GDACS alerts are issued for earthquakes and possible subsequent tsunamis, tropical cyclones, floods and volcanoes. Earthquake, tsunami and tropical cyclones calculations and assessments are done automatically, without human intervention. Floods and volcanic eruptions are currently manually introduced. Research and development is continuous to improve the global monitoring.
HungerMapLIVE is the World Food Programme (WFP)’s global hunger monitoring system. It combines key metrics from various data sources – such as food security information, weather, population size, conflict, hazards, nutrition information and macro-economic data – to help assess, monitor and predict the magnitude and severity of hunger in near real-time. The resulting analysis is displayed on an interactive map that helps WFP staff, key decision makers and the broader humanitarian community to make more informed and timely decisions relating to food security.
The platform covers 94 countries, including countries where WFP has operations as well as most lower and lower-middle income countries (as classified by the World Bank).
This dataset contains data obtained from the
HDX Humanitarian API (HDX HAPI),
which provides standardized humanitarian indicators designed
for seamless interoperability from multiple sources.
The data facilitates automated workflows and visualizations
to support humanitarian decision making.
For more information, please see the HDX HAPI
landing page
and
documentation.
Warnings typically indicate corrections have been made to
the data or show things to look out for. Rows with only warnings
are considered complete, and are made available via the API.
Errors usually mean that the data is incomplete or unusable.
Rows with any errors are not present in the API but are included
here for transparency.
This dataset comes from the International Organization for Migration (IOM)'s displacement tracking matrix (DTM) publicly accessible API. This API allows the humanitarian community, academia, media, government, and non-governmental organizations to utilize the data collected by DTM. The DTM API only provides non-sensitive IDP figures, aggregated at the country, Admin 1 (states, provinces, or equivalent), and Admin 2 (smaller subnational administrative areas) levels. For more detailed information, please see the country-specific DTM datasets on HDX.
This dataset contains data obtained from the
HDX Humanitarian API (HDX HAPI),
which provides standardized humanitarian indicators designed
for seamless interoperability from multiple sources.
The data facilitates automated workflows and visualizations
to support humanitarian decision making.
For more information, please see the HDX HAPI
landing page
and
documentation.
Warnings typically indicate corrections have been made to
the data or show things to look out for. Rows with only warnings
are considered complete, and are made available via the API.
Errors usually mean that the data is incomplete or unusable.
Rows with any errors are not present in the API but are included
here for transparency.
Latest COD population statistics compiled at the admin level. The CSV files contain subnational p-codes, their corresponding administrative names, source organization, and reference dates where available. These are constructed from individual country level population files, which can be found using this search on HDX.
This dataset contains data obtained from the
HDX Humanitarian API (HDX HAPI),
which provides standardized humanitarian indicators designed
for seamless interoperability from multiple sources.
The data facilitates automated workflows and visualizations
to support humanitarian decision making.
For more information, please see the HDX HAPI
landing page
and
documentation.
Conflict and disaster population movement (flows) data for Zimbabwe. The data is the most recent available and covers a 180 day time period.
Internally displaced persons are defined according to the 1998 Guiding Principles as people or groups of people who have been forced or obliged to flee or to leave their homes or places of habitual residence, in particular as a result of armed conflict, or to avoid the effects of armed conflict, situations of generalized violence, violations of human rights, or natural or human-made disasters and who have not crossed an international border.
The IDMC's Event data, sourced from the Internal Displacement Updates (IDU), offers initial assessments of internal displacements reported within the last 180 days. This dataset provides provisional information that is continually updated on a daily basis, reflecting the availability of data on new displacements arising from conflicts and disasters. The finalized, carefully curated, and validated estimates are then made accessible through the Global Internal Displacement Database (GIDD). The IDU dataset comprises preliminary estimates aggregated from various publishers or sources.
Projects proposed, in progress, or completed as part of the annual Pakistan Humanitarian Response Plans (HRPs) or other Humanitarian Programme Cycle plans. The original data is available on https://hpc.tools
Important: some projects in Pakistan might be missing, and others might not apply specifically to Pakistan. See Caveats under the Metadata tab.
Projects proposed, in progress, or completed as part of the annual Colombia Humanitarian Response Plans (HRPs) or other Humanitarian Programme Cycle plans. The original data is available on https://hpc.tools
Important: some projects in Colombia might be missing, and others might not apply specifically to Colombia. See Caveats under the Metadata tab.
Projects proposed, in progress, or completed as part of the annual Niger Humanitarian Response Plans (HRPs) or other Humanitarian Programme Cycle plans. The original data is available on https://hpc.tools
Important: some projects in Niger might be missing, and others might not apply specifically to Niger. See Caveats under the Metadata tab.
Projects proposed, in progress, or completed as part of the annual Jordan Humanitarian Response Plans (HRPs) or other Humanitarian Programme Cycle plans. The original data is available on https://hpc.tools
Important: some projects in Jordan might be missing, and others might not apply specifically to Jordan. See Caveats under the Metadata tab.
The Food and Agriculture Organization of the United Nations (FAO) has developed a monitoring system in 26 food crisis countries to better understand the impacts of various shocks on agricultural livelihoods, food security and local value chains.
The Monitoring System consists of primary data collected from households on a periodic basis (more or less every four months, depending on seasonality). Data are collected through Computer-Assisted Telephone Interviews (CATI) and in-person surveys where the circumstances allow for field access.
As the system is developed, the information collected and analyzed is being used to guide strategic decisions, to design programmes and to inform analytical processes such as the Integrated Phase Classification (IPC) and the Humanitarian Needs Overview (HNO).
At the core of the system is a standardized household questionnaire administered to around 150,000 households per year across the 26 countries. Standardization permits comparisons across time and space, considerably enhancing the utility of the data for decision makers. At minimum the household data are representative at Admin 1 level (e.g. province, or region) and in frequent cases at Admin 2 level (e.g. district).
Core funding for this initiative comes from the United States Agency for International Development (USAID). The initiative also benefits from support from the European Union and FAO’s Special Fund for Emergency and Rehabilitation (SFERA).
In each aggregated field, the values indicate the frequencies of the different responses, expressed as a weighted percentage of the total sample.
The present datasets represents aggregated data referring to household interviews performed after December 2022. At every new survey data release, after cleaning and validation phases, aggregated data is appended to the present dataset.
For real-time updates, for accessing archived data and for additional survey-specific information, please visit the DIEM Hub: https://data-in-emergencies.fao.org/
View the column descriptions here.
Metadata available here.
Questionnaires used for data collection available here.
Reference administrative boundaries (levels 0, 1 and 2) available here in GIS format.
The WFP Global Market Monitor monitors food prices in markets across a range of countries globally. The resources are updated every other week, with country data updating based on when data is received from country offices.
ASAP is an online decision support system for early warning about hotspots of agricultural production anomaly (crop and rangeland), developed by the JRC for food security crises prevention and response planning.
The monthly hotspots data set is available below, but you can explore the hotspots on the ASAP Warning Explorer and access more contextual data on the downloads page. To learn more about the hotspots, refer to the warning classification methodology document.
This dataset contains data obtained from the
HDX Humanitarian API (HDX HAPI),
which provides standardized humanitarian indicators designed
for seamless interoperability from multiple sources.
The data facilitates automated workflows and visualizations
to support humanitarian decision making.
For more information, please see the HDX HAPI
landing page
and
documentation.
Warnings typically indicate corrections have been made to
the data or show things to look out for. Rows with only warnings
are considered complete, and are made available via the API.
Errors usually mean that the data is incomplete or unusable.
Rows with any errors are not present in the API but are included
here for transparency.
This dataset contains standardised Humanitarian Needs Overview data taken from the OCHA HPC Tools system which is under active development. For more detailed but less standardized data on humanitarian needs, see the Humanitarian Needs Overview data series.
This dataset contains data obtained from the
HDX Humanitarian API (HDX HAPI),
which provides standardized humanitarian indicators designed
for seamless interoperability from multiple sources.
The data facilitates automated workflows and visualizations
to support humanitarian decision making.
For more information, please see the HDX HAPI
landing page
and
documentation.
Warnings typically indicate corrections have been made to
the data or show things to look out for. Rows with only warnings
are considered complete, and are made available via the API.
Errors usually mean that the data is incomplete or unusable.
Rows with any errors are not present in the API but are included
here for transparency.
Ecuador administrative level 0-3 boundaries (COD-AB) dataset.
These administrative boundaries were established in: 2017
NOTE: ADM4 feature names are not yet availalble. (Currently ADM4_PCODE is copied into ADM4_ES as a proxy.) No lines layer is yet availalbe. The live geoservices do not reflect the new ADM4 level.
This COD-AB was most recently reviewed for accuracy and necessary changes in December 2024. The COD-AB does not require any update.
Sourced from INEC - Instituto Nacional de Estadística y Censos
Live geoservices (provided by Information Technology Outreach Services (ITOS) with funding from USAID) are available for this COD-AB. Please see COD_External. (For any earlier versions please see here, here, and here.) Vetting, configuration, and geoservices provision by Information Technology Outreach Services (ITOS) with funding from USAID.
This COD-AB is suitable for database or GIS linkage to the Ecuador COD-PS.
No edge-matched (COD-EM) version of this COD-AB has yet been prepared.
Please see the COD Portal.
Administrative level 1 contains 26 feature(s). The normal administrative level 1 feature type is ""currently not known"".
Administrative level 2 contains 223 feature(s). The normal administrative level 2 feature type is ""currently not known"".
Administrative level 3 contains 1,044 feature(s). The normal administrative level 3 feature type is ""currently not known"".
Recommended cartographic projection: South America Albers Equal Area Conic
This metadata was last updated on January 9, 2025.
UNOSAT code: TC20250308MOZ, GDACS ID: 1001154 This map shows the locations where damage was detected based on a very high resolution satellite image collected 18 March 2025 when compared to very high resolution imagery by Airbus from October 2023 and February 2024 (south only), available through Google Earth Pro. Between October 2023 and March 2025, multiple cyclones have passed over Île de Mozambique.
Across the Île de Mozambique, 78 damaged buildings were detected and accumulations of sand indicative of prior flooding were observed on roads and in public spaces.
This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to the United Nations Satellite Centre (UNOSAT).
Overview
This dataset provides a technically validated, multi-sectoral and system-wide Nexus Risk Index for Afghanistan.
It contains 100 curated indicators (IND001–IND100), tailored to fragile and conflict-affected settings, covering climate, health, energy, infrastructure, food, water, security, governance, and environmental systems.
Methodological Foundations
IPBES Nexus Assessment (2024): Used as the core methodological framework
Data Sources: IPCC, INFORM Risk Index, WMO Global Indicators, GRACE, WGMS, ERA5, GPCC, OSI SAF, and more
Processing: Standardized, rebaselined, and interpolated using climate-model aligned adjustments, temporal smoothing, and system simulations
Validation: Expert-reviewed under the GCRI Nexus Ecosystem as part of the Nexus Reports quarterly cycle
Structure
Each indicator includes:
- Disaster Risk Intelligence (DRI): Specialized interpretation of system risk, derived from climate models, hazard projections, or sector disruption patterns
- Disaster Risk Financing (DRF): Tailored financial exposure, shock-buffering capacity, and anticipatory resource needs
- Disaster Risk Reduction (DRR): Mitigation and adaptation strategy options, aligned with Afghanistan's capacities and SDGs
License and Restrictions
⚠️ This dataset is not intended for sensitive or life-critical operations.
It is configured specifically for Nexus-based scenario modeling and anticipatory governance applications.
Adaptability to external tools and platforms requires expert interpretation.
Technical Documentation
File formats: .csv, .txt, .md
Metadata compliant with HDX and GitHub standards
For full documentation, visit: https://therisk.global
Contact
For support or inquiries:
📧 contact@therisk.global
🌐 https://therisk.global
MIMU Pcode is similar to a zip code or postal code, and is a part of a data management system providing unique reference codes to around 67,000 locations across Myanmar. The MIMU maintains the P-codes for Myanmar based on information collected from a variety of sources, including the Government gazette and humanitarian and development organizations. Without a system for organizing such data it is almost impossible for data from more than one source to be combined.
FloodScan uses satellite data to map and monitor floods daily, helping compare current flood conditions with historical averages. This dataset contains two resources:
The first (hdx_floodscan_zonal_stats.xlsx) is a daily tabular dataset providing average FloodScan Standard Flood Extent Depiction (SFED) flood fraction (0-100%) per admin 1 and 2 level. Historical baseline values (SFED_BASELINE) are calculated per day-of-year from the last 10 years of historical data (non-inclusive of current year) after applying an 11 day smoothing mean window. Return Period (RP) is calculated empirically based on all historical data up to the current year (non-inclusive).
The second resource (aer_floodscan_300s_SFED_90d.zip) is a zipped file containing AER FloodScan estimated daily flood fraction (0-100%) gridded data at approximately 10 km resolution (300 arcseconds equivalent to approximately 0.083 degrees) for the last 90 days. Each file represents the estimates for a single day and includes 2 bands: SFED and SFED_BASELINE. The baseline band provides users an easy way to compare current values with historical averages. The baseline is calculated per day-of-year from the last 10 years of historical data (non-inclusive of current year) after applying an 11 day temporal smoothing mean window.
This dataset contains data obtained from the
HDX Humanitarian API (HDX HAPI),
which provides standardized humanitarian indicators designed
for seamless interoperability from multiple sources.
The data facilitates automated workflows and visualizations
to support humanitarian decision making.
For more information, please see the HDX HAPI
landing page
and
documentation.
Warnings typically indicate corrections have been made to
the data or show things to look out for. Rows with only warnings
are considered complete, and are made available via the API.
Errors usually mean that the data is incomplete or unusable.
Rows with any errors are not present in the API but are included
here for transparency.
Note that this dataset only contains data from the last 30 days. For the full timeseries, please visit the datasets listed in the second resource.
