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To address the management challenges of geographic information data of the Yangtze River channel, such as multi-source heterogeneity and significant dynamic evolution characteristics, this study developed an intelligent analysis framework integrating spatio-temporal databases and deep learning. By designing a multimodal data fusion mechanism and a lightweight LSTM-Transformer hybrid model, core functions such as dynamic prediction of waterway terrain and intelligent identification of navigational obstacles have been realized, providing technical support for the intelligent governance of the Yangtze Golden Waterway.

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Research on the Management and Application of Geographic Information Data of the Yangtze River Channel Based on Deep Learning Technology

  • 会议论文

  • 发表日期：

    2026年

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  • Zining Li,
  • Jinxiang Xiang,
  • Baorui Zhang,
  • Sihang Liu,
  • Ping Zhang

摘要

To address the management challenges of geographic information data of the Yangtze River channel, such as multi-source heterogeneity and significant dynamic evolution characteristics, this study developed an intelligent analysis framework integrating spatio-temporal databases and deep learning. By designing a multimodal data fusion mechanism and a lightweight LSTM-Transformer hybrid model, core functions such as dynamic prediction of waterway terrain and intelligent identification of navigational obstacles have been realized, providing technical support for the intelligent governance of the Yangtze Golden Waterway.