Chen et al. (2026) European coastal deformation drives unequal exposure to climate hazards

Identification

• Journal: Communications Earth & Environment
• Year: 2026
• Date: 2026-01-14
• Authors: Huilin Chen, Chisheng Wang, Jose Martinez Fernandez, Huawei Hou, Lin Chang, Qingquan Li
• DOI: 10.1038/s43247-026-03190-y

Research Groups

• Ministry of Natural Resources (MNR) Key Laboratory for Geo-Environmental Monitoring of Great Bay Area & Guangdong Key Laboratory of Urban Informatics & Shenzhen Key Laboratory of Spatial Smart Sensing and Services, School of Architecture & Urban Planning, Shenzhen University, Shenzhen, China
• Institute of Geosciences (IGEO), CSIC-UCM, Madrid, Spain
• Faculty of Geo-Information Science and Earth Observation, University of Twente, Enschede, The Netherlands

Short Summary

This study assesses the physical and social dimensions of coastal exposure to climate hazards across European coasts by integrating Interferometric Synthetic Aperture Radar measurements with land-cover, population, and socioeconomic data. It finds unequal exposure and vulnerability, with Northern Europe experiencing uplift while Mediterranean regions predominantly subside, projecting significant inundation risks by 2050 that disproportionately affect older adults, marginalized populations, and economically constrained regions.

Objective

• To systematically assess how the spatial patterns of vertical land motion (VLM) interact with land cover and socio-economic factors to shape social vulnerability to climate hazards (relative sea level rise) across the entire European coastal zone.

Study Configuration

• Spatial Scale: European coastal zone, defined as areas up to 100 kilometers inland from the coastline, analyzed at a 100-meter spatial resolution.
• Temporal Scale:
  • Vertical Land Motion (VLM) measurements: 2019–2023 (baseline), with a consistency check for 2018–2022.
  • Projections for inundation, population, and assets: 2050.
  • VLM rates are assumed constant from 2022 to 2050 for projections.

Methodology and Data

• Models used:
  • Bathtub model for predicting coastal inundation risk.
  • Constant-rate baseline projection for Vertical Land Motion (VLM).
• Data sources:
  • Vertical Land Motion (VLM): Interferometric Synthetic Aperture Radar (InSAR) data from Sentinel-1 satellite, European Ground Motion Service (EGMS) ortho product (100 m spatial resolution).
  • Land Cover: Urban Atlas 2018 dataset from Copernicus Earth Observation programme (100 m spatial resolution, 43 categories, aggregated to 4 primary types).
  • Digital Elevation Model (DEM): Copernicus Programme (30 m resolution).
  • Sea Level Rise (SLR): IPCC assessment reports, SSP2-4.5 scenario (median SLR rate).
  • Mean Sea Level (MSL): Permanent Service for Mean Sea Level (PSMSL).
  • Population: Projected population data for 2050 under the SSP2 scenario.
  • Buildings: Microsoft’s Building Footprints dataset.
  • Asset Value: Country-level housing price data from Statista and Numbeo databases.
  • Socioeconomic/Demographic: Official statistical offices of European countries (economic and demographic indicators), United Nations World Population Prospects 2024 (age structure projections), European Union Agency for Fundamental Rights (Roma population poverty indicators), Spanish Gypsy Foundation (Roma settlement spatial distribution).
  • Coastline: ne10 mcoastline dataset from Natural Earth.

Main Results

• Vertical Land Motion (VLM) Patterns: Northern Europe (e.g., Sweden, Finland) exhibits significant ground uplift, averaging over 5 mm per year, primarily due to glacial isostatic adjustment. Conversely, subsidence is prevalent in Mediterranean regions, with localized hotspots (e.g., Netherlands, Po River Delta, Malta) showing rates exceeding 2 mm per year. Wetlands experience the highest mean subsidence rates at 2.3 ± 3.1 mm per year.
• Land Cover Exposure: Forested/semi-natural and agricultural areas constitute nearly 80% of the total subsidence-affected land. Artificial areas show concentrated subsidence, peaking around -1 mm per year. Wetlands, despite covering only 2% of coastal areas, account for over twice their proportion in subsidence-prone zones.
• Projected Inundation by 2050 (SSP2-4.5 scenario, no flood prevention):
  • Approximately 94,000 square kilometers of European coastal land are projected to be exposed to inundation.
  • Nearly 25 million residents (86% of the total coastal population) and over 8 million buildings (6.8% of the total building stock) may be directly affected.
  • The Netherlands faces the most severe economic impact, with 3.5 million exposed buildings and estimated asset values exceeding €3.4 trillion.
  • Agricultural areas are the predominant land cover type within inundation risk zones, accounting for 67.1% of exposed areas.
• Social Vulnerability and Inequality:
  • Adaptive capacity varies significantly along a socioeconomic gradient, with economically developed areas generally demonstrating stronger climate resilience.
  • Older adults (>65 years) and children (<15 years) currently comprise about 40% of the exposed population, projected to increase to 60% by 2050, indicating heightened demographic vulnerability.
  • Marginalized communities, such as the Roma population, are disproportionately concentrated in high-risk zones, facing compounded vulnerabilities due to economic disadvantage, social exclusion, poor housing conditions, and limited institutional support.
• Risk Aggregation: High subsidence areas often coincide with low-lying, highly urbanized regions, leading to an aggregation of high physical exposure and high social vulnerability, particularly for socio-economically disadvantaged groups.

Contributions

• Provides a unified and systematic assessment of coastal subsidence and its socio-economic implications across the entire European continent.
• Develops a multi-source exposure risk framework by integrating validated vertical land motion (VLM) mapping with land cover and socioeconomic indicators.
• Reveals the complex interplay between natural physical processes (VLM) and social structures, highlighting the spatial heterogeneity of exposure and vulnerability.
• Identifies specific vulnerable populations (older adults, children, marginalized communities) and economically constrained regions disproportionately affected by climate hazards, offering a scientific basis for equitable adaptation planning.

Funding

• National Natural Science Foundation of China (42374018)
• Guangdong Basic and Applied Basic Research Foundation (2025B1515020092)
• Disciplines Breakthrough Project in Aerospace Information and Spatiotemporal Intelligence, MOE China
• Shenzhen Science and Technology Program (KCXFZ20240903093000002 and SYSPG20241211173845013)
• Grant G2HOTSPOTS (PID2021-122142OBI00) from the AEI/10.13039/ 501100011033/Union EuropeaNextGenerationEU/PRTR

Citation

@article{Chen2026European,
  author = {Chen, Huilin and Wang, Chisheng and Fernandez, Jose Martinez and Hou, Huawei and Chang, Lin and Li, Qingquan},
  title = {European coastal deformation drives unequal exposure to climate hazards},
  journal = {Communications Earth & Environment},
  year = {2026},
  doi = {10.1038/s43247-026-03190-y},
  url = {https://doi.org/10.1038/s43247-026-03190-y}
}