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Displaying 10 of about 10 resultsIn this paper, the authors present a brief overview of machine learning (ML) techniques, provide a general summary of the landslide studies conducted, in recent years, in the three above-mentioned categories, and make an attempt to critically evaluate the use of ML methods to model landslide processes. Upon the introduction of machine learning (ML)…
This preliminary study aims to demonstrate that machine learning (ML) techniques can be used to analyze monitoring data to select the most relevant variables for triggering shallow rainfall-induced landslides at a regional scale. Assessing the occurrence of shallow rainfall-induced landslides is crucial for engaging in effective short-term and long-term…
Climate change has increased the likelihood of the occurrence of disasters like wildfires, floods, storms, and landslides worldwide in the last years. Weather conditions change continuously and rapidly, and wildfires are occurring repeatedly and diffusing with higher intensity. The burnt catchments are known, in many parts of the world, as one of the ma…
This publication explores the contributions of science and technology in Asia. The first part evaluates the advancement of the science and technology in disaster risk reduction in 11 countries.
The second part of the report features 28 case studies and good practices on applying science and technology in different field of disaster risk reduction…
The project “Strengthening the disaster risk reduction capacity to improve the safety and security of communities by understanding disaster risk (SeDAR)” in Malaysia was launched in June 2018. This project is jointly conducted by Tohoku University in Japan, University Teknologi Malaysia, and the Selangor State Government with the support of Japan Intern…
The Status of Science and Technology report is an important step for monitoring the progress in the implementation of the Sendai Framework and an attempt to capture some of the progress across geographies, stakeholders, and disciplines towards the application of science and technology towards risk reduction in Asia-Pacific.
Developed by…
Natural hazards are becoming increasingly frequent within the context of climate change—making reducing risk and building resilience against these hazards more crucial than ever. An emerging shift has been noted from broad-scale, top-down risk and resilience assessments toward more participatory, community-based, bottom-up approaches. Arguably, non-scie…
This research uses the landslide inventory of Chittagong Metropolitan Area (CMA) to create a new Artificial Intelligence (AI) based insight system for the town planners and senior disaster recovery strategists of Chittagong, Bangladesh. The system generates dynamic AI-based insights for a range of complex scenarios created from 7 different landslide fea…
This study therefore tests an innovative approach of volunteer citizen science and an open mapping platform to build resilience to natural hazards in the remote mountainous parts of western Nepal. In this study, citizen scientists and mapping experts jointly mapped two districts of Nepal (Bajhang and Bajura) using the OpenStreetMap (OSM) platform.
The…
In this paper, the authors characterize experimentally the waves generated by the gravity-driven collapse of a dry granular column into water. Tsunami waves induced by landslides are a threat to human activities and safety along coastal areas. The generation of tsunami waves by landslides may be triggered by volcanic or seismic events not…