AndreaBozzo/ceres-open-data-index huggingface dataset:
GRID3 COD - Health Zones v8.0

The GRID3 COD - Health Zones v8.0 dataset consists of health zone boundaries with name and other related attributes for all the twenty-six provinces in the Democratic Republic of the Congo (COD).

This operational dataset has not been fully validated by government officials or ministries.

The current version supersedes the GRID3 COD - Health Zones v7.0. The following changes were made:

- Added data for the provinces of Bas-Uele, Haut-Uele, Kwango, and Nord-Kivu
- The data for Tanganyika was updated.

Suggested Dataset Citation:

Center for Integrated Earth System Information (CIESIN), Columbia University, Ministère de la Santé Publique, Hygiène et Prévention, Democratic Republic of the Congo, and GRID3. 2025. GRID3 COD - Health Zones v8.0. New York: Columbia University. URL. Accessed DAY MONTH YEAR.



Tags: geodata, health
Organization: GRID3
Lesotho - 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
Syria - Damage density 2015 of Idlib, Idlib Governorate

This map illustrates satellite-detected damage density in the city of Idlib, Syrian Arab Republic. Using satellite imagery acquired 06 April 2015, 02 May 2014, 15 September 2013, and 22 March 2010 UNITAR - UNOSAT identified a total of 545 affected structures within the city. Approximately 176 of these were destroyed, 180 severely damaged, and 189 moderately damaged. While much of the city was damaged by 02 May 2014, 249 structures were newly damaged and 5 structures experienced an increase in damage between that date and 06 April 2015. 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)
Floodwater depth in Camarines Sur Provinces & Albay Province, Bicol Region of Philippines as of 1 November 2020

**UNOSAT code: TC20201101PHL**  This map illustrates floodwater depth in Nabua and Baao Municipalities, Camarines Sur Provinces & Bato and Libon, Albay Province, Bicol Region (Region V) of Philippines  based on surface waters observed from a Sentinel-1 image acquired on 1st of November 2020 and 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)
GRID3 COD - Settlement Names v8.0

The GRID3 COD - Settlement Names v8.0 dataset consists of settlement points with name and attributes for all the twenty-six provinces in the Democratic Republic of the Congo (COD).

This operational dataset has not been fully validated by government officials or ministries.

This current version supersedes the GRID3 COD - Settlement Names v7.0 The following changes were made:

- Added data for the provinces of Bas-Uele, Haut-Uele, Kwango, and Nord-Kivu
- The data for Tanganyika was updated

Suggested Dataset Citation:
Center for Integrated Earth System Information (CIESIN), Columbia University, Ministère de la Santé Publique, Hygiène et Prévention, Democratic Republic of the Congo, and GRID3. 2025. GRID3 COD - Settlement Names v8.0. New York: GRID3. URL. Accessed DAY-MONTH-YEAR


Tags: geodata, populated places-settlements
Organization: GRID3
Coulée de lave et structures affectées suite à l'éruption volcanique du Nyiragongo, Province du Nord-Kivu, RD Congo

**UNOSAT code: VO20210523COD**  Cette carte illustre les structures et bâtiments potentiellement impactées par la coulée de lave dans le district de Nyiragongo, province du Nord-Kivu en République Démocratique du Congo suite à l'éruption  du volcan Nyiragongo du 22 mai 2021. A partir de l'analyse d'une image radar TerraSAR-X acquise le 24 mai 2021 à 16:13 UTC, UNITAR-UNOSAT a observé une coulée de lave qui s'est arrêtée à 700m des installations aéroportuaires. Sur l'étendue de l'analyse, environ 1,600 structures sont potentiellement impactées par la coulée de lave à la date d'acquisition de l'image radar.
Ceci est une analyse préliminaire et n'a pas encore été validée sur le terrain. Veuillez d'envoyer vos commentaires à UNITAR-UNOSAT.
Note:  L'analyse de coulée de lave à partir d'une image radar peut surestimer la trace de la coulée de lave à cause du coefficient de rétrodiffusion du signal radar.

Tags: geodata, natural disasters
Organization: United Nations Satellite Centre (UNOSAT)
Geodata of Satellite Detected Waters Over Ampara and Batticaloa Districts, Sri Lanka

This map illustrates satellite-detected areas of flood water as observed in Sentinel-1 imagery collected 24 November 2014 and 18 December 2014. Waters extended along coastal areas and shores of inland lakes, with few large bodies of flood waters detected. Numerous roads and railroads are likely inundated by flood waters which may impede transport in those areas. It is likely that flood waters have been systematically underestimated in highly vegetated areas along main river banks, and within built-up urban areas because of the characteristics of the satellite data used. This analysis has not yet been validated in the field. Please send ground feedback to UNITAR /UNOSAT.

Tags: flooding, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Sudan: Sanitary Pad Distribution and GBV Awareness Activities – Kassala State

This dataset summarizes sanitary pad distribution and gender-based violence (GBV) awareness activities implemented by Sanabl Al Ataa Organization in Kassala State, Sudan, between 30 November and 7 December 2025.

The activities targeted women and girls, including internally displaced persons (IDPs), and aimed to improve menstrual hygiene management, reduce stigma related to menstruation, and strengthen basic protection awareness.

The dataset contains aggregated, non-sensitive data collected during school- and community-based interventions.

Tags: education, education facilities-schools, female, forced displacement, gender-based violence-gbv, girls, internally displaced persons-idp
Organization: Sanabl Al Ataa Organization
Satellite detected waters in Camarines Norte Province, Bicol Region (Region V) of Philippines as of 12 November 2020

**UNOSAT code: TC20201111PHL**  This map illustrates satellite-detected surface waters in Camarines Norte province of Philippines as observed from a Sentinel-1 image acquired on 12 November 2020 at 05:38 local time. Within the analyzed area of about 650 km2, a total of about 60 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters, about 32,000 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 extent over Zambezia and Sofala  province,  Mozambique as of 02 February 2022

**UNOSAT code: TC20220124MOZ**  This map illustrates satellite-detected surface waters in Malawi and Mozambique as observed from a Sentinel-1 image acquired on 02 February 2022 at 10:04 local time. The flood analysis were carried out by using an automated analysis with Artificial Intelligence based methods.

Within the analyzed area of about 145,978 km2, about 859 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters in the analyzed area, the potentially exposed population is mainly located in the districts of Mutarara, Cidade de Quelim and Morrumbala with respectively ~ 33,000 people, ~ 11,000 people, and  with ~16,600 people.

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)
Estimated precipitation accumulation over Yemen from 20th July to 1st August 2021

**UNOSAT code: FL20210729YEM**  This map illustrates the estimated total precipitation accumulated over Yemen. The total estimate was derived from the NASA Precipitation Processing System (PPS) dataset at a spatial resolution of approximately 10km and covers the period from 20th July to 1st August 2021. Western Governorates have been predominantly affected by precipitation, with some values greater than 600mm over the 13-day period. It is possible that precipitation levels may have been underestimated for local areas and are not a substitute for ground station measurements. 
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)
Satellite detected water extent over Aj Jabalain District, White Nile State of Sudan as of 22 September 2021

**UNOSAT code: FL20210907SDN**  This map illustrates satellite detected waters and the related potentially affected croplands as deduced using a satellite Kanopus-V image acquired on 22 September 2021 over Aj Jabalain District, White Nile State of Sudan. The water extent appears to have decreased of about 230 km2 since 12 September 2021. In this area, about 64 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)
Burkina Faso: Integrated Context Analysis (ICA), 2018


    The ICA is a process of consultations supported by mapped-out data that produces a strategic plan describing where different combinations of programme themes are appropriate to achieve goals of reducing food insecurity and climate related shock risk.

The ICA combines multi-year food security trends with natural shock risk data to highlight sub-national areas where different programme strategies make sense. Food security trend maps shows areas where safety nets can address regular food insecurity, and others where shocks make recovery more important. Climate-related natural shock risk maps show where DRR, preparedness and early warning efforts can complement food-security objectives. Atop this core foundation, mapped data on subjects including nutrition, gender, livelihoods and resilience can enrich theme-level strategic planning in which all pieces work together. The full group of ICA partners discuss these analytical results to arrive at strategic programmatic directions.
    

Tags: geodata, hazards and risk
Organization: WFP - World Food Programme
Global School Closures COVID-19

The number of children, youth and adults not attending schools or universities because of COVID-19 is soaring. Governments all around the world have closed educational institutions in an attempt to contain the global pandemic.

According to UNESCO monitoring, over 100 countries have implemented nationwide closures, impacting over half of world’s student population. Several other countries have implemented localized school closures and, should these closures become nationwide, millions of additional learners will experience education disruption.

Tags: covid-19, disease, education, education facilities-schools, epidemics-outbreaks, health, hxl
Organization: UNESCO
Satellite-detected water extents in Taolagnaro District, Anosy Region, Madagascar as of 27 February 2022

**UNOSAT code: TC20220221MDG**  This map illustrates satellite-detected surface waters in Taolagnaro District, Anosy Region, Madagascar as observed from a TerraSAR-X image acquired on 26 February 2022 at 18:15  local time. 
Within the analyzed area of about 140 km2, about 4 km2 of lands appear to be flooded. 
Based on Worldpop population data and the detected surface waters, about 400 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)
Satellite detected water extents as of 5 January 2026 in Sofala Province, Mozambique

**UNOSAT code: FL20251229MOZ, GDACS ID: 1103694**  This map illustrates the flood extent derived from Sentinel-1 imagery acquired on 5 January 2026, using an automated machine-learning-based analysis. Within the analysed area of approximately 25,000 km², an estimated 870 km² of land appears to be affected by floodwaters, representing an increase of about 100 km² compared to 31 December 2025 within the same analysed area. Based on WorldPop spatial demographic data, approximately 7,300 people are exposed to or living in close proximity 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).  
Important note: Flood analysis from radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to the backscattering properties of the radar signal.

Tags: flooding, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Ukraine - Subnational Administrative Boundaries

Ukraine administrative level 0-4 boundaries (COD-AB) dataset version 05.  
  
This dataset is structured into 4 levels:  
- Admin 1: 27 Oblast (Region)  
- Admin 2: 139 Raion (District)  
- Admin 3: 1769 Hromada (Community)  
- Admin 4: 29706 Settlement, partial coverage  
  
  
Note: This dataset is structured into 4 levels:
- Admin 1: 27 oblast (region) with three exceptions
- Admin 2: 139 raion (district) with three exceptions
- Admin 3: 1769 hromada (community) with three exceptions
- Admin 4: 29706 populated place (city, settlement or village), partial coverage  
  
  
Dates associated with this dataset:  
- 18 December 2025: dataset reviewed for accuracy and completeness  
- 01 September 2025: valid for use by the humanitarian community  
- 01 September 2025: last edit to the dataset before publishing  
  
Contributed by [OCHA Ukraine](https://data.humdata.org/organization/ocha-ukraine).  
Quality assured, configured, and published by [OCHA Field Information Services (FIS)](https://data.humdata.org/organization/ocha-fiss) and [HDX](https://data.humdata.org/organization/hdx).  
  
Part of the dataset: [Global Subnational Administrative Boundaries](https://data.humdata.org/dataset/cod-ab-global)

Tags: administrative boundaries-divisions, gazetteer, geodata
Organization: OCHA Field Information Services Section (FISS)
Registry of Russian NGO’s affected by COVID-19

Registry of Russian social-oriented non profit organizations recognized by the government as affected by COVID-19 and that receive government support. The Ministry of Economic Development of Russia published the register of non profit non government organizations (NGOs) that will be provided with additional measures of support.

Dataset columns: name of organization, OGRN, INN, Responsible government agency, Status, Orgform. 

The dataset contains information about 11 208 NGOs of 85 Russian regions. 


Tags: covid-19, governance and civil society
Organization: Infoculture
Whole of Afghanistan Assessment 2025 (Analysis)

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, health, humanitarian access, internally displaced persons-idp, livelihoods, malnutrition, markets, natural disasters, non-food items-nfi, protection, shelter, water sanitation and hygiene-wash
Organization: REACH Initiative
GRID3 COD - Travel Time Friction Surface v1.0

The aim of this work is to generate two friction surfaces for modeling physical accessibility in the Democratic Republic of the Congo: one incorporating walking speed only, and another combining walking and motorized travel speeds. Motorized speeds are applied exclusively on roads that are present and passable by vehicles; in all other areas, walking speeds are used.

The GRID3 COD - Travel Time Friction Surface v1.0 dataset is a spatial data layer in tiff format. The datasets contain 2 layers:

(1) GRID3_COD_walk_travel_time_friction_surface_v1_0.tif - Applies walking speeds across the entire surface, adjusted for slope and elevation.
(2) GRID3_COD_mix_travel_time_friction_surface_v1_0.tif - Applies motorized speeds on roads and walking speeds in all other areas.

The resolution is 30 m. The unit of measurement in both surfaces is minutes per meter.

Suggested Dataset Citation

Center for Integrated Earth System Information (CIESIN), Columbia University. 2026. GRID3 COD - Travel Time Friction Surface v1.0. New York: Columbia University. URL. Accessed DAY-MONTH-YEAR.


Tags: geodata, transportation
Organization: GRID3
Geodata of Damage Assessment of Aden, Aden Governorate, Yemen

This map illustrates satellite-detected damage and destruction in the city of Aden, Aden Governorate, Yemen. Using satellite imagery acquired 10 May 2015, 15 April 2015, and 31 December 2014, UNITAR-UNOSAT identified a total of 642 affected structures, 258 of which were temporarily assembled for a probable open street market. Approximately 327 structures were destroyed, 153 severely damaged, and 162 moderately damaged. Additionally, 38 impact craters were found within the city, the majority of which were located in the vicinity of Aden International Airport. A total of 13 medical facilities were identified within 100 meters of damaged and destroyed buildings, and it is possible that these facilities also sustained some damage. 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)
GRID3 COD - Gridded Population Estimates v4.4

Democratic Republic of the Congo gridded population estimates.

This data release provides gridded population estimates (spatial resolution of 3 arc-seconds, approximately 100-metre grid cells) for the Democratic Republic of the Congo (DRC), along with uncertainty estimates. The data is a mosaic of gridded population estimates produced for all 26 provinces namely Bas-Uele, Equateur, Haut-Katanga, Haut-Lomami, Haut-Uele, Ituri, Kasai, Kasai-Central, Kasai-Oriental, Kinshasa, Kongo-Central, Kwango, Kwilu, Lomami, Lualaba, Mai-Ndombe, Maniema, Mongala, Nord-Kivu, Nord-Ubangi, Sankuru, Sud-Kivu, Sud-Ubangi, Tanganyika, Tshopo and Tshuapa. The project team used the Pre-Distribution Registration Survey (PDRS) data from the National Malaria Control Programme (PNLP) collected as part of anti-malarial campaigns in the DRC, settlement extent and geospatial covariates to model and estimate population numbers at grid cell level using a Bayesian statistical hierarchical modelling framework. Please note that PNLP data were collected across the DRC, except in Kasai, Kasai Central, Kasai Oriental, Kwango, Nord Ubangi and Lualaba, where the modelling utilised observations from neighbouring provinces

The projection for all GIS files is the geographic coordinate system WGS84 (World Geodetic System 1984). Grid cells with values of NA represent areas that were mapped as unsettled according to building footprints data or being outside the national boundary.

Suggested Dataset Citation:
Yankey O., Nnanatu C., Boo G., Chaudhuri S., Krishnaveni K S, Megheib M, Bonnie A., Chamberlain H., Lazar A. N., Tatem A. J. 2025. Bottom-up gridded population estimates for the Democratic Republic of Congo, version 4.4. WorldPop. URL. Accessed DAY-MONTH-YEAR.


Tags: demographics, geodata, population
Organization: GRID3
Satellite detected water extents as of 23 January 2026 in Gaza, Maputo and Maputo City Provinces, Mozambique

**UNOSAT code: FL20251229MOZ**  This map illustrates the flood extent derived from Sentinel-1 imagery acquired on 23 January 2026. Within the analysed area of approximately 43,500 km², an estimated 3,000 km² of land appears to be affected by floodwaters. Based on WorldPop spatial demographic data, approximately 230,000 people are exposed to or living near 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).  
  
Important note: Flood analysis from radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to the backscattering properties of the radar signal.

Tags: flooding, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Satellite detected water extents in Nampula Province, Mozambique as of 13 March 2022

**UNOSAT code: TC20220311MOZ**  This map illustrates satellite-detected surface waters in Mossuril, Mogincual and Liúpo Districts, Nampula Province, Mozambique as observed from a Sentinel-1 image acquired on 13 February 2022 at 17:44 local time. Within the analyzed area of about 14,000 km2, about 110 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters, about 12,000 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: cyclones-hurricanes-typhoons, geodata
Organization: United Nations Satellite Centre (UNOSAT)