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September 10, 2025Engineering Technology & Applied Science ResearchOpen Access

High-Precision Landslide Susceptibility Mapping Using CNN-LSTM-Attention Models

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Authors

DAD AnilSMS H Manjula

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Overview

This research demonstrates advanced susceptibility mapping using CNN, LSTM, and Attention models, enhancing risk assessment.

Key Points

  • The LSTM model achieved a high accuracy of 98.80% and an AUC of 0.988 in landslide prediction.
  • CNN, LSTM, and Attention U-Net models were combined to enhance the accuracy of landslide susceptibility mapping.
  • The study analyzed 1,580 landslide occurrence data points and 17 geospatial conditioning factors.
  • The susceptibility map aids in proactive hazard mitigation planning for urban planners and disaster response teams.

Cite This Study

Anil et al. (2025) studied this question.

synapsesocial.com/papers/68c1ac0954b1d3bfb60e4ad6https://doi.org/10.48084/etasr.11505
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