AndreaBozzo/ceres-open-data-index huggingface dataset:
Electric Power Substations in Myanmar

Non-authoritative dataset of >300  approximate centre point locations of of electricity transmission and distribution substations as of 2025. Produced by CDE Myanmar based on publicly available reference data (incl. https://www.moep.gov.mm/en/ignite/page/641), OpenStreetMap, local knowledge and high resolution satellite imagery.
The attribute data includes the non-authoritative English name of each substation along with a "best-guess" operational status as of 2025, based on satellite imagery analysis and publicly available online sources.

Creation methodology:
- Identifying substation locations primarily based on https://www.moep.gov.mm/en/ignite/page/641, OpenStreetMap and high resolution satellite imagery.
- Mapping the approximate centrepoint of each substation and matching it with the reference data available.
- assigning a "power facility code" to each substation
- operational status was assessed based on satellite imagery, considering visible signs of ongoing construction, complete decommissioning, or disuse
- assigning substation type and capacity (in KV) based on MOEP reference map from 2019, internet searches and "best guess" assessment based on the visual apearance of the substation in the imagery.
- assigning a non-authoritative substation name, based on google maps, MOEP, OSM and other publicly available data.
- creating a public dataset by excluding planned and non-confirmed substation locations and by reducing the attribute table to a selection of cleaned and relevant fields.

Known issues: 
- Substation names are unofficial and non-authoritative; Myanmar-language names are still missing.
- Some substations have been classified as industrial or power plant substations when there was strong evidence linking them to industrial facilities or when they serve to feed electricity generated on-site into the grid. However, the majority of substations are classified as unspecified, assumed to be general power grid transmission or distribution substations—though this classification is not always certain.
- A few larger substations (66 kV and above) are still missing, while the number of missing substations at 33 kV and below is uncertain.
- The matching of substation locations with data from the Ministry of Electricity and Energy (MOEP) and other reference sources is not always reliable, and mismatches may have occurred in the dataset.
- for some substations no names are known or are highly uncertain. Those names are places in square backets "[]"

Spatial dataset created based on approximately 1:5.000 scaled imagery.

Tags: geodata, populated places-settlements
Organization: Myanmar Information Management Unit (MIMU)
Buildings of Cameroon

Building footprints across the region: every feature tagged `building=*`, from residential homes to hospitals, schools, and places of worship. Useful for population estimation, damage assessment, and urban planning.

Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge.

- Source: [OpenStreetMap](https://www.openstreetmap.org), a free, collaborative world map
- Tags: [building](https://wiki.openstreetmap.org/wiki/Key:building)
- Part of the [exports grid on HDX](https://data.humdata.org/organization/hot/) by [HOT](https://www.hotosm.org/)


Tags: facilities-infrastructure, geodata
Organization: Humanitarian OpenStreetMap Team (HOT)
Roads of Mozambique

Road network across the region tagged `highway=*`: motorways, residential streets, service roads, footways, and trails. Useful for routing, accessibility analysis, and evacuation planning.

Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge.

- Source: [OpenStreetMap](https://www.openstreetmap.org), a free, collaborative world map
- Tags: [highway](https://wiki.openstreetmap.org/wiki/Key:highway)
- Part of the [exports grid on HDX](https://data.humdata.org/organization/hot/) by [HOT](https://www.hotosm.org/)


Tags: geodata, roads, transportation
Organization: Humanitarian OpenStreetMap Team (HOT)
Railways of Niger

Railway lines and stations tagged `railway=*`: rail lines, tram tracks, and stations. Useful for transport accessibility analysis and basemap context.

Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge.

- Source: [OpenStreetMap](https://www.openstreetmap.org), a free, collaborative world map
- Tags: [railway](https://wiki.openstreetmap.org/wiki/Key:railway)
- Part of the [exports grid on HDX](https://data.humdata.org/organization/hot/) by [HOT](https://www.hotosm.org/)


Tags: facilities-infrastructure, geodata, railways, transportation
Organization: Humanitarian OpenStreetMap Team (HOT)
Financial Services of Mozambique

Financial services: banks, ATMs, post offices, money transfer agents, and microfinance branches tagged via `amenity`. Useful for financial-inclusion mapping, cash-distribution planning, and economic analysis.

Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge.

- Source: [OpenStreetMap](https://www.openstreetmap.org), a free, collaborative world map
- Tags: [amenity](https://wiki.openstreetmap.org/wiki/Key:amenity)
- Part of the [exports grid on HDX](https://data.humdata.org/organization/hot/) by [HOT](https://www.hotosm.org/)


Tags: economics, geodata
Organization: Humanitarian OpenStreetMap Team (HOT)
Buildings of Lebanon

Building footprints across the region: every feature tagged `building=*`, from residential homes to hospitals, schools, and places of worship. Useful for population estimation, damage assessment, and urban planning.

Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge.

- Source: [OpenStreetMap](https://www.openstreetmap.org), a free, collaborative world map
- Tags: [building](https://wiki.openstreetmap.org/wiki/Key:building)
- Part of the [exports grid on HDX](https://data.humdata.org/organization/hot/) by [HOT](https://www.hotosm.org/)


Tags: crisis-greater-middle-east, facilities-infrastructure, geodata
Organization: Humanitarian OpenStreetMap Team (HOT)
Health Facilities of Congo, The Democratic Republic of the

Health facilities: hospitals, clinics, pharmacies, doctors, and dentists tagged via `amenity` or `healthcare`. Useful for service-access analysis, emergency response, and healthcare gap mapping.

Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge.

- Source: [OpenStreetMap](https://www.openstreetmap.org), a free, collaborative world map
- Tags: [amenity](https://wiki.openstreetmap.org/wiki/Key:amenity), [healthcare](https://wiki.openstreetmap.org/wiki/Key:healthcare)
- Part of the [exports grid on HDX](https://data.humdata.org/organization/hot/) by [HOT](https://www.hotosm.org/)


Tags: crisis-ebola-bundibugyo-virus-disease, geodata, health, health facilities
Organization: Humanitarian OpenStreetMap Team (HOT)
Southeast Asia - MODIS Active Fire Detections

Near-real-time active fire and thermal anomaly detections from NASA's [Fire Information for Resource Management System (FIRMS)](https://firms.modaps.eosdis.nasa.gov/active_fire/) covering **Southeast Asia**, derived from the **MODIS** sensor family (Terra since 2000, Aqua since 2002).

Each resource is an external link directly to a NASA-hosted file. The files are continuously updated as new satellite overpasses are processed (typically within 3 hours of acquisition).

**Formats:** SHP, KML, CSV

**Time windows:** Last 24h, 48h, 7d


Tags: climate hazards, environment, geodata, hazards and risk, natural disasters
Organization: NASA Fire Information for Resource Management System
Education Facilities of Ethiopia

Education facilities: schools, kindergartens, colleges, and universities tagged via `amenity` or `building`. Useful for school-access mapping, education planning, and resource allocation.

Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge.

- Source: [OpenStreetMap](https://www.openstreetmap.org), a free, collaborative world map
- Tags: [amenity](https://wiki.openstreetmap.org/wiki/Key:amenity), [building](https://wiki.openstreetmap.org/wiki/Key:building)
- Part of the [exports grid on HDX](https://data.humdata.org/organization/hot/) by [HOT](https://www.hotosm.org/)


Tags: education facilities-schools, geodata
Organization: Humanitarian OpenStreetMap Team (HOT)
Airports of Ethiopia

Airports and aviation infrastructure: airports, heliports, helipads, runways, terminals, and emergency landing sites tagged via `aeroway`, `building`, or `emergency`. Useful for logistics, evacuation routing, and aerial-response planning.

Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge.

- Source: [OpenStreetMap](https://www.openstreetmap.org), a free, collaborative world map
- Tags: [aeroway](https://wiki.openstreetmap.org/wiki/Key:aeroway), [building](https://wiki.openstreetmap.org/wiki/Key:building), [emergency](https://wiki.openstreetmap.org/wiki/Key:emergency)
- Part of the [exports grid on HDX](https://data.humdata.org/organization/hot/) by [HOT](https://www.hotosm.org/)


Tags: aviation, facilities-infrastructure, geodata
Organization: Humanitarian OpenStreetMap Team (HOT)
Uganda- Mbale District: Operational Presence

This dataset contains Who, What, Where and When (4W) data for the district of Mbale in Uganda. The operational presence of the various organisations (who) by sector (what), location (where) at the province level and when the information was collected (when). 

Tags: hxl, operational partners, operational presence, who is doing what and where-3w-4w-5w
Organization: Fields Data
American Red Cross West Africa Project

From February to October 2016, the American Red Cross and its local Red Cross partners completed an effort to extensively map areas within a 15-kilometer distance of the shared borders between Guinea, Liberia, and Sierra Leone. 

The goal of this work was to create an open and comprehensive dataset of communities for West Africa and to ensure that decision makers, humanitarian workers, and community stakeholders are better aware of water, sanitation, health, and community resources before and during the next crisis.

To complete this mapping, the American Red Cross launched a mapping center in Guéckédou, Guinea, and used it as both a base of operations and a community engagement facility. Over 100 volunteers helped to complete a rapid assessment of the region, visiting over 7,000 communities by motorbike to complete a vulnerability survey with the village leader. Next, over 100 communities were selected for a round of detailed mapping, focusing on collecting the location and information about every water point, health facility and other community resource in the area. In addition, we led technical skills trainings and mapping events both in Guéckédou and across the region. 

**ALL DATA EXCEPT FOR THE OpenStreetMap EXTRACTS ARE LICENSED AS CC-BY 4.0**

Tags: disease, geodata, west africa
Organization: American Red Cross (inactive)
2019 Tropical Cyclone Pawan Path

<p>This layer shows movement path of 2019 Tropical Cyclone Pawan in Somalia. A Tropical Storm initially named 06A formed in the northern Indian Ocean and later developed into a Tropical Cyclone named Pawan after sustaining wind speeds of more than 39mph (48kph) and heavy rain for two days. TC Pawan spread its clouds as far northwest as Oman and Yemen on its way to Somalia. It made landfall in Somalia on 7th December 2019 on the Coastal side of Puntland (Bossaso, Garowe). &nbsp;</p>

<p>The worst hit areas by 2019 TC Pawan included Nugaal Region (Eyl and Dangorayo Districts), Karkaar (Qardho District) and Bari Region (Alula, Iskushuban, and Baargaal Districts) who are under Garowe Somalia Red Crescent Society (SRCS) Branch) and the Coastal villages of Hafun, Iskushuban, Baargaal, Quandala and Alula Districts in Bari Region (under Bosasso SRCS Branch). Other areas affected include the coastal villages in Bari Region including Hafun, Iskushuban, Baargaal, Quandala and Alula districts.</p>
<p>Most affected households needed urgent humanitarian assistance as they were already living in dire conditions prior to the crisis. The destruction and flooding caused by TC Pawan increased the vulnerability of communities and heightened the impact of the ever -challenging climatic extremes.</p>
<p>The assessment estimated that 35,600 households, representing a population of 213,600 people had been affected. The assessment further estimated the affected population to represented 60-70% of the entire Bari and Nugaal Regions.</p>

Tags: geodata, hazards and risk
Organization: IGAD Climate Prediction and Applications Center (ICPAC)
Somalia Regions hit by 1992 Tropical Cyclone 12A

<p>In December 24, 1992 Tropical Cyclone 12A struck southern Bari region,bringing beneficial rainfall to the normally arid areas. This was the fourth cyclone in the Arabian Sea and the twelfth in the North Indian Ocean in 1992.</p>
<p>The tropical disturbance that became TC12A first formed in the Maldives near the equatorial trough.&nbsp;</p>

<p>The peak intensity reached by this cyclone was 50 kt (26 m/s) just prior to landfall. TC12A weakened rapidly after making landfall in Somalia, bringing much needed rain to a dry country. It dissipated over land. Bari region was the most affected region by this storm.</p>

Tags: geodata, hazards and risk
Organization: IGAD Climate Prediction and Applications Center (ICPAC)
Myanmar tentative UNESCO World Heritage Sites

Polygon dataset of all 15 properties considered to be cultural and/or natural heritage of outstanding universal value and submitted by Myanmar for inscription on the World Heritage List. Based on documents from https://whc.unesco.org/en/tentativelists. Approximate geolocation added by CDE Myanmar based on publicly available reference data and local knowledge.

Original dataset title: Myanmar tentative UNESCO World Heritage Sites (2020)

Tags: geodata, populated places-settlements
Organization: Myanmar Information Management Unit (MIMU)
Resumen mensual eventos y afectados por violencia armada en Colombia 2012-2018

Dataset con resumen mensual eventos y afectados por violencia armada en Colombia 2012-2018

Las categorías contenidas en los datasets son:
- Desplazamiento masivo* (eventos y afectados)
- Restricciones al acceso por violencia armada (eventos y afectados)
- Acciones armadas (eventos)
- Ataques contra población civil (eventos)

*Un desplazamiento se considera masivo si afecta a más de 50 personas o 10 familias

Información en línea sobre eventos de violencia armada en monitor.umaic.org
Más sobre nuestras categorías de Violencia armada en: https://wiki.umaic.org/wiki/Sistema_de_categor%C3%ADa_del_m%C3%B3dulo_de_eventos_de_violencia_armada

- - - - - - - - - - - - - - - -  - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 
Dataset with monthly totals on events and people affected by armed violence in Colombia 2012-2018

The categories contained in the datasets are:
- Mass* displacement (events and people affected - IDPs)
- Access restrictions caused by armed violence (events and people affected)
- Armed actions (events)
- Attacks against civilians (events)

Online information about events and people affected by armed violence (in Spanish) in monitor.umaic.org 
More about our categories on armed violence (in Spanish) in: https://wiki.umaic.org/wiki/Sistema_de_categor%C3%ADa_del_m%C3%B3dulo_de_eventos_de_violencia_armada

Tags: conflict-violence, humanitarian access, hxl, internally displaced persons-idp
Organization: OCHA Colombia
Non-authoritative zones of Myanmar inscribed UNESCO World Heritage Sites

Non-authoritative management zone polygon dataset of inscribed UNESCO World Heritage Sites in Myanmar (Bagan and Pyu Ancient Cities). Digitized in medium scale by CDE Myanmar based on georeferenced publicly available reference maps.

Original dataset title: Non-authoritative zones of Myanmar inscribed UNESCO World Heritage Sites (2020)

Tags: geodata
Organization: Myanmar Information Management Unit (MIMU)
#HXL core vocabulary list

Core dataset for resolving [#HXL](http://hxlstandard.org) "+v" attributes, first introduced in [release 1.1](http://hxlstandard.org/standard/1_1final/). To request new entries or changes to existing ones, please send a message to the [public #HXL mailing list](https://groups.google.com/forum/#!forum/hxlproject).

Tags: baseline population, hxl
Organization: Humanitarian Exchange Language (#HXL) (inactive)
Education Facilities of Myanmar

Education facilities: schools, kindergartens, colleges, and universities tagged via `amenity` or `building`. Useful for school-access mapping, education planning, and resource allocation.

Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge.

- Source: [OpenStreetMap](https://www.openstreetmap.org), a free, collaborative world map
- Tags: [amenity](https://wiki.openstreetmap.org/wiki/Key:amenity), [building](https://wiki.openstreetmap.org/wiki/Key:building)
- Part of the [exports grid on HDX](https://data.humdata.org/organization/hot/) by [HOT](https://www.hotosm.org/)


Tags: crisis-myanmar-earthquake, education facilities-schools, geodata
Organization: Humanitarian OpenStreetMap Team (HOT)
Cultural Places of Central African Republic

Cultural and historic places: museums, galleries, theatres, places of worship, monuments, and historic sites tagged via `tourism`, `amenity`, `historic`, or `heritage`. Useful for heritage protection, cultural mapping, and tourism context.

Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge.

- Source: [OpenStreetMap](https://www.openstreetmap.org), a free, collaborative world map
- Tags: [tourism](https://wiki.openstreetmap.org/wiki/Key:tourism), [amenity](https://wiki.openstreetmap.org/wiki/Key:amenity), [historic](https://wiki.openstreetmap.org/wiki/Key:historic), [heritage](https://wiki.openstreetmap.org/wiki/Key:heritage)
- Part of the [exports grid on HDX](https://data.humdata.org/organization/hot/) by [HOT](https://www.hotosm.org/)


Tags: facilities-infrastructure, geodata, points of interest-poi
Organization: Humanitarian OpenStreetMap Team (HOT)
Europe - VIIRS Active Fire Detections

Near-real-time active fire and thermal anomaly detections from NASA's [Fire Information for Resource Management System (FIRMS)](https://firms.modaps.eosdis.nasa.gov/active_fire/) covering **Europe**, derived from the **VIIRS** sensor family (Suomi-NPP since 2011, NOAA-20 since 2017, NOAA-21 since 2022).

Each resource is an external link directly to a NASA-hosted file. The files are continuously updated as new satellite overpasses are processed (typically within 3 hours of acquisition).

**Formats:** SHP, KML, CSV

**Time windows:** Last 24h, 48h, 7d


Tags: climate hazards, environment, geodata, hazards and risk, natural disasters
Organization: NASA Fire Information for Resource Management System
Roads of Afghanistan

Road network across the region tagged `highway=*`: motorways, residential streets, service roads, footways, and trails. Useful for routing, accessibility analysis, and evacuation planning.

Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge.

- Source: [OpenStreetMap](https://www.openstreetmap.org), a free, collaborative world map
- Tags: [highway](https://wiki.openstreetmap.org/wiki/Key:highway)
- Part of the [exports grid on HDX](https://data.humdata.org/organization/hot/) by [HOT](https://www.hotosm.org/)


Tags: geodata, roads, transportation
Organization: Humanitarian OpenStreetMap Team (HOT)
Populated Places of Mozambique

Settlements and residential areas: named cities, towns, villages, suburbs, and residential land (`place=*` and `landuse=residential`). Useful for demographic context, settlement-level targeting, and population analysis.

Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge.

- Source: [OpenStreetMap](https://www.openstreetmap.org), a free, collaborative world map
- Tags: [place](https://wiki.openstreetmap.org/wiki/Key:place), [landuse](https://wiki.openstreetmap.org/wiki/Key:landuse)
- Part of the [exports grid on HDX](https://data.humdata.org/organization/hot/) by [HOT](https://www.hotosm.org/)


Tags: geodata, populated places-settlements
Organization: Humanitarian OpenStreetMap Team (HOT)
Waterways of Mozambique

Water features across the region: rivers, streams, canals, lakes, ponds, and water bodies tagged with `waterway`, `water`, or `natural=water`. Useful for flood-risk modelling, watershed analysis, and environmental basemap context.

Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge.

- Source: [OpenStreetMap](https://www.openstreetmap.org), a free, collaborative world map
- Tags: [waterway](https://wiki.openstreetmap.org/wiki/Key:waterway), [water](https://wiki.openstreetmap.org/wiki/Key:water), [natural](https://wiki.openstreetmap.org/wiki/Key:natural)
- Part of the [exports grid on HDX](https://data.humdata.org/organization/hot/) by [HOT](https://www.hotosm.org/)


Tags: geodata, hydrology, rivers
Organization: Humanitarian OpenStreetMap Team (HOT)
Uganda- Nakapiripiti District: Operational Presence

This dataset contains Who, What, Where and When (4W) data for the district of Nakapiripiti in Uganda. The operational presence of the various organisations (who) by sector (what), location (where) at the province level and when the information was collected (when). 

Tags: hxl, operational partners, operational presence, who is doing what and where-3w-4w-5w
Organization: Fields Data
Mandalay Region Village Tract Boundaries MIMU v9.4

Polygons of Village Tract boundaries (Admin4) for the Mandalay Region, based on the latest MIMU Pcode version 9.4 . Place names from General Administration Department (GAD), are available in Myanmar Unicode. Transliteration in roman script by MIMU.

Place names are in line with the general cartographic practice to reflect the names of such places as designated by the host governments. The United Nations encourages authorities to review place names which include terms that may be viewed or perceived as derogatory.  

Tags: administrative boundaries-divisions, geodata
Organization: Myanmar Information Management Unit (MIMU)