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GF-1 Wide-Field Multispectral Multi-temporal Water Body Extraction Dataset

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科学数据银行2025-06-30 更新2026-04-23 收录
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The data used in this study (Figure 1) were obtained from the Wide-Field Multispectral Camera (WFV) of the China High-Resolution Earth Observation System's "Gaofen-1" (GF-1) satellite, with a spatial resolution of 16 meters. The spectral range covers 450–890 nm, including four bands: blue (0.45–0.52 μm), green (0.52–0.59 μm), red (0.63–0.69 μm), and near-infrared (0.77–0.89 μm). The satellite has a revisit cycle of approximately four days, enabling efficient acquisition of large-scale surface data, making it suitable for monitoring water bodies, land use, and environmental changes. The dataset covers three typical lake regions—Poyang Lake, Yangcheng Lake, and Nam Co—with each image having a pixel size of 256×256 and containing four bands. Additionally, it includes a single-band water body annotation image of the same size, featuring the following characteristics:(1) Multi-Temporal CharacteristicsThe dataset comprehensively covers the spring, summer, autumn, and winter remote sensing images of Poyang Lake and Nam Co, which exhibit high dynamic variability, as well as Yangcheng Lake, which shows relatively low variability. Using time-series images with a 16-meter spatial resolution, Figure 2 illustrates the intra-annual dynamic changes in the proportion of water body samples in the dataset. In 2022, Poyang Lake experienced a severe drought, with most areas showing moderate to severe drought conditions from August onward. Nam Co, primarily influenced by plateau climate conditions, entered a distinct ice period in winter, with large areas of the lake covered by snow and ice, leading to a significant decline in the proportion of water body samples. As temperatures rose in spring, the lake gradually thawed, resulting in dynamic changes in water boundaries. In contrast, Yangcheng Lake maintained a stable water coverage throughout the year. The multi-temporal nature of this dataset provides diverse scenarios for model training, including floodplain water bodies during flood seasons, transitional zones during intermediate periods, main river channels during dry seasons, and plateau lakes during ice periods.(2) Heterogeneity in Water Body MorphologyThis study selected three typical lakes to construct a comparative observation system: Poyang Lake, the largest freshwater lake in China, exhibits significant changes in water boundaries due to the backwater effect of the Yangtze River, featuring complex texture characteristics of natural wetlands. Nam Co, located on the Tibetan Plateau, represents a typical plateau lake dominated by natural temperature variations, with notable seasonal snow and ice coverage. Yangcheng Lake, situated in the urban agglomeration of the Yangtze River Delta, is regulated by sluices and interspersed with aquaculture ponds, presenting a fragmented pattern under artificial intervention. The combination of these three lakes ensures a sufficient sample size for large-scale dynamic water bodies while encompassing challenges such as water-ice morphological changes in high-altitude regions and the identification of dense, small water bodies.(3) Fine-Grained AnnotationThis study employed automated annotation and manual visual interpretation, combined with rigorous accuracy verification, to achieve high-precision annotation results. Given the dense distribution of small water bodies and the complexity of water types in Yangcheng Lake, the annotation results for this region were refined by distinguishing between three types of water bodies: lakes, rivers, and ponds. The differentiation between lakes and ponds was primarily based on statistical features such as shape area and width-to-length ratio after segmentation, supplemented by manual visual confirmation. For the Nam Co region, considering its extensive snow and ice coverage in winter, annotations were applied to snow and ice areas, further enriching the water body annotation information provided by the dataset.
提供机构:
ji lu yan; Aerospace Information Research Institute; University of Hong Kong
创建时间:
2025-03-18
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