Datasets:
Global Multi-Hazard Risk Assessment Dataset
Dataset Description
This dataset contains comprehensive global multi-hazard risk assessment data covering 9 different natural hazard types. The data is sourced from the UNEP Grid and represents state-of-the-art hazard modeling for disaster risk assessment and climate change adaptation planning.
Dataset Summary
- Total Size: ~50GB of geospatial data
- Coverage: Global
- Resolution: Variable (1km to 11km depending on hazard type)
- Coordinate System: WGS84 (EPSG:4326)
- Format: GeoTIFF (.tif) and Shapefile (.shp)
- Time Periods: Current climate (1979-2016) and future climate scenarios (2017-2100)
Hazard Types
1. Flood Hazards π
- Files: 18 TIFF files
- Return Periods: 2, 5, 10, 25, 50, 100 years
- Climate Scenarios:
- Existing climate (1979-2016)
- SSP1 Lower bound (RCP2.6)
- SSP5 Upper bound (RCP8.5)
- Model: Continuum hydrological model with Manning equation hydraulic modeling
- Resolution: ~1km
- Total Size: ~50GB
2. Earthquake Hazards π
- Files: 1 TIFF file
- Parameter: Peak Ground Acceleration (PGA) for 475-year return period
- Model: Global seismic hazard assessment
- Resolution:
3 minutes (5.5km at equator)
3. Volcano Hazards π
- Files: Shapefile format (Volcano.shp + associated files)
- Content: Global volcano locations and attributes
- Format: Vector data (can be converted to raster)
- Source: Global volcano database
4. Tropical Cyclone Hazards π
- Files: 6 TIFF files
- Parameter: Wind velocity
- Return Periods: 25, 50, 100 years
- Climate Scenarios: Current climate and climate change (RCP8.5)
- Resolution: 6 minutes (~11.1km at equator)
- Total Size: ~50MB
5. Tsunami Hazards π
- Files: 1 GeoPackage file
- Parameter: Tsunami run-up height on coastline
- Return Period: 475 years
- Coverage: Coastal areas with tsunami hazard
- Format: Vector data
6. Landslide Hazards ποΈ
- Files: 4 TIFF files
- Types:
- Earthquake-triggered landslides
- Precipitation-triggered landslides
- Climate Scenarios: Existing climate and SSP5 RCP8.5
- Parameter: Susceptibility classes
7. Drought Hazards βοΈ
- Status: Metadata available, files pending
- Coverage: Global drought risk assessment
8. Storm Surge Hazards π
- Status: Metadata available, files pending
- Coverage: Coastal storm surge risk
Data Structure
dataset/
βββ flood/ # Flood hazard data
β βββ metadata.json
β βββ *.tif # 18 flood hazard TIFF files
βββ earthquake/ # Earthquake hazard data
β βββ metadata.json
β βββ *.tif # PGA data
βββ volcano/ # Volcano hazard data
β βββ metadata.json
β βββ Volcano.shp # Shapefile
β βββ Volcano.dbf # Database file
β βββ Volcano.prj # Projection file
β βββ Volcano.shx # Index file
βββ tropical_cyclone/ # Tropical cyclone data
β βββ metadata.json
β βββ *.tif # 6 wind velocity files
βββ tsunami/ # Tsunami hazard data
β βββ metadata.json
β βββ *.gpkg # GeoPackage file
βββ landslide/ # Landslide hazard data
β βββ metadata.json
β βββ *.tif # 4 susceptibility files
βββ drought/ # Drought hazard data
β βββ metadata.json
βββ storm_surge/ # Storm surge hazard data
βββ metadata.json
Usage
Loading the Dataset
import rasterio
import geopandas as gpd
import os
# Load a flood hazard TIFF
flood_data = rasterio.open('flood/flood_hazard_100_years_-_existing_climate.tif')
print(f"Shape: {flood_data.shape}")
print(f"CRS: {flood_data.crs}")
print(f"Bounds: {flood_data.bounds}")
# Load volcano shapefile
volcano_data = gpd.read_file('volcano/Volcano.shp')
print(f"Number of volcanoes: {len(volcano_data)}")
print(f"Columns: {volcano_data.columns.tolist()}")
Converting Shapefiles to Raster
import subprocess
# Convert volcano shapefile to optimized TIFF with 1km resolution
subprocess.run([
'gdal_rasterize',
'-burn', '1',
'-tr', '0.009', '0.009', # 1km resolution
'-a_nodata', '0',
'-ot', 'Byte',
'-co', 'COMPRESS=LZW',
'-co', 'TILED=YES',
'volcano/Volcano.shp',
'volcano_optimized_1km.tif'
])
Data Processing
Optimization for Large Files
The flood hazard files are large (~3-4GB each). For efficient processing:
- Use NoData values instead of storing zeros
- Apply compression (LZW or DEFLATE)
- Use tiled format for better performance
- Consider data type optimization (Byte vs Float32)
Coordinate System
All data uses WGS84 (EPSG:4326) coordinate system:
- Longitude: -180Β° to +180Β°
- Latitude: -90Β° to +90Β°
- Units: Decimal degrees
Applications
This dataset is suitable for:
- Risk Assessment: Multi-hazard risk modeling
- Climate Adaptation: Future scenario planning
- Disaster Management: Emergency response planning
- Research: Climate change impact studies
- Policy Making: Infrastructure planning
- Insurance: Risk pricing and underwriting
Citation
If you use this dataset, please cite:
@dataset{global_multi_hazard_2024,
title={Global Multi-Hazard Risk Assessment Dataset},
author={UNEP Grid and INGENIAR Risk},
year={2024},
url={https://hazards-data.unepgrid.ch/},
note={Multi-hazard disaster risk model of infrastructure and buildings at the global level}
}
References
- Flood Data: Silvestro et al. (2013, 2015) - Continuum hydrological model
- Climate Data: W5E5 Global Meteorological dataset, ISIMIP3b
- Background Paper: Multi-hazard Disaster Risk Model
- Source: UNEP Grid
License
This dataset is released under the MIT License. See the license file for details.
Contact
For questions about this dataset, please contact:
- UNEP Grid: https://unepgrid.ch/en
- INGENIAR Risk: https://www.ingeniar-risk.com/en
Updates
- v1.0 (2024): Initial release with 9 hazard types
- Future: Additional hazard types and higher resolution data planned
This dataset represents a comprehensive global multi-hazard risk assessment suitable for research, policy-making, and disaster risk management applications.
- Downloads last month
- 21