Myanmar GIS data

satellite imagery by Maxar, acquired 2025-03-31 to 2025-03-31, 32.9 cm per pixel, published on OpenAerialMap.

satellite imagery by Maxar, acquired 2025-03-30 to 2025-03-30, 33.0 cm per pixel, published on OpenAerialMap.

satellite imagery by Maxar, acquired 2025-03-31 to 2025-03-31, 33.0 cm per pixel, published on OpenAerialMap.

satellite imagery by Maxar, acquired 2025-03-30 to 2025-03-30, 32.9 cm per pixel, published on OpenAerialMap.

satellite imagery by Maxar, acquired 2025-04-03 to 2025-04-03, 32.9 cm per pixel, published on OpenAerialMap.

satellite imagery by Maxar, acquired 2025-04-03 to 2025-04-03, 32.7 cm per pixel, published on OpenAerialMap.

geoBoundaries ADM1 boundaries for Myanmar: 14 units, representing 2019. Source: Myanmar Analytics Project, geoBoundaries.

Open and free data for assessing the human presence on the planet. The Global Human Settlement Layer (GHSL) project produces global spatial information, evidence-based analytics, and knowledge describing the human presence on the planet. The GHSL relies on the design and implementation of spatial data processing technologies that allow automatic data analytics and information extraction from large amounts of heterogeneous geospatial data including global, fine-scale satellite image data streams, census data, and crowd sourced or volunteered geographic information sources. The JRC, together with the Directorate-General for Regional and Urban Policy (DG REGIO) and Directorate-General for Defence Industry and Space (DG DEFIS) are working towards a regular and operational monitoring of global built-up and population based on the processing of Sentinel Earth Observation data produced by European Copernicus space program. In addition, the EU Agency for the Space Programme (EUSPA) undertakes activities related to user uptake of data, information and services.

MapSwipe results focusing on areas with at least one building. This data is collected through the MapSwipe platform, whereby humans visually check for the presence of buildings using satellite imagery (Esri World Imagery for Myanmar). It combines results from several MapSwipe projects listed below. In the download files below the 'results_yes_maybe' are the results and the original input areas are 'aois'. Source MapSwipe Projects - Myanmar: Find - Buildings - Earthquake Response (2) - Myanmar: Find - Buildings - Earthquake Response (3) - Myanmar: Find - Buildings - Earthquake Response (4) - Myanmar: Find - Buildings - Earthquake Response (5) - Myanmar: Find - Buildings - Earthquake Response (6) - Myanmar: Find - Buildings - Earthquake Response (7) - Myanmar: Find - Buildings - Earthquake Response (8)

The Gender Equality Monitoring (GEM) platform offers open access to officially published data and periodically updated sex disaggregated data repository. It visualizes gender gaps at subnational level in various sectors such as education, health, employment, access to information, intra-household decision making, political participation, as well as gender inequality index (GII). These are starting points to further explore the causes and more complex dynamics of gender inequality. For more information, visit the ADPC Gender Equality Monitor.

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 is an open license, standardized resource of boundaries (i.e., state, county) for every country in the world.

Humanitarian OpenStreetMap Team (HOT) conducted a pilot of Crowdsourced Damage Assessment (CDA) with local mappers from the Myanmar OpenStreetMap Community (myOSM) to identify and map damaged buildings in priority affected townships from the March 2025 Myanmar earthquake. Through the CDA, mappers will review damaged buildings by comparing pre- and post-disaster satellite imageries (from Maxar and Planet) to identify signs of damages. These were reviewed, mapped, and validated with open-source tools MapSwipe, HOT Tasking Manager, and MapRoulette. Damage assessments were conducted in 20 townships, including: Bago, Magway, Aungmyaythazan, Chanayethazan, Mahaaungmyay, Chanmyathazi, Pyigyitagon, Amarapura, Sintgaing, Kyaukse, Meiktila, Thazi, Patheingyi, Za Bu Thi Ri, Det Khi Na Thi Ri, Pyinmana, Poke Ba Thi Ri, Oke Ta Ra Thi Ri, Lewe, and Sagaing. This dataset includes all OpenStreetMap features (nodes, ways, and relations) within Myanmar that contain any tag key related to “damage”.) Features may have these attributes: - name - building - damage - damage:event - source:damage - source:damage:date - addr:street - addr:city - source This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

**ADAM ID: **FL-20250729-MMR-00 A flood occurred on Jul 29 2025 in Myanmar. It affected an estimated 891547 people and 500878 ha of cropland. WFP’s Automated Disaster Analysis and Mapping (ADAM) system is an operational system for collecting, analysing and mapping geospatial and socio-economic information following sudden onset humanitarian emergencies.

**ADAM ID: **FL-20250605-MMR-01 A flood occurred on Jun 05 2025 in Myanmar. It affected an estimated 224615 people and 158413 ha of cropland. WFP’s Automated Disaster Analysis and Mapping (ADAM) system is an operational system for collecting, analysing and mapping geospatial and socio-economic information following sudden onset humanitarian emergencies.

Myanmar administrative level 0-5 boundaries (COD-AB) dataset version 01. This dataset is structured into 5 levels: - Admin 1: 18 State/Region - Admin 2: 80 District - Admin 3: 330 Township - Admin 4: 14174 Town / Village tract, partial coverage - Admin 5: 1999 , partial coverage Dates associated with this dataset: - 30 October 2025: dataset reviewed for accuracy and completeness - 15 February 2024: valid for use by the humanitarian community - 11 March 2024: last edit to the dataset before publishing - 11 March 2024: boundaries created by the source Quality assured, configured, and published by OCHA Field Information Services (FIS) and HDX. Part of the dataset: Global Subnational Administrative Boundaries

This dataset shows the list of operating health facilities. Attributes included: Name,Nature of Facility, Activities, Lat, Long

# EOS-RS Flood Proxy Map: Laymyethna, Myanmar, Floods , 08 August 2026, v0.9 The Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS) created this preliminary Flood Proxy Map (FPM) depicting areas that are likely flooded in Laymyethna, Myanmar after the Ngawun River burst through an embankment on 30 July 2026. This map was derived from synthetic aperture radar (SAR) images acquired by the Copernicus Sentinel-1 satellite operated by the European Space Agency (ESA) before (13 Dec 2025 to 24 July 2026) and during (05 August 2026) the event. The map covers an area indicated by the white polygon. The preliminary map shows areas which are likely flooded (shown by light blue pixels of approximately 30m in size) due to the heavy rainfall. Preliminary validation was conducted using news reports and ground-level imagery in selected areas. This map should be used as a guide to identify areas that are likely flooded, and may be less reliable over urban and vegetated areas. This product contains modified Copernicus Sentinel data (2025-2026), processed by ESA and analyzed by the Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS). **More map details and files:** **Legal Disclaimer:** **Credits:** Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS), Contains modified Copernicus Sentinel data (2025-2026)

# Myanmar Earthquakes: Damage Proxy Maps, Interferograms and Pixel Offset Maps, Mar 2025 The **Earth Observatory of Singapore – Remote Sensing Lab (EOS-RS)** produced these damage proxy maps, interferograms and pixel offset maps for Myanmar Earthquakes (Mar 2025) from synthetic aperture radar (SAR) satellite images. Each map is a separate ZIP below with its GeoTIFF, a KMZ for Google Earth, the PNG figures and a text file describing how it was made and how to read it. ## Maps in this dataset - **EOS-RS Damage Proxy Map: Naypyidaw Vicinity, Myanmar, Earthquakes, 05 Apr 2025, v0.9 ** (superseded) - **EOS-RS Damage Proxy Map: Myanmar, Earthquakes, 5 Apr 2025, v0.9 ** - **EOS-RS Damage Proxy Map: Myanmar, Earthquakes, 3 Apr 2025, v0.9 ** - **EOS-RS Damage Proxy Map: Myanmar, Earthquakes, 3 Apr 2025, v0.5 ** (superseded) - **EOS-RS Damage Proxy Map: Naypyidaw Vicinity, Myanmar, Earthquakes, 31 Mar 2025, v0.9 ** - **EOS-RS Pixel Offset Map (Sentinel-2 Data): Myanmar, Earthquakes, Pre-Event: 2025/03/25-27 NORTHING** - **EOS-RS Interferogram (Unwrapped): Myanmar, Earthquakes, 2025/02/16-2025/03/30, v0.1** - **EOS-RS Interferogram (Wrapped): Myanmar, Earthquakes, 2025/02/16-2025/03/30, v0.1** **More map details and files:** **More map details and files:** **Legal Disclaimer:** **Credits:** Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS), Contains modified Copernicus Sentinel data (2024-2025)

# EOS-RS Flood Proxy Map: Myanmar, Floods, 16 Sep 2024, v0.5 The Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS) created this preliminary Flood Proxy Map (FPM) depicting areas that are likely flooded in Myanmar due to heavy rainfall from Typhoon Yagi. This map was derived from synthetic aperture radar (SAR) images acquired by the Copernicus Sentinel-1 satellite operated by the European Space Agency (ESA) before (4 Sep 2024) and after (16 Sep 2024) the event. The map covers an area indicated by the white polygon. The preliminary map shows areas which are likely flooded (shown by light blue pixels of approximately 30m in size) in Myanmar due to heavy rainfall. Preliminary validation was conducted using news reports, aerial optical images, and ground-level images of flooding in selected areas. This map should be used as a guide to identify areas that are likely flooded, and may be less reliable over urban and vegetated areas. This product contains modified Copernicus Sentinel data (2024), processed by ESA and analyzed by the Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS). **More map details and files:** **More map details and files:** **Legal Disclaimer:** **Credits:** Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS), Contains modified Copernicus Sentinel data (2024)

# EOS-RS Flood Proxy Map: Myanmar, Floods, 8 July 2024, v0.4 The Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS) created this preliminary Flood Proxy Map (FPM) depicting areas that are likely flooded in Myitkyina, Myanmar due to heavy rainfall. This map was derived from synthetic aperture radar (SAR) images acquired by the Copernicus Sentinel-1 satellite operated by the European Space Agency (ESA) before (26 Jun 2024) and after (7 Jul 2024) the event. The map covers an area indicated by the white polygon. The preliminary map shows areas which are likely flooded (shown by light blue pixels of approximately 30m in size) in Myitkyina, Myanmar due to heavy rainfall. Preliminary validation was conducted using news reports of flooding in selected areas of Myitkyina. This map should be used as a guide to identify areas that are likely flooded, and is less reliable over urban and vegetated areas. The product contains modified Copernicus Sentinel data (2024), processed by ESA and analyzed by the Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS). Data processing used an AWS Open Dataset of Copernicus Sentinel-1 data for the Asia region (https://registry.opendata.aws/sentinel1-slc-seasia-pds). **More map details and files:** **More map details and files:** **Legal Disclaimer:** **Credits:** Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS), Contains modified Copernicus Sentinel data (2024)

# Myanmar Cyclone Mocha: Damage and Flood Proxy Maps, May 2023 The **Earth Observatory of Singapore – Remote Sensing Lab (EOS-RS)** produced these damage and flood proxy maps for Myanmar Cyclone Mocha (May 2023) from synthetic aperture radar (SAR) satellite images. Each map is a separate ZIP below with its GeoTIFF, a KMZ for Google Earth, the PNG figures and a text file describing how it was made and how to read it. ## Maps in this dataset - **EOS-RS Damage Proxy Map: Myanmar, Cyclone Mocha, 18 May 2023, v0.9** - **EOS-RS Damage Proxy Map: Myanmar, Cyclone Mocha, 18 May 2023, v0.9** - **EOS-RS Flood Proxy Map: Myanmar, Cyclone Mocha, 14 May 2023, v0.4** - **EOS-RS Flood Proxy Map: Myanmar, Cyclone Mocha, 14 May 2023, v0.3** (superseded) **More map details and files:** **More map details and files:** **Credits:** Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS), Advanced Rapid Imaging and Analysis (ARIA), NASA-JPL/Caltech, Contains modified Copernicus Sentinel data (2023)

# Myanmar Floods: Flood Proxy Maps, Aug 2019 The Advanced Rapid Imaging and Analysis (ARIA) team at NASA's Jet Propulsion Laboratory and Caltech, in collaboration with the Earth Observatory of Singapore (EOS), produced these flood proxy maps for Myanmar Floods (Aug 2019) from synthetic aperture radar (SAR) satellite images. Each map is a separate ZIP below with its GeoTIFF, a KMZ for Google Earth, the PNG figures and a text file describing how it was made and how to read it. ## Maps in this dataset - **ARIA-SG Flood Proxy Map: Myanmar, 2019 Floods v2.0 ** - **ARIA-SG Flood Proxy Map: Myanmar, 2019 Floods v1.0 ** **More map details and files:**

This dataset contains annual, 100m-resolution above ground biomass (AGB) estimates from CTrees, a NASA-affiliated forest-carbon monitoring organization, clipped to this country's boundary from CTrees' global AGB raster. Pixel values are stored as int16, scaled x10 relative to the true value in megagrams per hectare (Mg/ha) -- divide by 10 to get Mg/ha. See the caveats field and resource description for details on how this scale factor is recorded and why it isn't applied automatically by most tools.

# Myanmar Flood Dawei: Damage and Flood Proxy Maps, Oct 2026 The **Earth Observatory of Singapore – Remote Sensing Lab (EOS-RS)** produced these damage and flood proxy maps for Myanmar Flood Dawei (Oct 2026) from synthetic aperture radar (SAR) satellite images. Each map is a separate ZIP below with its GeoTIFF, a KMZ for Google Earth, the PNG figures and a text file describing how it was made and how to read it. ## Maps in this dataset - **EOS-RS Damage Proxy Map: Dawei, Myanmar, Landslide, 04 October 2026, v0.8 ** - **EOS-RS Flood Proxy Map: Dawei, Myanmar, Floods, 04 October 2026, v0.8** **More map details and files:** **Legal Disclaimer:** **Credits:** Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS), Contains modified Copernicus Sentinel data (2026)

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, a free, collaborative world map - Tags: aeroway, building, emergency - Part of the country exports on HDX by HOT

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, a free, collaborative world map - Tags: tourism, amenity, historic, heritage - Part of the country exports on HDX by HOT

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, a free, collaborative world map - Tags: amenity - Part of the country exports on HDX by HOT

Water features across the area: 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, a free, collaborative world map - Tags: waterway, water, natural - Part of the country exports on HDX by HOT

Road network across the area 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, a free, collaborative world map - Tags: highway - Part of the country exports on HDX by HOT

Building footprints across the area: 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, a free, collaborative world map - Tags: building - Part of the country exports on HDX by HOT

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, a free, collaborative world map - Tags: amenity, building - Part of the country exports on HDX by HOT

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, a free, collaborative world map - Tags: amenity, shop, tourism, man_made - Part of the country exports on HDX by HOT

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, a free, collaborative world map - Tags: place, landuse - Part of the country exports on HDX by HOT

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, a free, collaborative world map - Tags: railway - Part of the country exports on HDX by HOT

Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) is a biophysical dimensionless quantity (its values range from 0/no absorption to 1/total absorption) used to assess the greenness and health of vegetation. FAPAR anomalies can be used as an indicator to detect and monitor the impacts of agricultural drought on the growth and productivity of vegetation. The data is presented in 10-day time composite of the Visible Infrared Imaging Radiometer Suite (VIIRS).

GLIDEnumbers are GLobal unique IDEntifiers for Disasters. Each disaster is registered in a record that contains a GLIDEnumber that uniquely identifies it and allows information to be interoperable across multiple disaster information sources, both structured and textual. Accessing disaster information can be a time consuming and laborious task. Not only is data scattered but frequently identification of the disaster can be confusing in countries with many disaster events and across borders. To address both of these issues, Asian Disaster Reduction Center (ADRC) proposed a globally common Unique ID code for disasters. Among the institutions using actively GLIDEnumbers are UN-OCHA (ReliefWeb, FSCC, HDX), UNDRR, UNDP, WMO, IFRC, FAO, the European Commission and the Centre for Research on the Epidemiology of Disasters (CRED), among many others. Country datasets are only produced for countries with at least one GLIDE event since 1 January 2022. The global dataset contains all events available from the GLIDE API, including those not assigned to a country.