AndreaBozzo/ceres-open-data-index huggingface dataset:
Geodata of Damage Assessment of Idlib, Idlib Governorate, Syria

This map illustrates satellite-detected damage and destruction in the city of Idlib, Idlib Governorate, Syria. Using satellite imagery acquired 02 May 2014, 15 September 2013, and 22 March 2010, UNITAR / UNOSAT identified a total of 307 affected structures. Approximately 102 of these were destroyed, 101 severely damaged, and 104 moderately damaged. While much of the city was damaged by 15 September 2013, 115 structures were newly damaged and one structure experienced an increase in damage between that date and 02 May 2014. Due to cloud obstruction in 02 May 2014 imagery, the total number of affected structures may be underestimated. This analysis was done 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)
Floodwater depth in Camarines Sur Provinces, Bicol Region (Region V) of Philippines as of 1 November 2020

**UNOSAT code: TC20201101PHL**  This map illustrates floodwater depth in Camarines Sur provinces of Philippines based on surface waters observed from a Sentinel-1 image acquired on 1st of November 2020 and a digital elevation model data with the floodwater depth estimation tool(FwDET).
This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-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)
Kosovo: WOF Administrative Subdivisions and Human Settlements

This dataset contains administrative polygons grouped by country (admin-0) with the following subdivisions according to Who's On First placetypes:  
- macroregion (admin-1 including region)  
- region (admin-2 including state, province, department, governorate)  
- macrocounty (admin-3 including arrondissement)  
- county (admin-4 including prefecture, sub-prefecture, regency, canton, commune)  
- localadmin (admin-5 including municipality, local government area, unitary authority, commune, suburb)  
  
The dataset also contains human settlement points and polygons for:  
- localities (city, town, and village)  
- neighbourhoods (borough, macrohood, neighbourhood, microhood)  
  
The dataset covers activities carried out by Who's On First (WOF) since 2015. Global administrative boundaries and human settlements are aggregated and standardized from hundreds of sources and available with an open CC-BY license. Who's On First data is updated on an as-need basis for individual places with annual sprints focused on improving specific countries or placetypes. Please refer to the [README.md](https://github.com/whosonfirst/whosonfirst-sources/blob/main/sources/README.md) file for complete data source metadata. Refer to our [blog post](https://whosonfirst.org/blog/2023/05/31/shapefiles/) for explanation of field names.  
  
Data corrections can be proposed using [Write Field](https://writefield.nextzen.org/), an web app for making quick data edits. You’ll need a Github.com account to login and propose edits, which are then reviewed by the Who's On First community using the Github pull request process. Approved changes are available for download within 24-hours. Please contact WOF admin about bulk edits.

Tags: administrative boundaries-divisions, geodata, populated places-settlements, population
Organization: Who's On First
South Sudan - Flow Monitoring Registry - January - August 2025

Flow monitoring aims to derive quantitative estimates of the flow of individuals through specific locations (usually border points) and to collect information about the demographic information and reasons for migration of the people moving. This helps to quantify highly mobile populations by providing a picture of complex mobility dynamics.

Tags: administrative boundaries-divisions, border crossings, demographics, gender and age disaggregated data-gadd, migration
Organization: International Organization for Migration (IOM)
Sudan: 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
Kazakhstan: 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
Whole of Afghanistan Assesment (dataset) 2025

The Whole of Afghanistan Assessment (WoAA) 2025 is a multi-sectoral needs assessment conducted through in-person, household-level interviews across all provinces and districts of Afghanistan. The dataset provides a comprehensive analysis of households’ sectoral and intersectoral needs across various domains, including health, education, nutrition, WASH, food security, and protection, among others. The results are statistically representative of male-headed households at the district level, and of female-headed households in nine provinces. In addition, the assessment includes displaced population groups, such as internally displaced persons (IDPs) — both those displaced recently (2025) and those displaced non-recently (2023–2024) — as well as cross-border returnees, classified similarly as recent and non-recent based on their displacement timeframe. These displaced population groups are represented at the regional level.

Tags: agriculture-livestock, displacement, drought, education, food security, gender, humanitarian access, internally displaced persons-idp, livelihoods, markets, natural disasters, non-food items-nfi, nutrition, protection, returnees, shelter, water sanitation and hygiene-wash
Organization: REACH Initiative
Mozambique Displacement Data - Baseline Assessment - Northern Mozambique Crisis - [IOM DTM]

The increase of security incidents in northern Mozambique since 2017 resulted in population displacement as well as subsequent humanitarian needs in virtually every humanitarian sector. To better understand the scope of displacement and needs of displaced populations, and in light of the intensification of the situation, the International Organization for Migration (IOM) activated its Displacement Tracking Matrix (DTM) in the Cabo Delgado province in February 2019.

Tags: conflict-violence, demographics, displacement, gender and age disaggregated data-gadd, hxl, internally displaced persons-idp
Organization: International Organization for Migration (IOM)
Sao Tome and Principe - 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
Cyprus: WOF Administrative Subdivisions and Human Settlements

This dataset contains administrative polygons grouped by country (admin-0) with the following subdivisions according to Who's On First placetypes:  
- macroregion (admin-1 including region)  
- region (admin-2 including state, province, department, governorate)  
- macrocounty (admin-3 including arrondissement)  
- county (admin-4 including prefecture, sub-prefecture, regency, canton, commune)  
- localadmin (admin-5 including municipality, local government area, unitary authority, commune, suburb)  
  
The dataset also contains human settlement points and polygons for:  
- localities (city, town, and village)  
- neighbourhoods (borough, macrohood, neighbourhood, microhood)  
  
The dataset covers activities carried out by Who's On First (WOF) since 2015. Global administrative boundaries and human settlements are aggregated and standardized from hundreds of sources and available with an open CC-BY license. Who's On First data is updated on an as-need basis for individual places with annual sprints focused on improving specific countries or placetypes. Please refer to the [README.md](https://github.com/whosonfirst/whosonfirst-sources/blob/main/sources/README.md) file for complete data source metadata. Refer to our [blog post](https://whosonfirst.org/blog/2023/05/31/shapefiles/) for explanation of field names.  
  
Data corrections can be proposed using [Write Field](https://writefield.nextzen.org/), an web app for making quick data edits. You’ll need a Github.com account to login and propose edits, which are then reviewed by the Who's On First community using the Github pull request process. Approved changes are available for download within 24-hours. Please contact WOF admin about bulk edits.

Tags: administrative boundaries-divisions, geodata, populated places-settlements, population
Organization: Who's On First
Satellite detected water extent and impact over Sylhet, Mymensingh, Dhaka, and Chattogram Divisions as of 19 Jun. 2022.

**UNOSAT code: FL20220525BGD**  This map illustrates satellite-detected surface waters in Sylhet, Mymensingh, Dhaka, and Chattogram Divisions, Bangladesh observed from a RCM-1 images acquired on 19 Jun. 2022 at 18:02 local time. Within the analyzed area of about 22,300 km2, about 9,500 km2 of lands appear to be flooded. In this area, about 7,860 km2 of croplands and 1,340 km2 of herbaceous wetland appear to be likely affected by the flood waters.

Based on Worldpop population data and the detected surface waters, about 7,334,000 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)
Satellite detected waters in Quang Nam Province of Viet Nam as of 17 October 2020

**UNOSAT code: TC20201013VNM**  This map illustrates satellite-detected surface waters in Quang Nam Province of Viet Nam as observed from a Radarsat Constellation 1 image acquired on 17 October 2020. Within the analyzed area of about 6,000 km2, a total of about 135 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters, about 84,000 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 UNITAR-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)
Satellite detected water extents between the 13th and the 17th November 2020 in El Salvador

**UNOSAT code: TC20201118SLV**  This map illustrates satellite-detected surface waters (cumulative) in El Salvador as detected by VIIRS-NOAA satellite between 13th & 17th November 2020. Within the analyzed area of about 20,000 km2, a total of about 440 km2 of lands appear to be flooded. Based on HRSL population data and the detected surface waters, about 44,000 people are potentially exposed or living close to flooded areas. The potentially exposed population is mainly located in the departments of Usulutan with ~9,000 people, La Union with ~8,500 people, and Santa Ana with ~7,500 people. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.

Tags: cyclones-hurricanes-typhoons, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Pakistan Gridded Population Dataset

The methods developed for Haiti were refined for Pakistan, where a similar correlation was found between built-up areas and 1998 census data. The 100-meter gridded population map was made available to the public during summer 2010’s severe flooding via a viewer and a data download page. The methods used in the Pakistan project are described in a paper published in the journal Remote Sensing of Environment.

Tags: geodata, population
Organization: U.S. Census Bureau
Central America - Evolution of the IPC

The dataset displays the Integrated Food Security Phase Classification (IPC), a standardized global scale used to measure the severity and magnitude of food insecurity and malnutrition. The data, compared with a five-year historical series for the countries of El Salvador, Guatemala, and Honduras, have been assessed based on information obtained from the IPC portal.

For more information contact GIS4Tech: info@gis4tech.com. You can also visit the PREDISAN platform https://predisan.gis4tech.com/ca4 for detailed, accurate information.

Tags: integrated food security phase classification-ipc
Organization: Acción contra el hambre - GIS4tech
Latvia: WOF Administrative Subdivisions and Human Settlements

This dataset contains administrative polygons grouped by country (admin-0) with the following subdivisions according to Who's On First placetypes:  
- macroregion (admin-1 including region)  
- region (admin-2 including state, province, department, governorate)  
- macrocounty (admin-3 including arrondissement)  
- county (admin-4 including prefecture, sub-prefecture, regency, canton, commune)  
- localadmin (admin-5 including municipality, local government area, unitary authority, commune, suburb)  
  
The dataset also contains human settlement points and polygons for:  
- localities (city, town, and village)  
- neighbourhoods (borough, macrohood, neighbourhood, microhood)  
  
The dataset covers activities carried out by Who's On First (WOF) since 2015. Global administrative boundaries and human settlements are aggregated and standardized from hundreds of sources and available with an open CC-BY license. Who's On First data is updated on an as-need basis for individual places with annual sprints focused on improving specific countries or placetypes. Please refer to the [README.md](https://github.com/whosonfirst/whosonfirst-sources/blob/main/sources/README.md) file for complete data source metadata. Refer to our [blog post](https://whosonfirst.org/blog/2023/05/31/shapefiles/) for explanation of field names.  
  
Data corrections can be proposed using [Write Field](https://writefield.nextzen.org/), an web app for making quick data edits. You’ll need a Github.com account to login and propose edits, which are then reviewed by the Who's On First community using the Github pull request process. Approved changes are available for download within 24-hours. Please contact WOF admin about bulk edits.

Tags: administrative boundaries-divisions, geodata, populated places-settlements, population
Organization: Who's On First
Eritrea: WOF Administrative Subdivisions and Human Settlements

This dataset contains administrative polygons grouped by country (admin-0) with the following subdivisions according to Who's On First placetypes:  
- macroregion (admin-1 including region)  
- region (admin-2 including state, province, department, governorate)  
- macrocounty (admin-3 including arrondissement)  
- county (admin-4 including prefecture, sub-prefecture, regency, canton, commune)  
- localadmin (admin-5 including municipality, local government area, unitary authority, commune, suburb)  
  
The dataset also contains human settlement points and polygons for:  
- localities (city, town, and village)  
- neighbourhoods (borough, macrohood, neighbourhood, microhood)  
  
The dataset covers activities carried out by Who's On First (WOF) since 2015. Global administrative boundaries and human settlements are aggregated and standardized from hundreds of sources and available with an open CC-BY license. Who's On First data is updated on an as-need basis for individual places with annual sprints focused on improving specific countries or placetypes. Please refer to the [README.md](https://github.com/whosonfirst/whosonfirst-sources/blob/main/sources/README.md) file for complete data source metadata. Refer to our [blog post](https://whosonfirst.org/blog/2023/05/31/shapefiles/) for explanation of field names.  
  
Data corrections can be proposed using [Write Field](https://writefield.nextzen.org/), an web app for making quick data edits. You’ll need a Github.com account to login and propose edits, which are then reviewed by the Who's On First community using the Github pull request process. Approved changes are available for download within 24-hours. Please contact WOF admin about bulk edits.

Tags: administrative boundaries-divisions, geodata, populated places-settlements, population
Organization: Who's On First
Cameroon - SENS survey in the Central African refugee sites of the eastern region and Adamou, January and March 2015

UNHCR in collaboration with the Ministry of Public Health (MINSANTE) and all of its partners decided to carry out a SENS survey in all the sites developed for Central African refugees in the East and Adamawa regions in the period from January to March 2015. This is an extensive nutritional survey that includes six modules: anthropometry and health, anemia, Infant and Young Child Feeding (IYCF), Food security, Water, Sanitation and Hygiene, and Mosquito net coverage. This edition is the first of this kind of investigation into the operation to assist Central African refugees in Cameroon. Its interest is linked to the fact that it is a scientific work which provides basic information in several sensitive areas. Also it will serve as a basis for decision-making and orientation of ongoing projects, and then make advocacy for fundraising. This assessment is also part of a continuous monitoring of the nutritional situation of these refugee populations over time.

Tags: food security, health, nutrition, water sanitation and hygiene-wash
Organization: UNHCR - The UN Refugee Agency
Egypt: WOF Administrative Subdivisions and Human Settlements

This dataset contains administrative polygons grouped by country (admin-0) with the following subdivisions according to Who's On First placetypes:  
- macroregion (admin-1 including region)  
- region (admin-2 including state, province, department, governorate)  
- macrocounty (admin-3 including arrondissement)  
- county (admin-4 including prefecture, sub-prefecture, regency, canton, commune)  
- localadmin (admin-5 including municipality, local government area, unitary authority, commune, suburb)  
  
The dataset also contains human settlement points and polygons for:  
- localities (city, town, and village)  
- neighbourhoods (borough, macrohood, neighbourhood, microhood)  
  
The dataset covers activities carried out by Who's On First (WOF) since 2015. Global administrative boundaries and human settlements are aggregated and standardized from hundreds of sources and available with an open CC-BY license. Who's On First data is updated on an as-need basis for individual places with annual sprints focused on improving specific countries or placetypes. Please refer to the [README.md](https://github.com/whosonfirst/whosonfirst-sources/blob/main/sources/README.md) file for complete data source metadata. Refer to our [blog post](https://whosonfirst.org/blog/2023/05/31/shapefiles/) for explanation of field names.  
  
Data corrections can be proposed using [Write Field](https://writefield.nextzen.org/), an web app for making quick data edits. You’ll need a Github.com account to login and propose edits, which are then reviewed by the Who's On First community using the Github pull request process. Approved changes are available for download within 24-hours. Please contact WOF admin about bulk edits.

Tags: administrative boundaries-divisions, geodata, populated places-settlements, population
Organization: Who's On First
Congo: WOF Administrative Subdivisions and Human Settlements

This dataset contains administrative polygons grouped by country (admin-0) with the following subdivisions according to Who's On First placetypes:  
- macroregion (admin-1 including region)  
- region (admin-2 including state, province, department, governorate)  
- macrocounty (admin-3 including arrondissement)  
- county (admin-4 including prefecture, sub-prefecture, regency, canton, commune)  
- localadmin (admin-5 including municipality, local government area, unitary authority, commune, suburb)  
  
The dataset also contains human settlement points and polygons for:  
- localities (city, town, and village)  
- neighbourhoods (borough, macrohood, neighbourhood, microhood)  
  
The dataset covers activities carried out by Who's On First (WOF) since 2015. Global administrative boundaries and human settlements are aggregated and standardized from hundreds of sources and available with an open CC-BY license. Who's On First data is updated on an as-need basis for individual places with annual sprints focused on improving specific countries or placetypes. Please refer to the [README.md](https://github.com/whosonfirst/whosonfirst-sources/blob/main/sources/README.md) file for complete data source metadata. Refer to our [blog post](https://whosonfirst.org/blog/2023/05/31/shapefiles/) for explanation of field names.  
  
Data corrections can be proposed using [Write Field](https://writefield.nextzen.org/), an web app for making quick data edits. You’ll need a Github.com account to login and propose edits, which are then reviewed by the Who's On First community using the Github pull request process. Approved changes are available for download within 24-hours. Please contact WOF admin about bulk edits.

Tags: administrative boundaries-divisions, geodata, populated places-settlements, population
Organization: Who's On First