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<p>The cryosphere is a vital and rapidly changing component of the Earth’s climate system, marked by its extensive snow and ice-covered regions. This survey offers an in-depth overview of recent advancements in cryospheric research, with a particular focus on the impact of cutting-edge remote sensing technologies and artificial intelligence (AI) approaches. It highlights a range of state-of-the-art techniques used for processing, modeling, and interpreting radar echograms, offering valuable insights into subsurface ice properties. Key remote sensing missions, including ICESat, ICESat-2, Operation IceBridge, and various airborne and ground-based radar systems, are critically examined for their contributions to the study of ice sheets, glaciers, and sea ice. Recent progress in AI, such as transformer-based computer vision models and hybrid physics-informed machine learning frameworks, has greatly enhanced the ability to process complex datasets, leading to more accurate monitoring of cryospheric changes. This review emphasizes the significance of these technological innovations in measuring essential variables like ice sheet mass balance, surface dynamics, and internal ice structures in polar regions. By integrating findings from diverse remote sensing efforts and AI-driven methodologies, the survey presents a comprehensive view of current practices in cryospheric science, highlighting their essential role in understanding climate change and informing predictive environmental modeling.</p>

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Advancing cryospheric studies: a historical perspective on radio-echo soundgram analysis techniques

  • 期刊论文

  • 发表日期：

    2025年8月16日

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  • Adithya Awati,
  • Ankush Sirvi,
  • Charan Gowda BM,
  • Meshank Bansal,
  • Vindhya P Malagi,
  • Deepshree Buchade

摘要

The cryosphere is a vital and rapidly changing component of the Earth’s climate system, marked by its extensive snow and ice-covered regions. This survey offers an in-depth overview of recent advancements in cryospheric research, with a particular focus on the impact of cutting-edge remote sensing technologies and artificial intelligence (AI) approaches. It highlights a range of state-of-the-art techniques used for processing, modeling, and interpreting radar echograms, offering valuable insights into subsurface ice properties. Key remote sensing missions, including ICESat, ICESat-2, Operation IceBridge, and various airborne and ground-based radar systems, are critically examined for their contributions to the study of ice sheets, glaciers, and sea ice. Recent progress in AI, such as transformer-based computer vision models and hybrid physics-informed machine learning frameworks, has greatly enhanced the ability to process complex datasets, leading to more accurate monitoring of cryospheric changes. This review emphasizes the significance of these technological innovations in measuring essential variables like ice sheet mass balance, surface dynamics, and internal ice structures in polar regions. By integrating findings from diverse remote sensing efforts and AI-driven methodologies, the survey presents a comprehensive view of current practices in cryospheric science, highlighting their essential role in understanding climate change and informing predictive environmental modeling.