Cremen, G. et al see all authors
Multi-hazard disaster impact analysis outputs from synthetic future urban scenarios in 10 cities
https://doi.org/10.5285/30a025cc-4482-48a0-a0f9-9f5b71d7ef83
Cite this dataset as:
Cremen, G.; Gentile, R.; Dabeek, J.; Aljawhari, K.; Manandhar, V.; Rawal, P.; Nocera, F.; Rana, S.; Zisan, B.; Leandro, I.; Çaktı, E.; Kombe, W. (2026). Multi-hazard disaster impact analysis outputs from synthetic future urban scenarios in 10 cities. NERC EDS Environmental Information Data Centre. https://doi.org/10.5285/30a025cc-4482-48a0-a0f9-9f5b71d7ef83
Download/Access
This dataset is available under the terms of the Open Government Licence
By accessing or using this dataset, you agree to the terms of the relevant licence agreement(s). You will ensure that this dataset is cited in any publication that describes research in which the data have been used.
This dataset comprises spatially explicit risk analysis outputs for 10 study areas, representing potential disaster impacts across various future urban development scenarios, that are created by different community groups within each study area. Study areas include Istanbul (Türkiye), Nablus (Palestine), Chattogram (Bangladesh), Cox's Bazaar (Bangladesh), Nairobi (Kenya), Nakuru (Kenya), Quito (Ecuador), Kokhana (Nepal), Rapti (Nepal) and Darussalam (Tanzania). The data quantify the physical, social, and economic risks resulting from seismic activity or floods or landslides interacting with projected land-use plans and building typologies.
Key components of the dataset include attributes on damage states for each building and eight metrics related to socio-demographic characteristics:
- Number of workers unemployed,
- Number of children with no Access to education
- Number of households with no Access to hospital
- Number of individuals with no Access to hospital
- Number of households displaced
- Number of homeless individuals
- Population displacement
- Number of casualties
Details on the computation of each metric is provided in the readme file.
This dataset was created as case studies for the Tomorrows Cities: Tomorrowville virtual testbed. It is supported by NERC as part of the GCRF Urban Disaster Risk Hub (NE/S009000/1).
Key components of the dataset include attributes on damage states for each building and eight metrics related to socio-demographic characteristics:
- Number of workers unemployed,
- Number of children with no Access to education
- Number of households with no Access to hospital
- Number of individuals with no Access to hospital
- Number of households displaced
- Number of homeless individuals
- Population displacement
- Number of casualties
Details on the computation of each metric is provided in the readme file.
This dataset was created as case studies for the Tomorrows Cities: Tomorrowville virtual testbed. It is supported by NERC as part of the GCRF Urban Disaster Risk Hub (NE/S009000/1).
Publication date: 2026-04-09
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Formats
geojson, Comma-separated values (CSV)
Spatial information
Study area
Spatial representation types
Vector
Tabular (text)
Tabular (text)
Spatial reference system
WGS 84
Provenance & quality
The dataset was generated using the Tomorrow's Cities Decision Support Environment (TCDSE) workflow, designed to assess disaster risks in future urban planning scenarios. The process involved the integration of three primary components:
1. Hazard Models: Physics-based simulations or probabilistic models for relevant hazards (e.g., earthquakes, floods, landslides) specific to the project location.
2. Future Exposure Scenarios: Spatially explicit projections of future urban growth, land use, and building typologies, co-developed with local stakeholders and planning authorities.
3. Vulnerability Functions: Engineering-based curves defining the susceptibility of proposed infrastructure to specific hazard intensities.
These components were processed through a computational risk engine (served under https://webapp.tomorrowscities.org) to calculate potential impacts (e.g., physical damage, displacement, economic loss) for various future development trajectories.
Quality Assurance (QA) Steps:
1. Input Validation: Hazard models and exposure data were validated by local domain experts and compared against historical baseline data where applicable.
2. Internal Consistency Checks: The computational workflow underwent code reviews and unit testing to ensure data integrity during the integration of hazard and exposure layers.
3. Output Verification: Preliminary risk results were reviewed in stakeholder workshops to ensure plausibility and alignment with local knowledge before finalization.
1. Hazard Models: Physics-based simulations or probabilistic models for relevant hazards (e.g., earthquakes, floods, landslides) specific to the project location.
2. Future Exposure Scenarios: Spatially explicit projections of future urban growth, land use, and building typologies, co-developed with local stakeholders and planning authorities.
3. Vulnerability Functions: Engineering-based curves defining the susceptibility of proposed infrastructure to specific hazard intensities.
These components were processed through a computational risk engine (served under https://webapp.tomorrowscities.org) to calculate potential impacts (e.g., physical damage, displacement, economic loss) for various future development trajectories.
Quality Assurance (QA) Steps:
1. Input Validation: Hazard models and exposure data were validated by local domain experts and compared against historical baseline data where applicable.
2. Internal Consistency Checks: The computational workflow underwent code reviews and unit testing to ensure data integrity during the integration of hazard and exposure layers.
3. Output Verification: Preliminary risk results were reviewed in stakeholder workshops to ensure plausibility and alignment with local knowledge before finalization.
Licensing and constraints
This dataset is available under the terms of the Open Government Licence
Cite this dataset as:
Cremen, G.; Gentile, R.; Dabeek, J.; Aljawhari, K.; Manandhar, V.; Rawal, P.; Nocera, F.; Rana, S.; Zisan, B.; Leandro, I.; Çaktı, E.; Kombe, W. (2026). Multi-hazard disaster impact analysis outputs from synthetic future urban scenarios in 10 cities. NERC EDS Environmental Information Data Centre. https://doi.org/10.5285/30a025cc-4482-48a0-a0f9-9f5b71d7ef83
Supplemental information
Cremen, G., Galasso, C., McCloskey, J., Barcena, A., Creed, M., Filippi, M. E., Gentile, R., Jenkins, L. T., Kalaycioglu, M., Mentese, E. Y., Muthusamy, M., Tarbali, K., & Trogrlić, R. Š. (2023). A state-of-the-art decision-support environment for risk-sensitive and pro-poor urban planning and design in Tomorrow's cities. International Journal of Disaster Risk Reduction, 85, 103400.
Cremen, G., Galasso, C., & McCloskey, J. (2022). A Simulation‐Based Framework for Earthquake Risk‐Informed and People‐Centered Decision Making on Future Urban Planning. Earth's Future, 10(1).
Correspondence/contact details
Authors
Other contacts
Publisher
NERC EDS Environmental Information Data Centre
info@eidc.ac.uk
Rights holder
University of Edinburgh
manager@tomorrowscities.org

https://orcid.org/0000-0002-6699-7312