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A dataset of remote-sensed Forel-Ule Index for global inland waters during 2000-2018.
Wang, Shenglei; Li, Junsheng; Zhang, Wenzhi; Cao, Chang; Zhang, Fangfang; Shen, Qian; Zhang, Xianfeng; Zhang, Bing.
Afiliación
  • Wang S; School of Earth and Space Sciences, Peking University, Beijing, China.
  • Li J; Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China.
  • Zhang W; Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China.
  • Cao C; University of Chinese Academy of Sciences, Beijing, China.
  • Zhang F; Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China.
  • Shen Q; University of Chinese Academy of Sciences, Beijing, China.
  • Zhang X; School of Earth Sciences and Resources, China University of Geoscience (Beijing), Beijing, China.
  • Zhang B; Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China.
Sci Data ; 8(1): 26, 2021 01 25.
Article en En | MEDLINE | ID: mdl-33495477
Water colour is the result of its constituents and their interactions with solar irradiance; this forms the basis for water quality monitoring using optical remote sensing data. The Forel-Ule Index (FUI) is a useful comprehensive indicator to show the water colour variability and water quality change in both inland waters and oceans. In recent decades, lakes around the world have experienced dramatic changes in water quality under pressure from both climate change and anthropogenic activities. However, acquiring consistent water colour products for global lakes has been a challenge. In this paper we present the first time series FUI dataset for large global lakes from 2000-2018 based on MODIS observations. This dataset provides significant information on spatial and temporal changes of water colour for global large lakes during the past 19 years. It will be valuable to studies in search of the drivers of global and regional lake colour change, and the interaction mechanisms between water colour, hydrological factors, climate change, and anthropogenic activities.

Texto completo: 1 Banco de datos: MEDLINE Idioma: En Revista: Sci Data Año: 2021 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Banco de datos: MEDLINE Idioma: En Revista: Sci Data Año: 2021 Tipo del documento: Article País de afiliación: China