AndreaBozzo/ceres-open-data-index huggingface dataset:
Industrial Zones, Special Economic Zones (SEZ) and Other Economic Development Areas in Myanmar (Point)

Dataset of approximate location of >100  industrial zones, Special Economic Zones (SEZ) and other economic development areas in Myanmar. Based on publicly available reference data and google satellite by CDE Myanmar and MIMU. Location data is non-authoritative and based on publicly available reference data and local knowledge.
Masterdata in excel and location shapefiles (point and polygon). ArcGIS tool to combine, filter and export a cleaned product for public sharing.
Known issues: 
- area/polygon data only available for approx. 50% of industrial/economic zones.
- location is non-authoritative as based on scan maps, google imagery and other reference data and maps and local knowledge.
- some zones might be sub-zones or parts of a larger zone.
- year of establishment and "official notified" area information only available for some zones (based on AungMinKudo2012_IZMyanmar.pdf) 
- Pyay Industrial Zone and Pathein Industrial SME Zone (listed in FMR 2019 report) not included in dataset as no location data available for those 2 IZs

Spatial dataset created based on reference maps of various scales matching with Google Satellite. ~ 1:25.000

Tags: geodata, populated places-settlements
Organization: Myanmar Information Management Unit (MIMU)
Power Plant Locations in Myanmar

Non-authoritative dataset of >100  approximate centre point locations of of power plants and other larger electricity generation facilities 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 facility along with a "best-guess" operational status as of 2025, based on satellite imagery analysis and publicly available online sources.

Creation methodology:
- Identifying power generation 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 facility
- operational status was assessed based on satellite imagery, considering visible signs of ongoing construction, complete decommissioning, or disuse
- assigning power generation source and max. capacity (in MW) 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 facility name, based on google maps, MOEP, OSM and other publicly available data.
- creating a public dataset by excluding planned and non-confirmed power facility locations and by reducing the attribute table to a selection of cleaned and relevant fields.

Known issues: 
- power generation facility names are unofficial and non-authoritative; Myanmar-language names are still missing.
- some power plants present in reference lists (MOEP, Myanmar project bank, SEA 2018, ...) are only in planning stage, have been decomissions or canceled. Locations for those were not identified. 
- The matching of power generation 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 power generation facilities no names are known or are highly uncertain. Those names are places in square backets "[]"
- many smaller solar plants or solar mini-grids are included in this dataset (as visible in imagery) while mini-grid diesel generators, micro-hydro and other power generation facilities with similar capacity are not included (as not easily identifiable in imagery)

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

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

Sea ports and ferry terminals tagged via `amenity`, `building`, or `port`. Useful for maritime logistics, supply-chain analysis, and coastal access 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: [amenity](https://wiki.openstreetmap.org/wiki/Key:amenity), [building](https://wiki.openstreetmap.org/wiki/Key:building), [port](https://wiki.openstreetmap.org/wiki/Key:port)
- Part of the [exports grid on HDX](https://data.humdata.org/organization/hot/) by [HOT](https://www.hotosm.org/)


Tags: facilities-infrastructure, geodata, ports
Organization: Humanitarian OpenStreetMap Team (HOT)
Health Facilities of Ethiopia

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: geodata, health, health facilities
Organization: Humanitarian OpenStreetMap Team (HOT)
South 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 **South 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
Waterways of Central African Republic

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)
Financial Services of Afghanistan

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)
Southern Africa - 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 **Southern Africa**, 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
Populated Places of Haiti

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 Myanmar

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)
Roads of Myanmar

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: crisis-myanmar-earthquake, geodata, roads, transportation
Organization: Humanitarian OpenStreetMap Team (HOT)
Education Facilities of Lebanon

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-greater-middle-east, education facilities-schools, geodata
Organization: Humanitarian OpenStreetMap Team (HOT)
Airports of Lebanon

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, crisis-greater-middle-east, facilities-infrastructure, geodata
Organization: Humanitarian OpenStreetMap Team (HOT)
Sea Ports of Mali

Sea ports and ferry terminals tagged via `amenity`, `building`, or `port`. Useful for maritime logistics, supply-chain analysis, and coastal access 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: [amenity](https://wiki.openstreetmap.org/wiki/Key:amenity), [building](https://wiki.openstreetmap.org/wiki/Key:building), [port](https://wiki.openstreetmap.org/wiki/Key:port)
- Part of the [exports grid on HDX](https://data.humdata.org/organization/hot/) by [HOT](https://www.hotosm.org/)


Tags: facilities-infrastructure, geodata, ports
Organization: Humanitarian OpenStreetMap Team (HOT)
Waterways of Ethiopia

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)
South America - 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 **South America**, 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
Points of Interest of Madagascar

Points of interest: public-facing amenities, shops, tourist attractions, and landmarks tagged via `amenity`, `shop`, `tourism`, or `man_made`. Useful for general POI reference, urban analysis, and basemap detail.

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), [shop](https://wiki.openstreetmap.org/wiki/Key:shop), [tourism](https://wiki.openstreetmap.org/wiki/Key:tourism), [man_made](https://wiki.openstreetmap.org/wiki/Key:man_made)
- 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)
Buildings of Kenya

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)
HDX HAPI Data for Zimbabwe

This dataset contains data obtained from the
[HDX Humanitarian API](https://hapi.humdata.org/) (HDX HAPI),
which provides standardized humanitarian indicators designed
for seamless interoperability from multiple sources.
The data facilitates automated workflows and visualizations
to support humanitarian decision making.
For more information, please see the HDX HAPI
[landing page](https://data.humdata.org/hapi)
and
[documentation](https://hdx-hapi.readthedocs.io/en/latest/).


Tags: baseline population, climate-weather, conflict-violence, displacement, economics, education, food security, funding, hazards and risk, health, indicators, internally displaced persons-idp, markets, migration, poverty, refugees, returnees
Organization: HDX Humanitarian API Data
HDX HAPI Data for Zambia

This dataset contains data obtained from the
[HDX Humanitarian API](https://hapi.humdata.org/) (HDX HAPI),
which provides standardized humanitarian indicators designed
for seamless interoperability from multiple sources.
The data facilitates automated workflows and visualizations
to support humanitarian decision making.
For more information, please see the HDX HAPI
[landing page](https://data.humdata.org/hapi)
and
[documentation](https://hdx-hapi.readthedocs.io/en/latest/).


Tags: baseline population, climate-weather, conflict-violence, displacement, economics, education, food security, funding, hazards and risk, health, indicators, internally displaced persons-idp, markets, migration, poverty, refugees, returnees
Organization: HDX Humanitarian API Data
HDX HAPI Data for South Africa

This dataset contains data obtained from the
[HDX Humanitarian API](https://hapi.humdata.org/) (HDX HAPI),
which provides standardized humanitarian indicators designed
for seamless interoperability from multiple sources.
The data facilitates automated workflows and visualizations
to support humanitarian decision making.
For more information, please see the HDX HAPI
[landing page](https://data.humdata.org/hapi)
and
[documentation](https://hdx-hapi.readthedocs.io/en/latest/).


Tags: baseline population, climate-weather, conflict-violence, displacement, economics, education, food security, hazards and risk, health, indicators, internally displaced persons-idp, markets, migration, poverty, refugees, returnees
Organization: HDX Humanitarian API Data
HDX HAPI Data for Yemen

This dataset contains data obtained from the
[HDX Humanitarian API](https://hapi.humdata.org/) (HDX HAPI),
which provides standardized humanitarian indicators designed
for seamless interoperability from multiple sources.
The data facilitates automated workflows and visualizations
to support humanitarian decision making.
For more information, please see the HDX HAPI
[landing page](https://data.humdata.org/hapi)
and
[documentation](https://hdx-hapi.readthedocs.io/en/latest/).


Tags: climate-weather, conflict-violence, displacement, economics, education, food security, funding, hazards and risk, health, humanitarian needs overview-hno, indicators, internally displaced persons-idp, markets, migration, operational presence, people in need-pin, poverty, refugees, returnees, who is doing what and where-3w-4w-5w
Organization: HDX Humanitarian API Data
HDX HAPI Data for Samoa

This dataset contains data obtained from the
[HDX Humanitarian API](https://hapi.humdata.org/) (HDX HAPI),
which provides standardized humanitarian indicators designed
for seamless interoperability from multiple sources.
The data facilitates automated workflows and visualizations
to support humanitarian decision making.
For more information, please see the HDX HAPI
[landing page](https://data.humdata.org/hapi)
and
[documentation](https://hdx-hapi.readthedocs.io/en/latest/).


Tags: conflict-violence, education, hazards and risk, health, indicators, poverty, refugees
Organization: HDX Humanitarian API Data
HDX HAPI Data for Wallis and Futuna Islands

This dataset contains data obtained from the
[HDX Humanitarian API](https://hapi.humdata.org/) (HDX HAPI),
which provides standardized humanitarian indicators designed
for seamless interoperability from multiple sources.
The data facilitates automated workflows and visualizations
to support humanitarian decision making.
For more information, please see the HDX HAPI
[landing page](https://data.humdata.org/hapi)
and
[documentation](https://hdx-hapi.readthedocs.io/en/latest/).


Tags: conflict-violence, indicators
Organization: HDX Humanitarian API Data
HDX HAPI Data for Vanuatu

This dataset contains data obtained from the
[HDX Humanitarian API](https://hapi.humdata.org/) (HDX HAPI),
which provides standardized humanitarian indicators designed
for seamless interoperability from multiple sources.
The data facilitates automated workflows and visualizations
to support humanitarian decision making.
For more information, please see the HDX HAPI
[landing page](https://data.humdata.org/hapi)
and
[documentation](https://hdx-hapi.readthedocs.io/en/latest/).


Tags: baseline population, climate-weather, conflict-violence, displacement, education, funding, hazards and risk, health, indicators, internally displaced persons-idp, migration, poverty, refugees
Organization: HDX Humanitarian API Data
HDX HAPI Data for Viet Nam

This dataset contains data obtained from the
[HDX Humanitarian API](https://hapi.humdata.org/) (HDX HAPI),
which provides standardized humanitarian indicators designed
for seamless interoperability from multiple sources.
The data facilitates automated workflows and visualizations
to support humanitarian decision making.
For more information, please see the HDX HAPI
[landing page](https://data.humdata.org/hapi)
and
[documentation](https://hdx-hapi.readthedocs.io/en/latest/).


Tags: baseline population, climate-weather, conflict-violence, economics, education, food security, funding, hazards and risk, health, indicators, markets, poverty, refugees, returnees
Organization: HDX Humanitarian API Data