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Article

4 Citations

2,279 Views

18 Pages

Identification and Analysis of the Geohazards Located in an Alpine Valley Based on Multi-Source Remote Sensing Data

Yonglin Yang,
Zhifang Zhao,
Dingyi Zhou,
Zhibin Lai,
Kangtai Chang,
Tao Fu and
Lei Niu

Sensors2024, 24(13), 4057;https://doi.org/10.3390/s24134057

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21 June 2024

Geohazards that have developed in densely vegetated alpine gorges exhibit characteristics such as remote occurrence, high concealment, and cascading effects. Utilizing a single remote sensing datum for their identification has limitations, while util...

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Article

35 Citations

4,580 Views

27 Pages

Integrating Machine Learning Ensembles for Landslide Susceptibility Mapping in Northern Pakistan

Nafees Ali,
Jian Chen,
Xiaodong Fu,
Rashid Ali,
Muhammad Afaq Hussain,
Hamza Daud,
Javid Hussain and
Ali Altalbe

Remote Sens.2024, 16(6), 988;https://doi.org/10.3390/rs16060988

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12 March 2024

Natural disasters, notably landslides, pose significant threats to communities and infrastructure. Landslide susceptibility mapping (LSM) has been globally deemed as an effective tool to mitigate such threats. In this regard, this study considers the...

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Article

528 Views

28 Pages

PS-InSAR Monitoring Integrated with a Bayesian-Optimized CNN–LSTM for Predicting Surface Subsidence in Complex Mining Goafs Under a Symmetry Perspective

Tianlong Su,
Linxin Zhang,
Xuzhao Yuan,
Xiaoquan Li,
Xuefeng Li,
Xuxing Huang,
Zheng Huang and
Danhua Zhu

Symmetry2025, 17(12), 2152;https://doi.org/10.3390/sym17122152

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14 December 2025

Mine-induced surface subsidence threatens infrastructure and can trigger cascading geohazards, so accurate and computationally efficient monitoring and forecasting are essential for early warning. We integrate Persistent Scatterer InSAR (PS-InSAR) ti...

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