GIS and mapping

This paper identifies transboundary GLODF threats across the Himalayas and projects their future evolution under climate change, highlighting growing risks, hotspots along the China–Nepal border, and the need for stronger monitoring and early warning.

A globally scalable framework combines dense-array seismic observations, rupture imaging and shaking models to estimate earthquake impacts within minutes of origin time.

A national Coastal Exposure Index maps relative climate hazard exposure around Ireland, highlighting exposure hotspots, coastal habitats’ protective role and populations and cultural heritage sites near highly exposed coastlines.

A team analyzed radar data from European Space Agency’s Sentinel-1 satellites acquired between 8 January and 18 August. The last observation was only seven days before the disaster. Images revealed accelerated glacier-rock movement before the collapse.

Scientists used seismic data, satellite imagery and drone surveys to rapidly identify a massive landslide as the cause of the deadly Nepal-Tibet flood. The event highlights cascading hazards, glacier instability and the need for stronger early warning.

UNU-EHS research maps disaster risks in Bosnia & Herzegovina and explores how communities can build resilience to a changing climate.

Official flood maps shape disaster preparedness, insurance decisions and urban planning, but large parts of USA are unmapped or under-mapped, so some communities may be left unaware of risks they face, limiting their ability to prepare for future floods.

Coastal groundwater responds to sea level rise in different ways. Where the water table is free to rise with the sea, it does exactly that, rising toward the surface and increasing the risk of groundwater flooding.

This study presents machine learning and GIS-based approach to map nationwide susceptibility to floods, landslides, and identify their potential interaction zones, and delineate critical multi-hazard flow zones through spatial adjacency analysis. Using

During storms, water rushes into low-lying areas and has nowhere to go. To highlight the problem, the researcher partnered with community groups to develop a flood mapping tool that combines satellite data with information shared by residents.

This study examines how successive governments´ state power has shaped the urban landscape in Varanasi, India, and how these interventions have led to uneven vulnerabilities that are now being exacerbated by increasing climate stresses.

Historical observations are our best way of filling crucial gaps in Australia’s climate records, allowing us to sharpen our forecasts of future weather extremes in a warmer world.

Intensifying at a dramatic pace, Hurricane Genevieve became the first Category 5 storm of 2026 in the Eastern Pacific, with top sustained winds touching 160 mph. Fortunately, Genevieve’s wrath is playing out far away from land.

The impacts of climate change are escalating, compounded by urban expansion into fire-prone areas. Eight cutting-edge technologies have the potential to revolutionize wildfire risk reduction strategies.

Destructive landslides are more likely to occur after wildfires, but how does the hazard change as vegetation regrows? Scientists are improving prediction methods to reduce costly unnecessary warnings

Sea level rise driven by climate change is increasingly threatening coastal cities worldwide through flooding, ocean acidification, and erosion, highlighting the urgent need for adaptation and resilience strategies.

This paper analyses drought severity across Mexican regions between 2000 and 2025 using satellite-based indicators of vegetation health and surface moisture.

This analytical study aims to identify strategic land restoration opportunities and inform policy and investment planning for resilient landscape management in Turkmenistan.

This study captures how households in Delhi experience heat, combining high-resolution climate and remote-sensing data with a primary household survey to estimate impacts on health, productivity, and coping capacity based on appliance ownership.

This report presents the findings from the first of two activities conducted with the primary aim of gaining insights into the increasing threats posed by wildfire outbreaks to both forests and local communities in Thailand.

Researchers led by the Technical University of Munich (TUM) have created the first global atlas of the influence of tides on coastal rivers.

Researchers in South Dakota State University's Geospatial Sciences Center of Excellence utilized satellite data to better understand how destructive wildfires swept through Los Angeles in January 2025.

This study develops a Spatial Footprint Impact Assessment framework (SFIA), which is applied to the Three Gorges Project (TGP), evaluating the spatial heterogeneity of indirect flood-retention benefits induced by the TGP across 31 provinces in China.

In Iraq, moderate storms become disasters because flood risk is shaped as much by urbanization, degraded ecosystems, and weak governance as by rainfall intensity itself.

This paper presents a generative-AI–assisted, open-source framework designed to democratize access to complex climate data and strengthen public climate literacy, using Kolkata as a case study.

This study outlines a comprehensive, data‑driven strategy for reducing coastal disaster risk in Kuala Nerus and Kuala Terengganu, Malaysia, where communities face increasing exposure to erosion, flooding, sea‑level rise and climate‑related hazards.

Geographic information system (GIS) maps help researchers, policymakers, and community members see how environmental risks are spread throughout a given region.

This study presents a large-scale screening method using GIS techniques and remotely sensed data to assess the overtopping potential of RWCs.

This study focuses on the identification of optimal safe assembly areas in the case of urban flash floods using Geographic Information System (GIS) and machine learning techniques.

New mapping tool helps communities anticipate sea‑level rise by showing where salt marshes will migrate, guiding smarter development, conservation, and resilience planning. Built collaboratively, it offers a model other coastal states can replicate.

After the avalanche winter of 1950/51, SLF researchers developed a system for mapping areas at risk from avalanches. The resulting colour scale for danger zones still forms the basis of the hazard maps produced today.

Can we build landslide susceptibility maps that are more objective, transparent, and useful for local authorities and residents?

This article examines how maps are developed and used in climate security work, calling for more reflexive approaches that recognise limitations, draw on diverse knowledge, and ensure transparency in data sources and methods.

The researchers aim to produce the most detailed mapping of space weather to date and to gain a deeper understanding of the processes that lead to the formation of strong geomagnetic storms.

This study develops habitability functions to quantify the relationship between hydrodynamic hazards and the probability of buildings becoming uninhabitable following Hurricane Irma.

This study demonstrates how advances in multi-GPU computing can enable high-resolution, operational pluvial flood forecasting for large urban areas.

This article covers the growing challenge of heavy rainfall events becoming more frequent and intense under climate change, increasing flood and damage risks for agriculture while localized impacts remain difficult to predict.

This study combines time-series remote sensing data and analytical algorithms to quantify the dynamics of ecosystem disturbance and recovery within this agricultural heritage landscape.

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 study examines the factors influencing landslides in the Benighat-Rorang RM by analyzing soil structure, geology, land cover, geomorphology, fault lines, weather data, and road density to generate a comprehensive landslide Susceptibility Mapping.

Satellite and reanalysis data show aerosol changes in the Northern and Southern Hemispheres largely cancel out, shifting attention to cloud changes due to surface warming and natural climate variability.

This study employed comparative analysis, spatial interpolation, and random forest regression to develop an approach for the rapid assessment of severely affected areas using multiple mobile signaling indicators and multi-temporal analysis.

This study develops a probabilistic GIS-based flood risk assessment framework that integrates the Analytic Hierarchy Process (AHP) with its Monte Carlo extension (MC-AHP) for the Chengdu, China, metro network.

Human activities - such as mining, oil and gas extraction, dam-building and tapping into geothermal energy - have set off unexpected quakes in these stable regions.