TY  - Data
T1  - Annual Surface Water Distribution Dataset of the Songliao  Basin, 1984-2023
A1  - xiahaoming
DO  - 10.12072/ncdc.csd.db6687.2024
PY  - 2024
DA  - 2024-12-19
PB  - National Cryosphere Desert Data Center
AB  - Fine mapping of surface water plays an important role in water resource management, ecological environment protection, and flood prevention and control. However, the Songliao River Basin still lacks high-precision, long-term surface water distribution datasets. To fill this gap, this article constructs a surface water extraction algorithm suitable for the Songliao River Basin based on multi-source satellite remote sensing data (Landsat 5/7/8/9) and the Google Earth Engine (GEE) platform, generating an annual surface water distribution dataset from 1984 to 2023. This dataset includes annual water body frequency data (WBF) and water body classification data (SWC), covering seasonal water bodies, permanent water bodies, and maximum water body distribution. Through precision evaluation, the overall accuracy of the water extraction method reached 98%, with a Kappa coefficient of 0.95. In order to verify the reliability of the data, a comparative analysis was conducted between the SWC data and the Global Water Classification History (GWS) dataset. The results showed that the classification accuracy of the SWC dataset in the Songliao Basin was better than that of the GWS dataset in multiple regions. The high-precision water body dataset provided in this study will provide important support for water resource monitoring and management in the Songliao River Basin, and will also lay a solid data foundation for scientific research in related fields
DB  - NCDC
UR  - http://www.ncdc.ac.cn/portal/metadata/361a036a-299e-4c06-a025-376101d9ee8c
ER  -