This dashboard is focusing on issues related to landslides and is fed by data from a variety of sources: worldwide news, published science articles, AI policies, education resources, and innovation ecosystems.
The dashboard is configurable and can explore other related issues and comparative data-driven scenarios in landslide research.
The initial interactive visualisation modules show the main concepts in landslide-related research (on the top left side) and their worldwide coverage (below on the left side), the SDG coverage on related policies (on the top right side), and the evolution of research publications in these topics (below on the right side).
Using mouse over the visualization graphs helps to get more information on these plots.
LANDSLIDES CASE STUDIES
2025 Blatten, Switzerland glacier collapse
The 2025 Blatten landslide in Switzerland illustrates the importance of integrating heterogeneous information sources into a unified analytical framework for disaster awareness and knowledge synthesis.
Using the Landslides Knowledge Observatory dashboards, media coverage of the event can be rapidly analyzed across geographic distribution and languages, revealing its global attention and communication dynamics. The media dashboard shows how reporting on the Blatten event spread internationally, with coverage appearing across multiple continents and languages—dominated by English but also including Indonesian, Chinese, Spanish, and others—highlighting the transnational relevance of landslide disasters and the role of global media networks in disseminating risk information. At the same time, the scientific concept dashboard connects the event to the main disciplinary domains studying landslides, such as geotechnical engineering, geomorphology, geology, and environmental science, while mapping these concepts to relevant Sustainable Development Goals (SDGs), particularly SDG 11 (Sustainable Cities and Communities), SDG 13 (Climate Action), SDG 15 (Life on Land), SDG 9 (Industry, Innovation and Infrastructure), and SDG 6 (Clean Water and Sanitation). Together, these dashboards demonstrate how integrated analytics linking media signals, scientific concepts, and SDG frameworks can provide a multidimensional understanding of landslide events, supporting improved situational awareness, interdisciplinary research, and evidence-based policy responses to natural hazards.
2024 Enga, Papua New Guinea landslide
The 2024 Enga landslide in Papua New Guinea, one of the most devastating recent landslide disasters, highlights the importance of integrated knowledge analysis for understanding the broader scientific, policy, and societal dimensions of natural hazards.
Through the Landslides Knowledge Observatory dashboards, the event can be contextualized within a wider ecosystem of research, policy priorities, and sustainable development challenges. Analysis of the 100 SDG-related topics in scientific literature shows that landslide research is strongly linked with themes such as disaster risk, water systems, reforestation, land management, and climate-related impacts, reflecting the interdisciplinary nature of landslide science. The distribution of medical and environmental topics across relevant SDGs further emphasizes how landslides intersect with goals such as SDG 6 (Clean Water and Sanitation), SDG 15 (Life on Land), and SDG 13 (Climate Action), where topics such as environmental monitoring, soil degradation, river systems, and ecosystem stability are closely associated with landslide risk. In parallel, the analysis of AI and natural disaster policy topics indicates growing attention to the role of artificial intelligence, technology, and data-driven approaches within disaster governance frameworks, alongside themes such as climate change, infrastructure resilience, and emergency management. Finally, the global prevalence of AI and landslides in public policy discussions—spanning countries such as the United States, Australia, the United Kingdom, Japan, and others—demonstrates the increasing international recognition of AI as a tool for hazard monitoring, risk assessment, and disaster preparedness. Together, these dashboards illustrate how a single catastrophic event like the Enga landslide can be examined through multiple analytical lenses, linking scientific research, health and environmental impacts, technological innovation, and policy responses within the broader framework of the Sustainable Development Goals.
2021 Atami, Japan landslide
The 2021 Atami landslide in Shizuoka Prefecture, Japan, triggered by extreme rainfall, provides a compelling case for examining how disaster events are reflected across social media discourse and scientific research.
Using the Landslides Knowledge Observatory dashboards, Twitter data reveals that discussions of the event quickly spread beyond Japan, with tweet locations concentrated in North America, Europe, and parts of Asia, illustrating the rapid global dissemination of disaster information through digital platforms. Sentiment analysis of tweets shows that public reactions were overwhelmingly concerned, with negative sentiment accounting for 48.48% and neutral sentiment 46.96%, while only a small portion (4.56%) expressed positive sentiment, reflecting the tragedy and uncertainty surrounding the event. In parallel, the analysis of published scientific literature demonstrates the multidisciplinary nature of landslide research associated with such disasters. The top expert domains represented include geotechnical engineering (14.96%), hydrology (14.69%), geology (14.82%), geomorphology (10.4%), and geography (10.37%), alongside environmental science, oceanography, cartography, and physical geography. Examination of analysis methods used in scientific papers highlights the prominence of landslide modelling, scientific assessment frameworks, slope stability analysis, soil characterization, rainfall analysis, and drainage and causality studies. Together, the integration of social media signals and scientific knowledge provides a richer understanding of how landslide events such as the Atami disaster are perceived by the public, investigated by the scientific community, and communicated globally, demonstrating the value of integrated data dashboards for disaster awareness and research coordination.
2010 Gansu, China mudslide
The 2010 Gansu mudslide in Zhouqu County, China, one of the deadliest landslide disasters of the last decades, illustrates the importance of integrating education, research, and policy knowledge to better understand and respond to catastrophic natural hazards. Using the Landslides Knowledge Observatory dashboard, the event can be explored through multiple knowledge dimensions that reveal how disasters propagate across scientific, educational, and societal domains.
The Open Education dashboard highlights the main domains addressed in educational materials related to the event, including education sciences, scientific methodology, data analysis, and research practices, demonstrating the role of open educational resources (OERs) in disseminating disaster risk knowledge and supporting training for resilience. The SDG topics across OERs further connect the mudslide to broader development challenges, particularly SDG 8 (Decent Work and Economic Growth), SDG 4 (Quality Education), and SDG 3 (Good Health and Well-being), reflecting how disaster impacts intersect with economic inclusion, education policy, and community health. Complementing this perspective, the scientific literature dashboard reveals the interdisciplinary research landscape associated with the event, linking domain areas such as medicine, psychology, computer science, political science, and law to key SDG-related themes including climate change, poverty, food security, mental health, and water resource management. Finally, the timeline of scientific publications shows how scholarly attention to the Gansu mudslide evolved over time, with strong peaks in the years immediately following the disaster and sustained research activity in subsequent years as the event continued to inform studies on hazard mitigation, disaster governance, and climate-related risk. Together, these visual analytics demonstrate how data visualization dashboards can transform dispersed datasets into coherent insights, enabling researchers, policymakers, and educators to better understand the long-term scientific, social, and educational implications of major landslide disasters.
Developed in collaboration with IRCAI – International Research Centre on Artificial Intelligence under the auspices of UNESCO.