A Unified Spatial Database
The foundation of our risk-resilience framework is the extensive collection of geospatial data layers engineered from first-party and third-party sources.
From satellite observations, climate models to socio-economic data and text-based reports, we monitor a growing list of high-quality data sources and curate the best available data onto our platform.
During this process, the data sources go through a stringent quality control and curation process whereby all data layers are aligned to a uniform spatial index and enhanced when necessary. These curated data layers ensure that the insights generated by AlphaGeo are reliable and explainable everywhere in the world.
Database Factsheet:
Spatial coverage
Global
Temporal range (applicable to climate projections and timeseries data)
1975 - 2100
Supported Climate Scenarios
SSP245, SSP370, SSP585
Highest Data Resolution
30m
Number of Engineered Features
154 features
Number of Curated Datapoints
41 billion
Number of data sources
85 unique sources
Update Cycle
Every Quarter
List of Data Sources:
When curating data sources, the target source must meet one or more criteria below to ensure their reliability. These are:
Peer-reviewed - the data is published in academic journals that underwent a peer-review process. E.g. Downscaled CMIP6 ensemble models from HighResMIP.
Well-documented - the data is published with clear explanation of methodologies and/or code repositories for third parties to reproduce the results. E.g. OpenStreetMap.
Well-established - the data is published by reputable organizations and are widely used by the industry. E.g. the IBTrACS Project by NOAA.
The table below presents a partial selection of publicly accessible data sources that are integrated into AlphaGeo's database. Last Updated: 28 September 2024.
Global CMIP6 Climate Projections
(carbon)plan
Daily values from 1975 to 2100
0.25 degrees (25km)
Aqueduct 4.0
World Resources Institute (WRI)
Yearly values in 2014, 2030, 2050, 2080
15 arcseconds (450 meters)
Global Storm Surge Indicator
Copernicus
Yearly values in 2015, 2050
0.25 degrees (25km)
Global Mean Sea Level Change
Intergovernmental Panel on Climate Change (IPCC)
2021-2040, 2041-2060, 2081-2100
1 degree (100km)
International Best Track Archive for Climate Stewardship (IBTrACS)
National Oceanic and Atmospheric Administration (NOAA)
Daily values from 1841 - 2023
0.1 degrees (10km)
Global Consensus Land Cover
EarthEnv
2014
30 arcseconds (900 meters)
FEMA National Flood Hazard Layer
FEMA
2023
10 arcseconds (300 meters)
POIs
OpenStreetMap
For this product, flood, fire, and drought infrastructure data points were queried from OSM.
Population
WorldPop
This product utilized the estimated total number of people per grid-cell (at the equator) by mosaicking 1km resolution global datasets using 100m resolution population count datasets.
Age and Sex Structure
WorldPop
This dataset provides estimates of the total number of people per grid square, broken down by sex and age groupings (including 0-1 years and in 5-year increments up to 80+ years) for the year 2020. The units are the estimated number of males and females in each age group per grid square.
Night Light
Earth Observation Group
This product uses the annual global VIIRS nighttime lights V2.2 cloud-free median radiance grids spanning 2020.
Income Index
Global Data Lab
The data used in this product includes the log of Gross National Income (GNI) per capita in thousands of US Dollars (2011 PPP).
Gross National Income
World Bank
For this product, data on GNI, PPP (current international $) was utilized.
Global Consensus Land Cover
EarthEnv
The datasets integrate multiple global remote sensing-derived land-cover products and provide consensus information on the prevalence of 12 land-cover classes at 1-km resolution.
Local Climate Zones
WUDAPT
The global map of Local Climate Zones, published in the open-access data journal Earth System Science Data, was used in this product.
References
(carbon)plan. “CMIP6 Downscaling,” n.d. https://carbonplan.org/.
Eyring, Veronika, Sandrine Bony, Gerald A. Meehl, Catherine A. Senior, Bjorn Stevens, Ronald J. Stouffer, and Karl E. Taylor. “Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) Experimental Design and Organization.” Geoscientific Model Development 9, no. 5 (May 26, 2016): 1937–58. https://doi.org/10.5194/gmd-9-1937-2016.
Knapp, Kenneth R., Michael C. Kruk, David H. Levinson, Howard J. Diamond, and Charles J. Neumann. “The International Best Track Archive for Climate Stewardship (IBTrACS): Unifying Tropical Cyclone Data.” Bulletin of the American Meteorological Society 91, no. 3 (March 1, 2010): 363–76. https://doi.org/10.1175/2009BAMS2755.1.
Kuzma, Samantha, Marc F. P. Bierkens, Shivani Lakshman, Tianyi Luo, Liz Saccoccia, Edwin H. Sutanudjaja, and Rens Van Beek. “Aqueduct 4.0: Updated Decision-Relevant Global Water Risk Indicators,” August 16, 2023. https://www.wri.org/research/aqueduct-40-updated-decision-relevant-global-water-risk-indicators.
Muis, Sanne, Jeroen C. J. H. Aerts, José A. Á. Antolínez, Job C. Dullaart, Trang Minh Duong, Li Erikson, Rein J. Haarsma, et al. “Global Projections of Storm Surges Using High-Resolution CMIP6 Climate Models.” Earth’s Future 11, no. 9 (2023): e2023EF003479. https://doi.org/10.1029/2023EF003479.
O’Neill, Brian C., Elmar Kriegler, Keywan Riahi, Kristie L. Ebi, Stephane Hallegatte, Timothy R. Carter, Ritu Mathur, and Detlef P. van Vuuren. “A New Scenario Framework for Climate Change Research: The Concept of Shared Socioeconomic Pathways.” Climatic Change 122, no. 3 (February 1, 2014): 387–400. https://doi.org/10.1007/s10584-013-0905-2.
Tuanmu, Mao-Ning, and Walter Jetz. “A Global 1-Km Consensus Land-Cover Product for Biodiversity and Ecosystem Modelling.” Global Ecology and Biogeography 23, no. 9 (2014): 1031–45. https://doi.org/10.1111/geb.12182.
Stewart, I. D., & Oke, T. R. (2012). Local climate zones for urban temperature studies. Bulletin of the American Meteorological Society, 93(12), 1879–1900. https://doi.org/10.1175/bams-d-11-00019.1
Aslam, A., & Rana, I. A. (2022). The use of local climate zones in the urban environment: A systematic review of data sources, methods, and themes. Urban Climate, 42, 101120. https://doi.org/10.1016/j.uclim.2022.101120
Bechtel, B., Demuzere, M., Mills, G., Zhan, W., Sismanidis, P., Small, C., & Voogt, J. (2019). SUHI analysis using Local Climate Zones—A comparison of 50 cities. Urban Climate, 28, 100451. https://doi.org/10.1016/j.uclim.2019.01.005
Verdonck, M., Demuzere, M., Hooyberghs, H., Beck, C., Cyrys, J., Schneider, A., Dewulf, R., & Van Coillie, F. (2018). The potential of local climate zones maps as a heat stress assessment tool, supported by simulated air temperature data. Landscape and Urban Planning, 178, 183–197. https://doi.org/10.1016/j.landurbplan.2018.06.004
Sohn, W., Kim, J., Li, M., Brown, R. D., & Jaber, F. H. (2020). How does increasing impervious surfaces affect urban flooding in response to climate variability? Ecological Indicators, 118, 106774. https://doi.org/10.1016/j.ecolind.2020.106774
Blum, A. G., Ferraro, P. J., Archfield, S. A., & Ryberg, K. R. (2020). Causal effect of impervious cover on annual flood magnitude for the United States. Geophysical Research Letters, 47(5). https://doi.org/10.1029/2019gl086480
Yang, W., Yang, H., Yang, D., & Hou, A. (2021). Causal effects of dams and land cover changes on flood changes in mainland China. Hydrology and Earth System Sciences, 25(5), 2705–2720. https://doi.org/10.5194/hess-25-2705-2021
Dedekorkut-Howes, A., Torabi, E., & Howes, M. (2020). When the tide gets high: a review of adaptive responses to sea level rise and coastal flooding. Journal of Environmental Planning and Management, 63(12), 2102–2143. https://doi.org/10.1080/09640568.2019.1708709
Zhu, X., Linham, M. M., & Nicholls, R. J. (2010). Technologies for Climate Change Adaptation - Coastal Erosion and Flooding. Danmarks Tekniske Universitet, Risø Nationallaboratoriet for Bæredygtig Energi. TNA Guidebook Series
Nazarnia, H., Nazarnia, M., Sarmasti, H., & Wills, W. O. (2020). A Systematic review of civil and environmental infrastructures for coastal adaptation to sea level rise. Civil Engineering Journal, 6(7), 1375–1399. https://doi.org/10.28991/cej-2020-03091555
Tariq, M. a. U. R., Farooq, R., & Van De Giesen, N. (2020). A critical review of flood risk management and the selection of suitable measures. Applied Sciences, 10(23), 8752. https://doi.org/10.3390/app10238752
Cea L, Costabile P. Flood Risk in Urban Areas: Modelling, Management and Adaptation to Climate Change. A Review. Hydrology. 2022; 9(3):50. https://doi.org/10.3390/hydrology9030050
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