wen, Pierre-Andre Jacinthe, et al.
Water Research|February 1, 2024
Spatial variations of DOM in a diverse range of lakes across various frozen ground zones in China: Insights into molecular compositionZhidan Wen, Jiarui Han, Yingxin Shang, et al.
Environmental Research|October 22, 2023
A novel chlorophyll-a retrieval model based on suspended particulate matter classification and different machine learningChong Fang, Changchun Song, Zhidan Wen, et al.
Pageof 4