AndreaBozzo/ceres-open-data-index huggingface dataset:
Water Point Data Exchange (SSD)

WPdx is a platform to compile crowdsourced data focused on rural water points (wells, springs, tapstands) with contributions from governments, NGOs, and researchers. Shared data is cleaned and harmonized using the [WPdx Data Standard](https://www.waterpointdata.org/share-data)  to create a robust analysis-ready dataset. There are [two primary datasets](https://www.waterpointdata.org/access-data) available from WPdx. The first is WPdx-Basic, which includes all records shared with the platform. The second, WPdx-Plus is a subset of the Basic dataset which focuses on countries where district and/or national data is available and undergoes additional cleaning. WPdx-Plus is used as an input to the [WPdx Decision Support tools](https://www.waterpointdata.org/use-data/) and is the basis for the datasets posted here. The decision support tools provide insights on rural basic water service access and recommendations regarding prioritized water point repair, highlight areas with apparent service gaps, and identify water points which are at high risk of failure. For each country where WPdx data is available, there are two datasets available for download are described below.

- The wpdx_adm_region_analysis file provides an overview of the population served, unserved and uncharted for each available administrative level. The file also includes a data quality analysis based on water point record age.
- The wpdx_water_points file provides water point level details for each point shared with WPdx including all the WPdx data standard parameters plus results from the WPdx Rehab Priority, Service Gap/New Construction and Status Prediction analyses.
- A data dictionary describing each parameter included in each file is available in the Data and Resources section.  
To share data with the WPdx platform, please visit (www.waterpointdata.org/share-data) and/or reach out to [info@waterpointdata.org](mailto:info@waterpointdata.org)




Tags: geodata, hxl, water sanitation and hygiene-wash
Organization: Water Point Data Exchange
Syria - Damage assessment of Deir Ez Zor, Deir Ez Zor Governorate

This map illustrates satellite-detected damage in a portion of the city of Deir Ez Zor, Syrian Arab Republic. Using satellite imagery acquired 25 May 2016, 10 May 2015, 13 May 2014, and 24 October 2013, UNITAR - UNOSAT identified a total of 4,673 affected structures within the city. Approximately 802 of these were destroyed, 1,410 severely damaged, and 2,461 moderately damaged. While much of the city was damaged by 10 May 2015, 1,389 structures were newly damaged and 66 structures experienced an increase in damage between that date and 25 May 2016. This analysis was done as part of the REACH initiative for the U.S. Office of Foreign Disaster Assistance. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.

Tags: complex emergency-conflict-security, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Nepal - Subnational Administrative Boundaries

This dataset contains the following administrative boundaries: ADM0, ADM1, ADM2, ADM3.  
  
Produced and maintained since 2017, the geoBoundaries Global Database of Political Administrative Boundaries Database [www.geoboundaries.org](https://www.geoboundaries.org) is an open license, standardized resource of boundaries (i.e., state, county) for every country in the world.  

Tags: administrative boundaries-divisions, gazetteer, geodata
Organization: geoBoundaries
Geodata of Damage Assessment of Bhaktapur, Kathmandu Valley, Nepal

This map illustrates satellite-detected damage and destruction in the city of Bhaktapur, Kathmandu Valley, Nepal. Located about 20 kilometers east of Kathmandu city, Bhaktapur was significantly impacted by the 25 April 2015 earthquake in Nepal. Using satellite imagery acquired 27 April 2015 UNITAR / UNOSAT identified a total of 458 affected structures. Approximately 115 of these were destroyed, 170 severely damaged, and 173 moderately damaged. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR / UNOSAT.

Tags: earthquake-tsunami, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Iraq - Geodata of Damage Assessment for Fallujah and Al Anbar Provinces

This map illustrates satellite-detected damage and destruction in the city of Fallujah, Al Anbar Province, Iraq. Using satellite imagery acquired 28 and 29 June 2016, UNOSAT identified 491 destroyed structures, 300 severely damaged structures, and 453 moderately damaged structure. This latest analysis, combined with a previous UNOSAT analysis (done using an image from 30 November 2014), indicates a total of 1,422 destroyed structures (an increase of 53% from 2014), 604 severely damaged structures (an increase of 99% from 2014), and 578 moderately damaged structures (an increase of 362% from 2014). The total number of destroyed or damaged structures therefore increased from 1,360 to 3,964, an increase of 191%. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.

Tags: complex emergency-conflict-security, geodata
Organization: United Nations Satellite Centre (UNOSAT)
UNOSAT Live Web map- Cyclone Ditwah and Floods in Sri Lanka (November 2025)

**UNOSAT code: FL20251128LKA, GDACS ID: 1001238**  This application provides geospatial information from ongoing satellite-based assessments of the floods in Sri Lanka triggered by Cyclone DITWAH in November 2025.  
  
Important note: Flood analysis derived from radar imagery may underestimate the presence of standing water in built-up and densely vegetated areas due to the backscattering properties of the radar signal.

Tags: flooding, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Central African Republic: Displacement Data - Baseline Assessment [IOM DTM]

This dataset presents information on internally displaced persons, returnees from the Central African Republic who were previously displaced, and returnees from other countries. It outlines their distribution by place of origin and period of displacement.

Tags: displacement, gender and age disaggregated data-gadd, hxl, internally displaced persons-idp, migration, returnees
Organization: International Organization for Migration (IOM)
Pakistan: IBTrACS Storm Tracks

The International Best Track Archive for Climate Stewardship (IBTrACS) project is the most complete global collection of tropical cyclones available. It merges recent and historical tropical cyclone data from multiple agencies to create a unified, publicly available, best-track dataset that improves inter-agency comparisons.   
   
 Fields available:   
 SID: A unique storm identifier (SID) assigned by IBTrACS algorithm.  
 ISO_TIME: Time of the observation in ISO format (YYYY-MM-DD hh:mm:ss)   
 BASIN: Basin of the current storm position   
 SUBBASIN: Sub-basin of the current storm position   
 NATURE: Type of storm (a combination of the various types from the available sources)   
 NUMBER: Number of the storm for the year (restarts at 1 for each year   
 LAT: Mean position - latitude (a combination of the available positions)   
 LON: Mean position - longitude (a combination of the available positions)   
 WMO_WIND: Maximum sustained wind speed assigned by the responsible WMO agency   
 WMO_PRES: Minimum central pressure assigned by the responsible WMO agency.

Tags: cyclones-hurricanes-typhoons, hxl
Organization: HDX
Congo - Subnational Administrative Boundaries

This dataset contains the following administrative boundaries: ADM0, ADM1, ADM2.  
  
Produced and maintained since 2017, the geoBoundaries Global Database of Political Administrative Boundaries Database [www.geoboundaries.org](https://www.geoboundaries.org) is an open license, standardized resource of boundaries (i.e., state, county) for every country in the world.  

Tags: administrative boundaries-divisions, gazetteer, geodata
Organization: geoBoundaries
Pitcairn: IBTrACS Storm Tracks

The International Best Track Archive for Climate Stewardship (IBTrACS) project is the most complete global collection of tropical cyclones available. It merges recent and historical tropical cyclone data from multiple agencies to create a unified, publicly available, best-track dataset that improves inter-agency comparisons.   
   
 Fields available:   
 SID: A unique storm identifier (SID) assigned by IBTrACS algorithm.  
 ISO_TIME: Time of the observation in ISO format (YYYY-MM-DD hh:mm:ss)   
 BASIN: Basin of the current storm position   
 SUBBASIN: Sub-basin of the current storm position   
 NATURE: Type of storm (a combination of the various types from the available sources)   
 NUMBER: Number of the storm for the year (restarts at 1 for each year   
 LAT: Mean position - latitude (a combination of the available positions)   
 LON: Mean position - longitude (a combination of the available positions)   
 WMO_WIND: Maximum sustained wind speed assigned by the responsible WMO agency   
 WMO_PRES: Minimum central pressure assigned by the responsible WMO agency.

Tags: cyclones-hurricanes-typhoons, hxl
Organization: HDX
Myanmar: IBTrACS Storm Tracks

The International Best Track Archive for Climate Stewardship (IBTrACS) project is the most complete global collection of tropical cyclones available. It merges recent and historical tropical cyclone data from multiple agencies to create a unified, publicly available, best-track dataset that improves inter-agency comparisons.   
   
 Fields available:   
 SID: A unique storm identifier (SID) assigned by IBTrACS algorithm.  
 ISO_TIME: Time of the observation in ISO format (YYYY-MM-DD hh:mm:ss)   
 BASIN: Basin of the current storm position   
 SUBBASIN: Sub-basin of the current storm position   
 NATURE: Type of storm (a combination of the various types from the available sources)   
 NUMBER: Number of the storm for the year (restarts at 1 for each year   
 LAT: Mean position - latitude (a combination of the available positions)   
 LON: Mean position - longitude (a combination of the available positions)   
 WMO_WIND: Maximum sustained wind speed assigned by the responsible WMO agency   
 WMO_PRES: Minimum central pressure assigned by the responsible WMO agency.

Tags: cyclones-hurricanes-typhoons, hxl
Organization: HDX
Nepal: IBTrACS Storm Tracks

The International Best Track Archive for Climate Stewardship (IBTrACS) project is the most complete global collection of tropical cyclones available. It merges recent and historical tropical cyclone data from multiple agencies to create a unified, publicly available, best-track dataset that improves inter-agency comparisons.   
   
 Fields available:   
 SID: A unique storm identifier (SID) assigned by IBTrACS algorithm.  
 ISO_TIME: Time of the observation in ISO format (YYYY-MM-DD hh:mm:ss)   
 BASIN: Basin of the current storm position   
 SUBBASIN: Sub-basin of the current storm position   
 NATURE: Type of storm (a combination of the various types from the available sources)   
 NUMBER: Number of the storm for the year (restarts at 1 for each year   
 LAT: Mean position - latitude (a combination of the available positions)   
 LON: Mean position - longitude (a combination of the available positions)   
 WMO_WIND: Maximum sustained wind speed assigned by the responsible WMO agency   
 WMO_PRES: Minimum central pressure assigned by the responsible WMO agency.

Tags: cyclones-hurricanes-typhoons, hxl
Organization: HDX
Sri Lanka: IBTrACS Storm Tracks

The International Best Track Archive for Climate Stewardship (IBTrACS) project is the most complete global collection of tropical cyclones available. It merges recent and historical tropical cyclone data from multiple agencies to create a unified, publicly available, best-track dataset that improves inter-agency comparisons.   
   
 Fields available:   
 SID: A unique storm identifier (SID) assigned by IBTrACS algorithm.  
 ISO_TIME: Time of the observation in ISO format (YYYY-MM-DD hh:mm:ss)   
 BASIN: Basin of the current storm position   
 SUBBASIN: Sub-basin of the current storm position   
 NATURE: Type of storm (a combination of the various types from the available sources)   
 NUMBER: Number of the storm for the year (restarts at 1 for each year   
 LAT: Mean position - latitude (a combination of the available positions)   
 LON: Mean position - longitude (a combination of the available positions)   
 WMO_WIND: Maximum sustained wind speed assigned by the responsible WMO agency   
 WMO_PRES: Minimum central pressure assigned by the responsible WMO agency.

Tags: cyclones-hurricanes-typhoons, hxl
Organization: HDX
Bangladesh: IBTrACS Storm Tracks

The International Best Track Archive for Climate Stewardship (IBTrACS) project is the most complete global collection of tropical cyclones available. It merges recent and historical tropical cyclone data from multiple agencies to create a unified, publicly available, best-track dataset that improves inter-agency comparisons.   
   
 Fields available:   
 SID: A unique storm identifier (SID) assigned by IBTrACS algorithm.  
 ISO_TIME: Time of the observation in ISO format (YYYY-MM-DD hh:mm:ss)   
 BASIN: Basin of the current storm position   
 SUBBASIN: Sub-basin of the current storm position   
 NATURE: Type of storm (a combination of the various types from the available sources)   
 NUMBER: Number of the storm for the year (restarts at 1 for each year   
 LAT: Mean position - latitude (a combination of the available positions)   
 LON: Mean position - longitude (a combination of the available positions)   
 WMO_WIND: Maximum sustained wind speed assigned by the responsible WMO agency   
 WMO_PRES: Minimum central pressure assigned by the responsible WMO agency.

Tags: cyclones-hurricanes-typhoons, hxl
Organization: HDX
Bhutan: IBTrACS Storm Tracks

The International Best Track Archive for Climate Stewardship (IBTrACS) project is the most complete global collection of tropical cyclones available. It merges recent and historical tropical cyclone data from multiple agencies to create a unified, publicly available, best-track dataset that improves inter-agency comparisons.   
   
 Fields available:   
 SID: A unique storm identifier (SID) assigned by IBTrACS algorithm.  
 ISO_TIME: Time of the observation in ISO format (YYYY-MM-DD hh:mm:ss)   
 BASIN: Basin of the current storm position   
 SUBBASIN: Sub-basin of the current storm position   
 NATURE: Type of storm (a combination of the various types from the available sources)   
 NUMBER: Number of the storm for the year (restarts at 1 for each year   
 LAT: Mean position - latitude (a combination of the available positions)   
 LON: Mean position - longitude (a combination of the available positions)   
 WMO_WIND: Maximum sustained wind speed assigned by the responsible WMO agency   
 WMO_PRES: Minimum central pressure assigned by the responsible WMO agency.

Tags: cyclones-hurricanes-typhoons, hxl
Organization: HDX
Modelled gridded population estimates for the Kinshasa, Kongo-Central, Kwango, Kwilu, and Mai-Ndombe provinces in the Democratic Republic of the Congo 2018, version 2.0

These data were produced by the [WorldPop](https://www.worldpop.org/) Research Group at the University of Southampton. This work is part of the [GRID3 ](https://grid3.org/) (Geo-Referenced Infrastructure and Demographic Data for Development) project funded by the Bill and Melinda Gates Foundation (BMGF) and the United Kingdom Foreign, Commonwealth & Development Office (OPP1182425). Project partners include WorldPop at the University of Southampton, the United Nations Population Fund ([UNFPA](https://www.unfpa.org)), Center for International Earth Science Information Network ([CIESIN](http://www.ciesin.org/)) in the Earth Institute at Columbia University, and the Flowminder Foundation. 
The modelling work was led by Gianluca Boo and Edith Darin with the support from Douglas R. Leasure and Claire A. Dooley. Coordination was provided by Heather R. Chamberlain and oversight by Andrew J. Tatem and Attila N. Lazar. The support of the whole WorldPop Research Group is acknowledged. The UCLA-DRC Health Research and Training Program, the Kinshasa School of Public Health (KSPH), and the Bureau Central du Recensement (BCR) coordinated and conducted the two microcensus rounds. The Oak Ridge National Laboratory contributed to the first round of microcensus. We acknowledge the contribution of the many individuals within these institutions. 

__Recommended citation:__

_Boo G, Darin E, Leasure DR, Dooley CA, Chamberlain HR, Lazar AN, Tatem AJ. 2020. Modelled gridded population estimates for the Kinshasa, Kongo-Central, Kwango, Kwilu, and Mai-Ndombe provinces in the Democratic Republic of the Congo, version 2.0. WorldPop, University of Southampton. doi:10.5258/SOTON/WP00669_

Tags: baseline population, demographics, geodata
Organization: GRID3
LAC Region (tri-National): Acute Food Insecurity Country Data

The IPC Acute Food Insecurity (IPC AFI) classification provides strategically relevant information to decision makers that focuses on short-term objectives to prevent, mitigate or decrease severe food insecurity that threatens lives or livelihoods. This data has been produced by the National IPC Technical Working Groups for IPC population estimates since 2018. All national population figures are based on official country population estimates. IPC estimates are those published in country IPC reports.

Tags: food security, integrated food security phase classification-ipc
Organization: Integrated Food Security Phase Classification (IPC)
South Sudan 2019 gridded population estimates from census projections adjusted for displacement, version 1.0

These data were produced by the [WorldPop](https://www.worldpop.org/) Research Group at the University of Southampton. This work was funded by the Bill and Melinda Gates Foundation (BMGF) and the United Kingdom's Department for International Development (OPP1182408). The primary intended use of these data was aiding the BMGF field teams. The modelling work was led by Claire Dooley with support from Chris Jochem and oversight by WorldPop director Andy Tatem and GRID3 lead Attila Lazar. The support of the whole WorldPop group is acknowledged, as well as the our [GRID3](https://grid3.org/)  partners ([UNFPA](https://www.unfpa.org), [Columbia University](http://www.ciesin.org/) and [Flowminder](https://www.flowminder.org/)). We thank the teams at IOM and ACLED for their excellent work in collecting data and making it freely available. This work was supported with funding from the Bill & Melinda Gates Foundation (BMGF) and the United Kingdom’s Department for International Development (DFID). These data may be distributed using a Creative [Commons Attribution Share-Alike 4.0](https://creativecommons.org/licenses/by-sa/4.0/) License.  

__DATA DESCRIPTION__

This dataset provides population estimates for each settled 100m grid square in South Sudan. The grid square values were derived using the National Bureau of Statistics’ 2019 population projection estimates that were adjusted to account for displacement of people. The locations people have been displaced to were directly obtained from IOM’s Displacement Tracking Matrix (DTM). The locations people have been displaced from were derived using DTM and the Armed Conflict Locations and Events Database (ACLED). Numbers of displaced people per location were calculated using recorded numbers of international refugees and internally displaced persons. 

For further details, please, read  SSD_population_v1_0_README.pdf

__Recommended citation__

_WorldPop (School of Geography and Environmental Science, University of Southampton). 2020. South Sudan 2019 gridded population  estimates from census projections adjusted for displacement, version 1.0. https://dx.doi.org/10.5258/SOTON/WP00659_

Tags: demographics, geodata
Organization: GRID3
Census-based gridded population estimates for Burkina Faso (2019), version 1.0

These data were produced by the [WorldPop](https://www.worldpop.org/) Research Group at the University of Southampton. This work is part of the [GRID3 ](https://grid3.org/) (Geo-Referenced Infrastructure and Demographic Data for Development) project funded by the Bill and Melinda Gates Foundation (BMGF) and the United Kingdom Foreign, Commonwealth & Development Office (OPP1182425). Project partners include WorldPop at the University of Southampton, the United Nations Population Fund ([UNFPA](https://www.unfpa.org)), Center for International Earth Science Information Network ([CIESIN](http://www.ciesin.org/)) in the Earth Institute at Columbia University, and the Flowminder Foundation. The Burkina Faso Institut National de la Statistique et de la Démographie supported, facilitated this work, reviewed the results and provided the census database. The modelling work, geospatial data processing, and stakeholder engagement was led by Edith Darin.  Support for the statistical modelling was provided by Gianluca Boo, Claire A. Dooley, Douglas R. Leasure and Chris W. Jochem. Support for the engagement work and review of the methods was offered by Mathias Kuépié. Oversight was done by Andrew J. Tatem and Attila N. Lazar.  

__Recommended citation:__

_WorldPop and Institut National de la Statistique et de la Démographie du Burkina Faso. 2021. Census based gridded population estimates for Burkina Faso (2019), version 1.0. WorldPop, University of Southampton. doi:10.5258/SOTON/WP00687_



Tags: baseline population, demographics, geodata
Organization: GRID3
Latin America and the Caribbean - Regional Refugee and Migrant Response Plan 2026

Full dataset of the RMRP 2026 , including activities, partners, population projections, people in need, and target estimates disaggregated by age and gender and population type. More info on the R4V website: https://www.r4v.info/en/data

Tags: affected population, demographics, funding, humanitarian response plan-hrp, migration, operational partners, people in need-pin, refugees
Organization: Inter-Agency Coordination Platform for Refugees and Migrants from Venezuela
El Salvador : Operational Presence

The Who does What Where (3W) is a core humanitarian coordination dataset. It is critical to know where humanitarian organizations are working, what they are doing and their capability in order to identify gaps, avoid duplication of efforts, and plan for future humanitarian response (if needed). The data includes a list of humanitarian organizations by district and cluster, as well as a unique count of organizations. 

Tags: hxl, who is doing what and where-3w-4w-5w
Organization: OCHA Latin America and the Caribbean (ROLAC)
Satellite detected water extents between 23 and 27 February 2022 over South Sudan

**UNOSAT code: FL20220119SSD**  This map illustrates cumulative satellite-detected water using VIIRS in South Sudan between 23 to 27 Feb. 2022 compared with the period from 11 to 15 Feb. 2022. Within the cloud free analyzed areas of about 629,000 km2, a total of about 21,200 km2 of lands appear to be affected with flood waters. Water extent appears to have decreased about 8,000 km2 since the period between 11 to 15 Feb. 2022. Based on Worldpop population data and the maximal flood water coverage, ~522,000 people are potentially exposed or living close to flooded areas.
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).

Tags: flooding, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Satellite  detected water extent over Guli District, White Nile State of Sudan as of 4 September 2021

**UNOSAT code: FL20210907SDN**  This map illustrates satellite detected waters and the related potentially affected croplands as deduced using a Sentinel-2 satellite image acquired on 4 September 2021 over the Guli District, White Nile State of Sudan. In this area, about 80 km2 of croplands appear to be likely affected by the flood waters.
This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to United Nations Satellite Centre (UNOSAT)

Tags: flooding, geodata
Organization: United Nations Satellite Centre (UNOSAT)