Daily-scale dataset of highly dynamic water of Poyang Lake

Poyang Lake experiences cyclical height changes annually, serving as a prime focus for highly dynamic water resource research. However, its complex environment and cloudy climate make timely and accurate mapping of water resources difficult, as well as more accurate ecological and water resource studies. We introduced the Tanh activation function and constructed a new optical water index, the Combined Water Index (CWI), to improve the accuracy and automation level of water identification. Meanwhile, in view of the cloudy weather conditions in Poyang Lake, we integrated the microwave images and proposed the New SAR Water Index (NSWI), which effectively supplemented the observation data. We established a 37-year-long observation experience of the water of Poyang Lake from 1986 to 2023. Third, we introduced water level, cumulative outflow from the Three Gorges Dam, and precipitation data to build a predictive model for random forests with reliable accuracy. Finally, we realized the spatial inversion of the predicted area and constructed a daily-scale water dataset of Poyang Lake (2016–2021). This study offers critical data support for advancing Poyang Lake ecological research and water resource management.

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Publication Details

Journal
Big Earth Data
Published
2025-05-25
DOI
https://doi.org/10.1080/20964471.2025.2506289
Citations
1
Primary Topic
Flood Risk Assessment and Management
Type
article
Field-Weighted Citation Impact
1.11

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article

Daily-scale dataset of highly dynamic water of Poyang Lake

Haifeng Tian, Yaochen Qin, Jie Pei, Xiaoying Liang et al.
1 citations
Big Earth Data
Flood Risk Assessment and Management
1.11
article

Daily-scale dataset of highly dynamic water of Poyang Lake

Haifeng Tian, Yaochen Qin, Jie Pei, Xiaoying Liang, Shuai Wang, Yijie Ma, Teng Gong, Li Wang, Yuqing Wang
article en
1 citations

Abstract

Poyang Lake experiences cyclical height changes annually, serving as a prime focus for highly dynamic water resource research. However, its complex environment and cloudy climate make timely and accurate mapping of water resources difficult, as well as more accurate ecological and water resource studies. We introduced the Tanh activation function and constructed a new optical water index, the Combined Water Index (CWI), to improve the accuracy and automation level of water identification. Meanwhile, in view of the cloudy weather conditions in Poyang Lake, we integrated the microwave images and proposed the New SAR Water Index (NSWI), which effectively supplemented the observation data. We established a 37-year-long observation experience of the water of Poyang Lake from 1986 to 2023. Third, we introduced water level, cumulative outflow from the Three Gorges Dam, and precipitation data to build a predictive model for random forests with reliable accuracy. Finally, we realized the spatial inversion of the predicted area and constructed a daily-scale water dataset of Poyang Lake (2016–2021). This study offers critical data support for advancing Poyang Lake ecological research and water resource management.

Big Earth DataVol. 9(4)
Sun Yat-sen University (CN), Henan University (CN), Chinese Academy of Sciences (CN), Geospatial Research (United Kingdom) (GB), Forest Research (GB), Aerospace Information Research Institute (CN), Henan Province Water Conservancy Survey and Design Research (CN), State Key Laboratory of Remote Sensing Science (CN)
National Natural Science Foundation of China, Henan University
Clean water and sanitation
Openalex Percentile: Top 24%
Flood Risk Assessment and Management
1.11
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