Data and information management

Our novel artificial intelligence model can predict extreme storm surges with high accuracy, including under future climate conditions.

Maximum Information today announces the launch of PsiClone, a new live event monitoring platform that helps insurers, reinsurers and underwriting teams monitor portfolio exposure and act earlier during active tropical cyclone events.

The paper demonstrates that a knowledge-driven VGE system with 3D animations significantly improves public disaster risk perception compared to static or textual formats, validated through eye-tracking experiments and comparative NLP model analysis.

The study analyzes the evolution of DRR policies in Brazil and examines how these developments are reflected in disaster outcomes.

This publication explores how generative language models combine social media, news and weather data to detect disasters quickly and accurately, using satellite data to validate results from flood and wildfire case studies.

ML models for hydrological forecasting, even when given perfect inputs, cannot yet match the reliability of experienced human forecasters operating real-world prediction systems.

The authors call for expanded detection and attribution studies to better quantify how specific climate shifts drive health outcomes, and to translate those findings into actionable public health guidance.

This study developed an integrated urban flood risk assessment framework for cities with significant spatial heterogeneity, combining differentiated hydrological-hydrodynamic modeling with complementary grid-based.