AndreaBozzo/ceres-open-data-index huggingface dataset:
Mokwa Town, Nigeria Railways (OpenStreetMap Export)


This theme includes all OpenStreetMap features in this area matching ( Learn what tags means [here](https://wiki.openstreetmap.org/wiki/Tags) ) :

tags['railway'] IN ('rail','station')

Features may have these attributes:

- [name](http://wiki.openstreetmap.org/wiki/Key:name)
- [railway](http://wiki.openstreetmap.org/wiki/Key:railway)
- [ele](http://wiki.openstreetmap.org/wiki/Key:ele)
- [operator:type](http://wiki.openstreetmap.org/wiki/Key:operator:type)
- [layer](http://wiki.openstreetmap.org/wiki/Key:layer)
- [addr:full](http://wiki.openstreetmap.org/wiki/Key:addr:full)
- [addr:city](http://wiki.openstreetmap.org/wiki/Key:addr:city)
- [source](http://wiki.openstreetmap.org/wiki/Key:source)

This dataset is one of many [OpenStreetMap exports on
HDX](https://data.humdata.org/organization/hot).
See the [Humanitarian OpenStreetMap Team](http://hotosm.org/) website for more
information.


Tags: facilities-infrastructure, geodata, railways, transportation
Organization: Humanitarian OpenStreetMap Team (HOT)
Mokwa Town, Nigeria Roads (OpenStreetMap Export)

OpenStreetMap contains roughly 205 km of roads in this region. Based on AI-mapped estimates, this is approximately 44 % of the total road length in the dataset region. The average age of data for the region is 3 years  ( Last edited 3 months ago ) and 5% of roads were added or updated in the last 6 months.
Read about what this summary means : [indicators](https://github.com/hotosm/raw-data-api/tree/develop/docs/src/stats/indicators.md) , [metrics](https://github.com/hotosm/raw-data-api/tree/develop/docs/src/stats/metrics.md)


This theme includes all OpenStreetMap features in this area matching ( Learn what tags means [here](https://wiki.openstreetmap.org/wiki/Tags) ) :

tags['highway'] IS NOT NULL

Features may have these attributes:

- [name](http://wiki.openstreetmap.org/wiki/Key:name)
- [highway](http://wiki.openstreetmap.org/wiki/Key:highway)
- [surface](http://wiki.openstreetmap.org/wiki/Key:surface)
- [smoothness](http://wiki.openstreetmap.org/wiki/Key:smoothness)
- [width](http://wiki.openstreetmap.org/wiki/Key:width)
- [lanes](http://wiki.openstreetmap.org/wiki/Key:lanes)
- [oneway](http://wiki.openstreetmap.org/wiki/Key:oneway)
- [bridge](http://wiki.openstreetmap.org/wiki/Key:bridge)
- [layer](http://wiki.openstreetmap.org/wiki/Key:layer)
- [source](http://wiki.openstreetmap.org/wiki/Key:source)

This dataset is one of many [OpenStreetMap exports on
HDX](https://data.humdata.org/organization/hot).
See the [Humanitarian OpenStreetMap Team](http://hotosm.org/) website for more
information.


Tags: geodata, roads, transportation
Organization: Humanitarian OpenStreetMap Team (HOT)
Belarus - Requirements and Funding Data

FTS publishes data on humanitarian funding flows as reported by donors and recipient organizations. It presents all humanitarian funding to a country and funding that is specifically reported or that can be specifically mapped against funding requirements stated in humanitarian response plans. The data comes from OCHA's [Financial Tracking Service](https://fts.unocha.org/), is encoded as utf-8 and the second row of the CSV contains [HXL](http://hxlstandard.org) tags.

Tags: covid-19, funding, humanitarian financial tracking service-fts, hxl
Organization: OCHA Financial Tracking System (FTS)
Mokwa Town, Nigeria Buildings (OpenStreetMap Export)

OpenStreetMap contains roughly 15.7 thousand buildings in this region. Based on AI-mapped estimates, this is approximately 85% of the total buildings.The average age of data for this region is 3 years ( Last edited 3 months ago ) and 0% buildings were added or updated in the last 6 months.
Read about what this summary means : [indicators](https://github.com/hotosm/raw-data-api/tree/develop/docs/src/stats/indicators.md) , [metrics](https://github.com/hotosm/raw-data-api/tree/develop/docs/src/stats/metrics.md)


This theme includes all OpenStreetMap features in this area matching ( Learn what tags means [here](https://wiki.openstreetmap.org/wiki/Tags) ) :

tags['building'] IS NOT NULL

Features may have these attributes:

- [name](http://wiki.openstreetmap.org/wiki/Key:name)
- [building](http://wiki.openstreetmap.org/wiki/Key:building)
- [building:levels](http://wiki.openstreetmap.org/wiki/Key:building:levels)
- [building:materials](http://wiki.openstreetmap.org/wiki/Key:building:materials)
- [addr:full](http://wiki.openstreetmap.org/wiki/Key:addr:full)
- [addr:housenumber](http://wiki.openstreetmap.org/wiki/Key:addr:housenumber)
- [addr:street](http://wiki.openstreetmap.org/wiki/Key:addr:street)
- [addr:city](http://wiki.openstreetmap.org/wiki/Key:addr:city)
- [office](http://wiki.openstreetmap.org/wiki/Key:office)
- [source](http://wiki.openstreetmap.org/wiki/Key:source)

This dataset is one of many [OpenStreetMap exports on
HDX](https://data.humdata.org/organization/hot).
See the [Humanitarian OpenStreetMap Team](http://hotosm.org/) website for more
information.


Tags: facilities-infrastructure, geodata
Organization: Humanitarian OpenStreetMap Team (HOT)
REACH Libya 2022 Multi-Sectoral Needs Assessment (Libyan Population)-Summary

This is the data summary of the 2022 Libyan population Multi-Sectoral Needs Assessment. The full dataset can be requested on the "REACH Libya 2022 Multi-Sectoral Needs Assessment (Libyan Population)" page.

Data collection took place between July 4th and October 4th, 2022 and covered a total of 3,758 households across 15 selected baladiyas. Findings are generalisable per population group and per baladiya with a 95 confidence interval and a 5% margin of error.** Findings relating to subsets of the sample are indicative only.

Tags: displacement, education, food security, health, internally displaced persons-idp, livelihoods, needs assessment, protection, water sanitation and hygiene-wash
Organization: REACH Initiative
Satellite detected water extents as of 31 December 2025 in Sofala Province, Mozambique

**UNOSAT code: FL20251229MOZ**  This map illustrates the flood extent derived from Sentinel-1 imagery acquired on 31 December 2025, using an automated machine-learning-based analysis. Within the analysed area of approximately 32,000 km², an estimated 930 km² of land appears to be affected by floodwaters. Based on WorldPop spatial demographic data, approximately 4,200 people are exposed to or living in 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).  
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)
Africa - HydroRIVERS - vectorized line network of all African rivers

HydroRIVERS represents a vectorized line network of all global rivers that have a catchment area of at least 10 km² or an average river flow of at least 0.1 m³/sec, or both. HydroRIVERS has been extracted from the gridded HydroSHEDS core layers at 15 arc-second resolution. The global coverage of HydroRIVERS encompasses 8.5 million individual river reaches with an average length of 4.2 km, representing a total of 35.9 million km of rivers globally. HydroRIVERS only includes a limited amount of (mostly geometric) attribute information, such as the river reach length, the distance from upstream headwaters and ocean outlet, the river order, and an estimate of long-term average discharge. Every river reach is also co-registered to the sub-basin of the HydroBASINS database in which it resides (via a shared ID).

More information: [Hydrosheds - Hydrorivers](https://www.hydrosheds.org/products/hydrorivers)

Tags: environment, rivers, water sanitation and hygiene-wash
Organization: 3iS
Africa - HydroBasin - vectorized polygon layers of hydrographic basins

HydroBASINS represents a series of vectorized polygon layers that depict sub-basin boundaries at a global scale. The goal of this product is to provide a seamless global coverage of consistently sized and hierarchically nested sub-basins at different scales (from tens to millions of square kilometers), supported by a coding scheme that allows for analysis of catchment topology such as up- and downstream connectivity. HydroBASINS has been extracted from the gridded HydroSHEDS core layers at 15 arc-second resolution.

More info: [HydroBASINS](https://www.hydrosheds.org/products/hydrobasins)

Tags: environment, water sanitation and hygiene-wash
Organization: 3iS
Satellite detected waters in Sirwah, Bani Dabyan, and Al Jubah districts of Yemen as of 26 July 2020

**UNOSAT code: FL20210729YEM**  This map illustrates satellite-detected surface waters over Sirwah, Bani Dabyan, and Al Jubah districts of Yemen as observed from a Sentinel-1 radar image acquired on 26 July 2021. Within the analyzed area of about 3,800 km2, a total of about 6.5 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters, about 1,800 people may be 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.



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

SABA Core dataset
This Syria core dataset comprises 14 quantitative indicators based on publicly available information from humanitarian organisations. It is updated on a monthly basis, and it covers the whole country. 
This dataset brings together data from a range of sources to provide a greater overall and comparative understanding of the current situation and context inside each district. The core dataset indicators cover a range of categories including agriculture, commodity prices (food and fuel), conflict, displacement, exchange rate, food security, humanitarian access severity, health, people in need per sector, and rainfall.  
When analysing and interpreting the data, please be aware that while we aim to include district-level data that is updated monthly, some indicators are updated on only a quarterly or annual basis and some data is only available on admin 1 level. Please ensure you check the details in the ‘indicator list’ tab and the references for each indicator before conducting analysis.  
The Syria Area Based Analysis (SABA) team recommends that this dataset is used only as a starting point. It will enable you to quickly examine and compare cross-sectoral, quantitative data at the district level in Syria. However, for operational decision making, we recommend you consult ACAPS analysis products on Syria available here: https://www.acaps.org/en/countries/syria 
ACAPS conducts random quality checking of a sample of entries to try to limit errors. However, it is likely that errors remain. For sensitive analysis, we recommend you cross check findings with the source data in the list of indicators and at the top row of each column. 
Do you have ideas to make this data set more useful? Do you see mistakes or disagree with our opinions or assumptions? Contact us at info@acaps.org. Your feedback helps us do better. 

Organization: ACAPS
Mokwa Town, Nigeria Financial Services (OpenStreetMap Export)


This theme includes all OpenStreetMap features in this area matching ( Learn what tags means [here](https://wiki.openstreetmap.org/wiki/Tags) ) :

tags['amenity'] IN ('mobile_money_agent','bureau_de_change','bank','microfinance','atm','sacco','money_transfer','post_office')

Features may have these attributes:

- [name](http://wiki.openstreetmap.org/wiki/Key:name)
- [amenity](http://wiki.openstreetmap.org/wiki/Key:amenity)
- [operator](http://wiki.openstreetmap.org/wiki/Key:operator)
- [network](http://wiki.openstreetmap.org/wiki/Key:network)
- [addr:full](http://wiki.openstreetmap.org/wiki/Key:addr:full)
- [addr:city](http://wiki.openstreetmap.org/wiki/Key:addr:city)
- [source](http://wiki.openstreetmap.org/wiki/Key:source)

This dataset is one of many [OpenStreetMap exports on
HDX](https://data.humdata.org/organization/hot).
See the [Humanitarian OpenStreetMap Team](http://hotosm.org/) website for more
information.


Tags: economics, geodata
Organization: Humanitarian OpenStreetMap Team (HOT)
French Polynesia - Age and gender structures

<b>WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. 
Please make sure you have read our <a href="/methods/populations" target="_blank">Mapping Populations</a> overview page before choosing and downloading a dataset.</b> 
<br/><br/>   

A description of the modelling methods used for age and gender structures can be found in 
<a href="https://pophealthmetrics.biomedcentral.com/articles/10.1186/1478-7954-11-11" target="_blank">
Tatem et al</a> and 
<a href="https://dx.doi.org/10.1038/sdata.2017.89" target="_blank">Pezzulo et al</a>. Details of the input population count datasets used can be found <a href="https://www.worldpop.org/project/categories?id=3" target="_blank">here</a>, and age/gender structure proportion datasets <a href="https://www.portal.worldpop.org/demographics/data/global_agegender_proportions_totals_2020.zip" target="_blank">here</a>. 
<br/>
Both top-down 'unconstrained' and 'constrained' versions of the datasets are available, and the differences between the two methods are outlined 
<a href="/methods/top_down_constrained_vs_unconstrained" target="_blank">here</a>. The  datasets represent the outputs from a project focused on construction of consistent 100m resolution population count datasets for all countries of the World structured by male/female and 5-year age classes (plus a <1 year class). These efforts necessarily involved some shortcuts for consistency. The unconstrained datasets are available for each year from 2000 to 2020.  
The constrained datasets are only available for 2020 at present, given the time periods represented by the building footprint and built settlement datasets used in the mapping.  
Data for earlier dates is available directly from WorldPop.  
  
WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00646

Tags: baseline population, demographics, geodata
Organization: WorldPop
Sierra Leone: Integrated Context Analysis (ICA), 2017


    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
GRID3 NGA - Travel Time Friction Surface v1.0

The aim of this work is to generate two friction surfaces for modeling physical accessibility: 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 NGA - Travel Time Friction Surface v1.0 dataset is a spatial data layer in tiff format. The datasets contain 2 layers:
⦁	GRID3_NGA_walk_travel_time_friction_surface_v1_0.tif - Applies walking speeds across the entire surface, adjusted for slope and elevation.
⦁	GRID3_NGA_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.


Dataset citation: Center for Integrated Earth System Information (CIESIN), Columbia University. 2025. GRID3 NGA - Travel Time Friction Surface v1.0. New York: Columbia University. URL. Accessed DAY-MONTH-YEAR.

Contacts and data queries: 
The authors of this dataset appreciate feedback regarding the data, including suggestions, discovery of errors, difficulties in using the data, and format preferences. For dataset-related questions, please send an email to: info@ciesin.columbia.edu


Tags: geodata, transportation
Organization: GRID3
Satellite detected water extent over Rajshahi, Rangpur, Mymensingh and Khulna Divisions, Bangladesh as of 21 June 2022

**UNOSAT code: FL20220525BGD**  This map illustrates satellite-detected surface waters in Rajshahi, Rangur, Mymensingh, Dhaka and Khulna Divisions, Bangladesh as observed from a Sentinel-1 images acquired on 21 Jun. 2022 at 18:05 local time and using an automated analysis with machine learning method. Within the analyzed area of about 20,400 km2, about 2,950 km2 of lands appear to be flooded. Water extent appears to have increased of about 2,360 km2 since 9 Jun. 2022.

Based on Worldpop population data and the detected surface waters in the analyzed area, the potentially exposed population is mainly located in the division of Rajshahi with ~1,335,000 people, Dhaka with 674,000 people,and Mymensingh with ~ 640,000 people.

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)
Mokwa Town, Nigeria Populated Places (OpenStreetMap Export)


This theme includes all OpenStreetMap features in this area matching ( Learn what tags means [here](https://wiki.openstreetmap.org/wiki/Tags) ) :

tags['place'] IN ('isolated_dwelling', 'town', 'village', 'hamlet', 'city')

Features may have these attributes:

- [name](http://wiki.openstreetmap.org/wiki/Key:name)
- [place](http://wiki.openstreetmap.org/wiki/Key:place)
- [population](http://wiki.openstreetmap.org/wiki/Key:population)
- [is_in](http://wiki.openstreetmap.org/wiki/Key:is_in)
- [source](http://wiki.openstreetmap.org/wiki/Key:source)

This dataset is one of many [OpenStreetMap exports on
HDX](https://data.humdata.org/organization/hot).
See the [Humanitarian OpenStreetMap Team](http://hotosm.org/) website for more
information.


Tags: facilities-infrastructure, geodata, populated places-settlements
Organization: Humanitarian OpenStreetMap Team (HOT)
Inundaciones en Nicaragua entre el 13 y 17 de Noviembre 2020

**UNOSAT code: TC20201116NIC**  Este mapa ilustra las inundaciones detectadas por el satélite NOAA-VIIRS en Nicaragua entre el 13 y 17 de Noviembre. Dentro del área analizada de aproximadamente 95,000 km2, un total de aproximadamente 2,000 km2 de tierras parecen estar inundadas. Basado en los datos de población de Worldpop y la extensión de las aguas superficiales detectadas, alrededor de 100,000 personas están potencialmente expuestas o viven cerca de áreas inundadas. La población potencialmente expuesta se encuentra principalmente en el departamento de Chinandega con ~25,000 habitantes, en el departamento de Manague con ~16,000 habitantes, y em el departamento de Atlántico Norte con 10,000 habitantes. Se trata de un análisis preliminar que aún no ha sido validado en el terreno. Por favor envíe comentarios a UNITAR-UNOSAT.

Tags: cyclones-hurricanes-typhoons, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Ukraine - 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
Afghanistan: Humanitarian Situation Monitoring (HSM) Round 11 KII (Analysis)

The Humanitarian Situation Monitoring (HSM) is a quarterly community-level multi-sectoral needs assessment. It builds upon the previously implemented Hard-to-Reach assessment and expanded its geographic coverage to encompass the entire country in early 2022, due to the shift in context. HSM aims to collect and triangulate information regularly regarding service provision, sectoral needs, and vulnerabilities in Afghan communities to support geographical and sectoral prioritizations, particularly in light of Afghanistan's rapidly evolving context. HSM assesses the sectoral and multi-sectoral needs of populations in all districts by filling in information gaps and enhancing response capacity for district-level prioritization.

Tags: displacement, education, food security, health, livelihoods, markets, non-food items-nfi, shelter, water sanitation and hygiene-wash
Organization: REACH Initiative
Central America - Productivity by Country

This dataset shows a comparison of the production of staple grains, green coffee, and sugar in El Salvador, Guatemala, Honduras, and Nicaragua. Units of measurement are: staple grains in thousands of metric tons (1,000 MT), coffee in thousands of 60-kilogram bags (K.60Kg Bags), and sugar in thousands of hectares (K.HA). The data are from the United States Department of Agriculture (USDA) database.

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: agriculture-livestock
Organization: Acción contra el hambre - GIS4tech
Central America - Legal Migrants

The dataset presents the number of labor migrants admitted into the United States (I-94) from El Salvador, Guatemala, Honduras, and Nicaragua, as well as the number of Nicaraguans registered under the humanitarian parole program, H2A visas (temporary agricultural) and H2B visas (temporary non-agricultural), and the total sum of all these groups. The data are periodically updated using advanced data collection techniques and document scraping from the Office of Homeland Security Statistics.

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: migration
Organization: Acción contra el hambre - GIS4tech
Kyrgyzstan - 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