Articles | Volume 26, issue 1
https://doi.org/10.5194/nhess-26-487-2026
https://doi.org/10.5194/nhess-26-487-2026
Review article
 | 
26 Jan 2026
Review article |  | 26 Jan 2026

Review article: Deep learning for potential landslide identification: data, models, applications, challenges, and opportunities

Pan Jiang, Zhengjing Ma, and Gang Mei

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Short summary
In order to elucidate the potential for integrating deep learning with potential landslide identification, this paper focuses on four key dimensions: (1) Summarising data sources for potential landslide identification. (2) Compare the roles of commonly used deep learning models. (3) Analyse the practical applications of deep learning in early landslide detection. (4) Investigate key challenges and propose future priorities for potential landslide identification.
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