Monitoring, Early Warning and Mitigation of Natural and Engineered Slopes – Volume II

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Editorial

21 April 2023

Editorial: Monitoring, early warning and mitigation of natural and engineered slopes—Volume II

Haijun Qiu

,

Wen Nie

and

Afshin Asadi

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1 citations

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Wen Nie

Jiangxi University of Science and Technology

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This Research Topic is Volume II of a series. The previous volume can be found here: Monitoring, Early Warning and Mitigation of Natural and Engineered Slopes

Natural and engineered slopes are widely distributed worldwide, including mountain slopes, highway slopes, mine slopes, reservoir dams, etc. These slopes could become unstable due to natural factors or human activities, causing catastrophic loss of life and infrastructure destruction. Therefore, these slopes require constant monitoring to provide early warning and enable mitigation. Advanced monitoring equipment, information technology, and multidisciplinary interaction theories have created new opportunities and challenges in this discipline.

Recently, advanced monitoring devices, information technologies, and multidisciplinary intersection theories have contributed to the monitoring, early warning and mitigation of natural and engineered slopes. However, effective and efficient monitoring, precise early warning, low-cost and low-time-consuming remediation, and reliable risk assessment remain obstacles. This Research Topic aims to present the most recent innovative advancements and state-of-the-art natural and engineered slope monitoring, early warning, mitigation, and risk assessment.

This Research Topic aims to provide an outlet for peer-reviewed publications that implement modern technologies, data-based approaches, and techniques incorporating multiple disciplines for the monitoring, early warning, and mitigation of natural and engineered slopes. The topics include but are not limited to the following:
• Analysis of internal structural changes and instability mechanisms of slopes
• Analysis and prediction of monitoring data based on machine learning/deep learning/big data information for slope instability and failure
• Multi-source data-based monitoring techniques, intelligent monitoring and early warning models and systems of slope instability
• Susceptibility mapping, risk assessment, and disaster evaluation of slope hazard;
• Innovative mitigation method and materials for slope hazard

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Editors

Wen Nie

Jiangxi University of Science and Technology

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Frontiers in Earth Science

Geohazards and Georisks

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