Advanced deep learning techniques for automated extraction of non-debris-covered areas of glaciers in High-Mountain Asia using time-series remote sensing data
【作者】Gexia Qin，Ninglian Wang，Bo Jiang，Yuwei Wu，Yanchao Yin，Zhijie Li
【刊名】International Journal of Applied Earth Observation and Geoinformation
【作者单位】1Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, College of Urban and Environmental Science, Northwest University, Xi’ an 710127, China;2Institute of Earth Surface System and Hazards, College of Urban and Environmental Sciences, Northwest University, Xi’ an 710127, China;3School of Information Science and Technology, Northwest University, Xi’an 710027, China;4Shaanxi Key Laboratory of Higher Education Institution of Generative Artificial Intelligence and Mixed Reality, Xi’an 710127, China;5School of Geographic Sciences, Taiyuan Normal University, Taiyuan 030619, China
【年份】2025
【卷号】Vol.142
【页码】104680
【ISSN】1569-8432
【关键词】Glacier boundary Swin transform Deep learning Remote sensing image High-Mountain Asia
【摘要】 Deep learning approaches have gained prominence for automatic glacier boundary extraction due to their localized nature of convolutional operations, potentially leading to incomplete or fragmented glacier pixel representations. Moreover, the accuracy...
