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Influences of environmental factors on the dissipation of green tides in the Yellow Sea, China.
Yang, Dian; Yuen, Ka-Veng; Gu, Xingfa; Sun, Chan; Gao, Liang.
Afiliación
  • Yang D; State Key Laboratory of Internet of Things for Smart City and Department of Civil and Environmental Engineering, University of Macau, Macao; Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China; University of Chinese Academy of Sciences, Beijing 100094, China;
  • Yuen KV; State Key Laboratory of Internet of Things for Smart City and Department of Civil and Environmental Engineering, University of Macau, Macao. Electronic address: kvyuen@um.edu.mo.
  • Gu X; Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China; University of Chinese Academy of Sciences, Beijing 100094, China; School of Remote Sensing and Information Engineering, North China Institute of Aerospace Engineering, Langfang 065000, China. Electronic add
  • Sun C; National Satellite Meteorological Center, China Meteorological Administration, Beijing 100081, China.
  • Gao L; State Key Laboratory of Internet of Things for Smart City and Department of Civil and Environmental Engineering, University of Macau, Macao. Electronic address: gaoliang@um.edu.mo.
Mar Pollut Bull ; 189: 114737, 2023 Apr.
Article en En | MEDLINE | ID: mdl-36863273
Green tides attack the Yellow Sea every year since 2007 and have caused substantial financial loss. Based on Haiyang-1C/Coastal zone imager (HY-1C/CZI) and Terra/MODIS satellite images, the temporal and spatial distribution of green tides floating in the Yellow Sea during 2019 was extracted. The relationships between the growth rate of the green tides and the environmental factors including sea surface temperature (SST), photosynthetically active radiation (PAR), sea surface salinity (SSS), nitrate and phosphate during the green tides' dissipation phase has been detected. Based on the maximum likelihood estimation, a regression model that includes SST, PAR and phosphate was recommended to predict the growth rate of the green tides in the dissipation phase (R2 = 0.63), and this model was also examined using Bayesian information criterion and Akaike information criterion. When the average SST in the study area was above 23.6 °C, the coverage of green tides began to decrease with the increase in temperature under the influence of PAR. The growth rate of the green tides was related to SST (R = -0.38), PAR (R = -0.67) and phosphate (R = 0.40) in the dissipation phase. Compared with HY-1C/CZI, the green tide area extracted using Terra/MODIS tended to be underestimated when the green tide patches were smaller than 11.2 km2. Otherwise, the lower spatial resolution of MODIS resulted in larger mixed pixels of water and algae, which would overestimate the total area of the green tides.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Ulva Tipo de estudio: Prognostic_studies País/Región como asunto: Asia Idioma: En Revista: Mar Pollut Bull Año: 2023 Tipo del documento: Article Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Ulva Tipo de estudio: Prognostic_studies País/Región como asunto: Asia Idioma: En Revista: Mar Pollut Bull Año: 2023 Tipo del documento: Article Pais de publicación: Reino Unido