Recent Phenomenal and Investigational Subsurface Landslide Monitoring Techniques: A Mixed Review

Author:

Ebrahim Kyrillos M. P.12ORCID,Gomaa Sherif M. M. H.12ORCID,Zayed Tarek1ORCID,Alfalah Ghasan3ORCID

Affiliation:

1. Department of Building and Real Estate, Faculty of Construction and Environment, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong SAR 999077, China

2. Structural Engineering Department, Faculty of Engineering, Mansoura University, Mansoura 35516, Egypt

3. Department of Architecture and Building Sciences, King Saud University, Riyadh 145111, Saudi Arabia

Abstract

Landslides are a common and challenging geohazard that may be caused by earthquakes, rainfall, or manmade activity. Various monitoring strategies are used in order to safeguard populations at risk from landslides. This task frequently depends on the utilization of remote sensing methods, which include the observation of Earth from space, laser scanning, and ground-based interferometry. In recent years, there have been notable advancements in technologies utilized for monitoring landslides. The literature lacks a comprehensive study of subsurface monitoring systems using a mixed review approach that combines systematic and scientometric methods. In this study, scientometric and systematic analysis was used to perform a mixed review. An in-depth analysis of existing research on landslide-monitoring techniques was conducted. Surface-monitoring methods for large-scale landslides are given first. Next, local-scale landslide subsurface monitoring methods (movement, forces and stresses, water, temperature, and warning signs) were examined. Next, data-gathering techniques are shown. Finally, the physical modeling and prototype field systems are highlighted. Consequently, key findings about landslide monitoring are reviewed. While the monitoring technique selection is mainly controlled by the initial conditions of the case study, the superior monitoring technique is determined by the measurement accuracy, spatiotemporal resolution, measuring range, cost, durability, and applicability for field deployment. Finally, research suggestions are proposed, where developing a superior distributed subsurface monitoring system for wide-area monitoring is still challenging. Interpolating the complex nonlinear relationship between subsurface monitoring readings is a clear gap to overcome. Warning sign systems are still under development.

Funder

Hong Kong Polytechnic University

Innovation and Technology Support Programme (ITSP) of the Hong Kong SAR

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences

Reference153 articles.

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4. Ebrahim, K.M.P., Gomaa, S.M.M.H., Zayed, T., and Alfalah, G. (2024). Landslide Prediction Models, Part I: Empirical-Statistical and Physically Based Causative Thresholds, Department of Building and Real Estate, Faculty of Construction and Environment, The Hong Kong Polytechnic University.

5. Ebrahim, K.M.P., Gomaa, S.M.M.H., Zayed, T., and Alfalah, G. (2024). Landslide Prediction Models, Part II: Deterministic Physical and Phenomenologically Models, Department of Building and Real Estate, Faculty of Construction and Environment, The Hong Kong Polytechnic University.

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