Science-policy-practice interface

This study aims to map and analyse the evolution, structure, and collaborative dynamics of scholarly output in this interdisciplinary domain through a comprehensive bibliometric analysis.

This study conducted a comprehensive fire risk evaluation in Jinan City using five machine learning models—Random Forest (RF), Support Vector Machine (SVM), Maximum Entropy (MaxEnt), Light Gradient-Boosting Machine, and Convolutional Neural Network (CNN).

This study reflects on progress towards the Sendai Framework for Disaster Risk Reduction, focusing on the health of the global-level science–policy interface.

Researchers combined a literature review with stakeholder interviews to assess how wildfire technology innovations move from idea to field use and to identify when and how innovation stalls.

Researchers found that artificial intelligence can learn to estimate heat by studying patterns in ordinary red-green-blue (RGB) images, the type of standard color photos taken by digital cameras.

Frontline practitioners share lessons on translating climate intelligence into action without widening risk or exclusion in fragile and conflict-affected settings.

This paper describes an AI‑based method for mapping landslide risk using Slide3 slope analysis, field tests like ERT and SPT, and GIS tools to create a clear, reliable picture of where landslides are most likely to occur.

This paper aims to advance the understanding and forecasting of volcanic eruptions by evaluating the short‑ and long‑term memory of volcano‑tectonic seismicity during unrest.

Researchers have begun a new €5 million EU-funded project that will allow fibre optic cable lines under our roads, fields, and seas to double up as sensors that spot earthquakes and infrastructure damage, monitor traffic, and detect changes.

This paper details the development and implementation of Volcano Voices, an interactive mapping methodology designed to collect environmental data and disseminate research findings ethically within communities affected by natural hazards.

End users, such as Indigenous community members developing climate adaptation efforts, make better use of climate models when researchers collaborate with them from the start.

This paper highlights how policymakers in Asia and the Pacific can harness new knowledge to protect people from extreme heat using improved risk tools and warning systems, and resilient public services and infrastructure.

Human-caused climate change has a “fingerprint” on weather that scientists can distinguish from the signals of natural climate variability. This fingerprint of human-caused climate change can be identified and measured in daily weather and extreme events.

A team of researchers from the Seismology Group of the Department of Physics "Ettore Pancini," has reconstructed in detail how the Earth's crust changed after a 6.2-magnitude earthquake.

This brief examines how the rights and needs of assistive technology users can be more effectively addressed in DRR and climate action.

The Santiago Network Secretariat is pleased to announce this call for proposals to catalyze technical assistance from organizations, bodies, networks and experts (OBNEs) in response to a request from the Cook Islands.

The agreement between UNDRR and the ISC extends the collaboration between the two organizations through 2035, reinforcing a shared commitment to harness science for a safer and more resilient world.

This edition of the Green Technology Book looks at solutions for confronting climate disasters, highlighting how innovation is transforming disaster preparedness, response, and recovery.

The World Meteorological Organization community will continue to provide science-based climate monitoring to anchor COP negotiations in authoritative evidence, and to support both mitigation and adaptation.

On the International Day for Disaster Risk Reduction 2025, the E-STAG, in support of the UNDRR ROECA, organized a webinar "Financial incentives as a strategy for promoting disaster resilience."

In a unique scientific trial, 36 volunteers were buried alive under snow to test a new device that could extend survival during avalanches.

The state of Acre counts on science to optimize its limited resources for monitoring and combating forest fires and environmental destruction.

A study published in Nature Communications reveals a breakthrough: citizens' smartphones can be used to create highly detailed site amplification maps.

Arizona State University researchers are using artificial intelligence to characterize a vast array of wildfire fuels and generate fuel maps at a much higher resolution than existing maps.

This research introduces an automated method for mapping glacial lakes in Himachal Pradesh based on multi-source remote sensing data and a random forest (RF) classifier.

Machine learning is expanding scientists’ catalogs of quakes and refining maps of underground faults. It also promises to improve quake forecasts.

Subducting plates are stronger in certain directions than in others, which may be a factor in how earthquakes occur and how seismic waves propagate.

The study suggests that within the next 30 to 40 years, ENSO may transition from its current irregular El Niño-La Niña cycles to a more consistent pattern of strong oscillations marked by larger sea surface temperature (SST) fluctuations.

Over six months, each Resident will lead three sessions that bring together people working at the intersections of STEM, disaster and climate management, and the arts.

Discover science-driven paths to resilience, Nature-based Solutions and a safer future through these five reads.

The new findings by Reiss and her colleagues advance volcano seismology by offering valuable insights into the dynamics of magma movement.

Researchers are developing artificial intelligence systems that can be translated into technologies for augmenting situational awareness and resilience capabilities across all stages of a weather hazard to reduce the impact of disasters.

Artificial intelligence models have improved weather forecasting, but their inner workings are largely opaque. A new approach could make their predictions more interpretable by scientists.

The collaboration combines IWMI’s research capabilities with Microsoft’s cutting-edge AI technology to tackle pressing water management challenges in southern Africa’s Limpopo River Basin.

Mahasarakham Municipality and University in Thailand’s Northeast are showing how local governments can build urban resilience – by engaging communities, embracing creativity and drawing on local knowledge.

Mapping and tracking heat stress - not just across cities, but street by street - is essential to inform early warning systems, urban planning, and public health interventions.

This summer 2025 was the 30th anniversary of the deadliest weather event in Chicago’s history. Daniel Horton of NU coleads the Defusing Disasters Working Group, a team formed to help make sure that something similar never happens again.

In Limbe, Cameroon, flooding is not just caused by heavy rainfall. Rather from a complex interplay of land-use decisions, poor waste management, weak governance and a lack of infrastructure. Tackling this requires a systems‑thinking approach.