AndreaBozzo/ceres-open-data-index huggingface dataset:
Angola: 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
Satellite detected water extents between 25 and 29 April 2025 over South Sudan

**UNOSAT code: FL20250110SSD**  This map illustrates cumulative satellite-detected water using VIIRS in South Sudan between 25 to 29 April 2025 compared with the period from 15 to 19 March 2025 . Within the cloud free analysed areas of about 620,000 km², a total of about 11,000 km² of lands appear to be affected with flood waters. Water extent appears to have decreased of about 10,600 km² since the period between 15 to 19 March 2025 within the cloud free analysed areas. Based on Worldpop population data and the maximal flood water extent ~180,000 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 extents between 13 and 17 August 2025 over South Sudan

**UNOSAT code: FL20250110SSD**  This map illustrates cumulative satellite-detected water using VIIRS in South Sudan between 13 to 17 August 2025, compared with the period from 25 to 29 April 2025. Within the cloud-free analysed areas of about 620,000 km², a total of about 26,000 km² of land appears to be affected by flood waters. Water extent appears to have increased of about 15,000 km² since the period between 25 to 29 April 2025 within the cloud-free analysed areas. Based on Worldpop population data and the maximal flood water extent ~416,000 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 extents in Swat District, Khyber Pakhtunkhwa Province, Pakistan as of 20 August 2025

**UNOSAT code: FL20250818PAK**  This map illustrates the satellite detected water extent in Swat District, Khyber Pakhtunkhwa Province, Pakistan as observed from a Sentinel-2 satellite image acquired on 20 August 2025 at 13:35 local time (08:35 UTC). Within the analyzed area of approximately 340 km², about 4 km² of land appears to be affected by floodwaters. Based on WorldPop population data and the flood extent, approximately 134,500 people are potentially exposed or living close to the flooded areas. additional. In addition, UNOSAT identified approximately 3,860 exposed buildings and about 30 km of affected roads.  
  
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)
Sumy Rapid Damage Assessment Overview Map

**UNOSAT code: CE20220223UKR**  This map illustrates a satellite imagery based Rapid Damage Building Assessment (RDBA) in Sumy City, Ukraine. The RDBA divides the city into 500m x 500m cells, each of which is analyzed to determine whether or not there are damaged buildings inside the cell.

Based on imagery collected on 20 and 22 March 2022, analysts found that 5 cells out of 1,111 cells sustained visible damage. This represents approximately 0.4% of the cells over the city.

This analysis is based on structures visibly damaged as of 20 and 22 March 2022 as seen in marginally degraded satellite imagery. 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: complex emergency-conflict-security, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Northern Mariana Islands - Coastal Proximity of Populations

Spatial datasets utilized to conduct the spatial analysis and additional information from the research article: Coastal proximity of populations in 22 Pacific Island Countries and Territories. 
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0223249
https://sdd.spc.int/mapping-coastal


_Access this dataset from the [Pacific Data Hub](https://pacificdata.org/data/dataset/coastal-population-dataset-mnp)_

Tags: demographics, population
Organization: Pacific Community
Coastal proximity of populations in 22 Pacific Island Countries and Territories - Dataset - Fiji

Spatial datasets utilized to conduct the spatial analysis and additional information from the research article: Coastal proximity of populations in 22 Pacific Island Countries and Territories. 
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0223249
https://sdd.spc.int/mapping-coastal


_Access this dataset from the [Pacific Data Hub](https://pacificdata.org/data/dataset/coastal-population-dataset-fji)_

Tags: demographics, population
Organization: Pacific Community
Coastal proximity of populations in 22 Pacific Island Countries and Territories - Dataset - Guam

Spatial datasets utilized to conduct the spatial analysis and additional information from the research article: Coastal proximity of populations in 22 Pacific Island Countries and Territories. 
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0223249
https://sdd.spc.int/mapping-coastal


_Access this dataset from the [Pacific Data Hub](https://pacificdata.org/data/dataset/coastal-population-dataset-gum)_

Tags: demographics, population
Organization: Pacific Community
Marshall Islands - Subnational Administrative Boundaries

This dataset contains the following administrative boundaries: ADM0, ADM1.  
  
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 Standing Waters Over Jowhar Middle Shabelle Region, Somalia

This map illustrates satellite-detected waters in the Jowhar, Middle Shabelle region of Somalia. Using satellite imagery acquired 16 November 2015 and 02 January 2015, UNITAR-UNOSAT identified a total affected area of roughly 8,300 hectares in the Shabelle Dhexe and Hoose provinces. As of 16 November 2015, approximately 8,300 hectares of probable standing rain waters were detected over the districts of Jowhar, Balcad and, Afgooye. Due to the characteristics of satellite data used for this analysis, the exact limit of flood water is uncertain. Detected water bodies likely reflect an underestimation of all flood-affected areas within the map extent. This analysis has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT. Pre-flood assessment performed by SWALIM.

Tags: el nino-el nina, flooding, geodata
Organization: United Nations Satellite Centre (UNOSAT)
India - Subnational Administrative Boundaries

This dataset contains the following administrative boundaries: ADM1, ADM1, ADM2, ADM3, ADM4, ADM5.  
  
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
Satellite detected water extent over Sylhet and Sunamganj Districts,  Sylhet Division, Bangladesh as of 25 May 2022.

**UNOSAT code: FL20220525BGD**  This map illustrates satellite-detected surface waters in Sylhet and Sunamganj Districts, Sylhet Division, Bangladesh as observed from a Chaohu-1 image acquired on 25 May 2022 at 22:23 local time. Within the analyzed area of about 730 km2, about 420 km2 of lands appear to be flooded. In this area, about 300 km2 of croplands and 70 km2 of herbaceous wetland appear to be likely affected by the flood waters. Based on Worldpop population data and the detected surface waters, about 307,000 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 United Nations Satellite Centre (UNOSAT).

Important note: Flood analysis from radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.

Tags: flooding, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Djibouti - 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
Malaysia - 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
Data for the Covid-19 Data Explorer

This dataset contains data obtained from a variety of sources and transformed into a form suitable for driving the [Covid-19 Data Explorer](https://data.humdata.org/visualization/covid19-humanitarian-operations/). The visual itself is driven by a JSON file which contains the same data as the resources in this dataset which point to published csvs from [a Google spreadsheet](https://docs.google.com/spreadsheets/d/1bbOp3N-pdW65HoxIYj1tVY4zLfTD4mbpaOZ5ZfrZE54/edit#gid=0).

Tags: covid-19, hxl, indicators
Organization: HDX
Kingdom of Eswatini - 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
Niger - 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
Satellite detected water extents in Maganja Da Costa, Namacurra & Nicoadala Districts, Mozambique as of 22 March 2022

**UNOSAT code: TC20220311MOZ**  This map illustrates satellite-detected surface waters in Maganja Da Costa, Namacurra & Nicoadala Districts, Zambezia Province, Mozambique as observed from a TerraSAR-X image acquired on 22 March 2022 at 05:01 local time. Within the analyzed area of about 6,174 km2, about 496 km2 of lands appear to be flooded.  Based on Worldpop population data and the detected surface waters, about 49,100 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 United Nations Satellite Centre (UNOSAT).
Important note: Flood analysis from radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.

Tags: cyclones-hurricanes-typhoons, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Ukraine: JIAF Humanitarian Needs and Response Plan

The dataset provides a full breakdown of the affected population, PiN, severity and planned reach by strategic priority, cluster, and population group. As applicable, estimates of age and gender disaggregation are also included, along with estimates of people with disability. A detailed list of the HNRP activities is also included, along with a reference table for the units of analysis coded to ADM3 boundaries. Please refer to the dataset’s ReadMe tab for more details.

Check the [Power BI](https://app.powerbi.com/view?r=eyJrIjoiZTFhMGViMDQtZTY4Yi00OWY1LWExYmUtMjM3NmY5MWEzZDdiIiwidCI6IjBmOWUzNWRiLTU0NGYtNGY2MC1iZGNjLTVlYTQxNmU2ZGM3MCIsImMiOjh9 "Power BI") and [ArcGIS](https://gis.unocha.org/portal/apps/experiencebuilder/experience?id=0d7a18725e5e41a686d891f47ba66b81 "ArcGIS") dashboards for the interactive overview of the 2026 HNRP.

Tags: affected population, humanitarian needs overview-hno, humanitarian response plan-hrp, hxl, people in need-pin
Organization: OCHA Ukraine
Nigeria: JIAF Humanitarian Needs People in Need and Severity

This dataset contains the overall people in need and intersectoral severity by disaggregation level which Includes administrative divisions and population groups, depending on each country's decision. The dataset is produced by the United Nations for the Coordination of Humanitarian Affairs (OCHA) in collaboration with humanitarian partners using the Joint Intersectoral Analysis Framework(JIAF).

Tags: affected area, affected population, humanitarian needs overview-hno, humanitarian response plan-hrp, hxl, people in need-pin, severity
Organization: OCHA Nigeria
Afghanistan: JIAF Humanitarian Needs People in Need and Severity

This dataset contains the overall people in need and intersectoral severity by disaggregation level which Includes administrative divisions and population groups, depending on each country's decision. The dataset is produced by the United Nations for the Coordination of Humanitarian Affairs (OCHA) in collaboration with humanitarian partners using the Joint Intersectoral Analysis Framework(JIAF).

Tags: affected area, affected population, humanitarian needs overview-hno, humanitarian response plan-hrp, hxl, people in need-pin, severity
Organization: OCHA Afghanistan
South Sudan - Damage density map in  Morobo-Kaya road, Nahr Yei district

This map illustrates satellite-detected damage density along the road connecting the cities of Morobo and Koya, Nahr Yei district, Central Equatoria, South Sudan. Using satellite imagery acquired 05 March 2017, UNITAR - UNOSAT identified a total of around 7,800 destroyed structures within the analysis extent of the current map (approximately 600 square kilometers). The whole analysis over the Nahr Yei district covers an area of approximately 3,640 square kilometers, and the results show over 18,300 destroyed structures. 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)
Bottom-up gridded population estimates for Nigeria, version 2.1

This data release provides gridded population estimates (spatial resolution of 3 arc-seconds, approximately 100 m grid cells) with national coverage for Nigeria, along with estimates of the number of people belonging to various age-gender groups. Version 2.1 is an update to the previous
version 2.0 gridded population estimates and is based on a correction of the settlement map. These model-based population estimates most likely represent the time period around 2019,  corresponding to the period when the satellite imagery was processed to generate building 
footprints. Populations are mapped only into areas where residential settlements are predicted. These data were produced by the WorldPop Research Group at the University of Southampton.  This work was part of the GRID3 Bridge Funding project with funding from the Bill and Melinda  Gates Foundation (INV-045694). Project partners included the GRID3 Inc and the Center for International Earth Science Information Network in the Earth Institute at Columbia University. Statistical modelling was originally led by Chris Jochem and Doug Leasure with additional 
support and oversight from Attila Lazar and Andy Tatem. Ortis Yankey led the population map update with additional support from Edith Darin. 

The authors followed rigorous procedures designed to ensure that the used data, the applied method  and thus the results are appropriate and of reasonable quality. If users encounter apparent errors or  misstatements, they should contact WorldPop at release@worldpop.org.

*SUGGESTED CITATIONS*

WorldPop. 2023. Bottom-up gridded population estimates for Nigeria, version 2.1. WorldPop, University of Southampton.   DOI: 10.5258/SOTON/WP00765

Tags: baseline population, demographics, geodata, population
Organization: WorldPop
Geodata of Overview of Flood Waters in Hai Phong Province, Vietnam

This map provides an overview of satellite detected waters in Hai Phong Province, northern Vietnam. Due to continuous rainfall, a notable increase in inundated areas occurred within this area. Using satellite imagery acquired 02 August 2015 and 05 October 2009, UNITAR - UNOSAT identified numerous regions with flood affected land in the analyzed extent. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.

Tags: flooding, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Landslide impact analysis eThekwini, Metropolitan Municipality, KwaZulu-Natal Province, South Africa as of 21 April 2022

**UNOSAT code: FL20220418ZAF**  This map illustrates satellite-detected landslides/mudflow-related impact in eThekwini, Metropolitan Municipality, eThekwini District, KwaZulu-Natal Province, South Africa as observed from a Kompsat-3 image acquired on 21 April 2022. Within the analyzed area, 21 ha of landslide scars were observed. Based on Worldpop population data, about 55,000 people live inside the analyzed area. Within the analysis extent, UNITAR-UNOSAT identified 121 damaged structures and 247 potentially damaged structures. 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)
Humanitarian Response Plan projects for Philippines

Projects proposed, in progress, or completed as part of the annual Philippines Humanitarian Response Plans (HRPs) or other Humanitarian Programme Cycle plans. The original data is available on https://hpc.tools

**Important:** some projects in Philippines might be missing, and others might not apply specifically to Philippines. See _Caveats_ under the _Metadata_ tab.

Tags: humanitarian response plan-hrp, hxl, who is doing what and where-3w-4w-5w
Organization: OCHA Financial Tracking System (FTS)
Mali: JIAF Humanitarian Needs People in Need and Severity

This dataset contains the overall people in need and intersectoral severity by disaggregation level which Includes administrative divisions and population groups, depending on each country's decision. The dataset is produced by the United Nations for the Coordination of Humanitarian Affairs (OCHA) in collaboration with humanitarian partners using the Joint Intersectoral Analysis Framework(JIAF).

Tags: affected area, affected population, humanitarian needs overview-hno, humanitarian response plan-hrp, hxl, people in need-pin, severity
Organization: OCHA Mali
Colombia: JIAF Humanitarian Needs People in Need and Severity

This dataset contains the overall people in need and intersectoral severity by disaggregation level which Includes administrative divisions and population groups, depending on each country's decision. The dataset is produced by the United Nations for the Coordination of Humanitarian Affairs (OCHA) in collaboration with humanitarian partners using the Joint Intersectoral Analysis Framework(JIAF).

Tags: affected area, affected population, humanitarian needs overview-hno, humanitarian response plan-hrp, hxl, people in need-pin, severity
Organization: OCHA Colombia
Chad: JIAF Humanitarian Needs People in Need and Severity

This dataset contains the overall people in need and intersectoral severity by disaggregation level which Includes administrative divisions and population groups, depending on each country's decision. The dataset is produced by the United Nations for the Coordination of Humanitarian Affairs (OCHA) in collaboration with humanitarian partners using the Joint Intersectoral Analysis Framework(JIAF).

Tags: affected area, affected population, humanitarian needs overview-hno, humanitarian response plan-hrp, hxl, people in need-pin, severity
Organization: OCHA Chad
GLIDE numbers used by UNOCHA

Subset of the full list of crisis identifiers available at [GLIDEnumber.net](http://glidenumber.net). OCHA provides these GLIDE numbers for interoperability purposes only, so that partners will know what identifiers we are using internally. Please refer to GLIDEnumber.net for the complete and most up-to-date list.


Tags: hxl
Organization: ReliefWeb
IATI COVID-19-related funding data

Aid funding related to the global COVID-19 pandemic, as published via the International Aid Transparency Initiative. This data is a result of a collaboration between the Centre for Humanitarian Data and USAID, and is the basis for the [IATI COVID-19 Funding Dashboard](https://data.humdata.org/viz-iati-c19-dashboard/) and related data story.

For more information about data licensing, see https://data.humdata.org/viz-iati-c19-dashboard/about#licensing

Tags: covid-19, funding, hxl, international aid transparency initiative-iati
Organization: HDX
Satellite detected water extents in Sindh, Balochistan and Punjab Provinces, Pakistan as of 11 July 2025

**UNOSAT code: FL20250630PAK**  This map illustrates the satellite-detected water extent in Sindh, Balochistan, and Punjab Provinces, Pakistan, as observed from Sentinel-2 satellite images acquired on 11 July 2025 at 10:56 local time (05:56 UTC). Within the analyzed area of approximately 83,000 km², about 4,900 km² of land appears to be affected by floodwaters. The floodwater extent appears to have increased by approximately 2,800 km² since 1 July 2025. Based on WorldPop population data and the flood extent, approximately 1.6 million people are potentially exposed or living close to the 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)