What is it about?

Among the natural hazards that affect humans, landslides play a key role in the devastation it creates and the economic loss it produces. Landslides mostly occur in hilly regions with unstable slopes. It is a complex nonlinear natural dynamical system with built-in uncertainty. The Evolution of landslides is influenced by multiple parameters, including tectonic, rainfall, water table fluctuation, soil condition, nature of the slope, vegetation availability, undercutting, and human activities in the region. Slow-moving landslides cause huge damage in terms of economy and ravaging facilities across their travel path, resulting in huge losses to human life. However, the quantification of fatalities caused by landslides is always underestimated and mainly incomplete; thus, the estimation of landslide risk is rather ambitious. Moreover, there is a growing demand for a detailed, and accurate estimation of landslides and their damage. It is also important to provide hazard mapping that shows the real vulnerability in an area, which will facilitate planners to plan and act. Quantification and estimation of landslide hazards is an hour in many countries where the quantum and frequency of landslides occurring in the last few decades are of major concern. Several methods have been studied by researchers. One such technique employed is machine learning, which is suitable for handling a large amount of data to predict the occurrence of landslides using various attributes. It is found in many studies that the critical role in landslide initiation is not only played by rainfall and earthquakes but also by intrinsic factors such as slope steepness, soil properties, lithology, etc. This work focuses on reviewing recent work done on landslide mapping, rainfall-induced landslides, and predictive methods of machine learning algorithms to map hazard vulnerability in tandem with GIS techniques

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Why is it important?

The Evolution of landslides is influenced by multiple parameters, including tectonic, rainfall, water table fluctuation, soil condition, nature of the slope, vegetation availability, undercutting, and human activities in the region. Slow-moving landslides cause huge damage in terms of economy and ravaging facilities across their travel path, resulting in huge losses to human life.

Perspectives

Writing this article was a great pleasure as it has co-authors with whom I have had long standing collaborations. This article also lead to rare disease groups contacting me and ultimately to a greater involvement in rare disease research.

Prof Gobinath R
S R Engineering College

Read the Original

This page is a summary of: Soft computing applications in rainfall-induced landslide analysis and protection—Recent trends, techniques, and opportunities, January 2022, Elsevier,
DOI: 10.1016/b978-0-323-89861-4.00036-1.
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