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            <Abstract>Non-authoritative dataset of &gt;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.
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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 &quot;power facility code&quot; 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 &quot;best guess&quot; 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 &quot;[]&quot;</Abstract>
            
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The attribute data includes the non-authoritative English name of each dam along with a &quot;best-guess&quot; operational status as of 2025, based on satellite imagery analysis and publicly available online sources.

Creation methodology:
- Identifying hydropower plants based on https://www.moep.gov.mm/en/ignite/page/641, OpenStreetMap and high resolution satellite imagery.
- Manually identifying the dam, weir or water intake location for each hydropower plant and crosschecking with the Worldbank 2018 &quot;Strategic Environmental Assessment of the Myanmar Hydropower Sector Report Dataset&quot; and setting the location point at the approximate centre of the dam crest or water intake.
- assigning a &quot;power facility code&quot; to each dam
- assessing the operational status of the dam based on the imagery (dam water level, visible signs of ongoing construcction activity, ...)
- assigning a non-authoritative dam name, based on either SEA, google maps, MOEP and other publicly available data.
- creating a public dataset by excluding planned and non-confirmed dam locations and by reducing the attribute table to a selection of cleaned and relevant fields.

Known issues: 
- Dam names are unofficial and non-authoritative; Myanmar-language names are still missing.
- In the case of reservoirs with multiple dams, only the largest or most visually prominent dam has been marked as a point.
- For weirs and water intakes not directly associated with a visible dam structure, the chosen point location may be inaccurate, as their exact positions are often difficult to determine from satellite imagery.
- Additional dam and reservoir attributes are not included in this public dataset due to the unreliability and incompleteness of the available reference sources.
- The dataset includes a few facilities that may only qualify as micro-hydro dams or smaller weirs. In the absence of a verified master list of hydropower dams and generating stations, these entries were retained to allow users to assess their relevance and decide whether to include or exclude them in their analysis.</Abstract>
            
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            <Title>Power Plant Locations in Myanmar</Title>
            <Abstract>Non-authoritative dataset of &gt;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 &quot;best-guess&quot; 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 &quot;power facility code&quot; 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 &quot;best guess&quot; 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 &quot;[]&quot;
- 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)</Abstract>
            
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            <Title>Sluice Gates in Myanmar</Title>
            <Abstract>Non-authoritative dataset of &gt;300  sluice gates (with geographic coordiates for 274 sluice gates) in Myanmar.
A sluice gate is a water control structure used to regulate the flow of water in rivers, canals, and irrigation systems. In agricultural settings, especially for large areas, sluice gates are vital for managing water levels, preventing flooding, and ensuring adequate irrigation. They are typically adjustable, allowing farmers to control water flow, direct it to fields, or block it to prevent water damage during storms or heavy rains. For Myanmar, esp. in the low lying delta areas installed, sluice gates are essential to protect farmland from flooding.
Dataset produced by CDE Myanmar based on publicly available reference date (esp. GAD Township profiles 2019 and IWUMD website), enhanced with local knowledge and determining geographic coordinates using mostly large scale satellite/google satellite. 
Attribute data available for most sluice dates include 
- the river/stream name the sluice gate provides protection from
- the size of the gate
- the construction material
- the construcction period (year of start &amp; completion)
- the size of the protected area
- Township name

Creation methodology:
- create excel masterlist from GAD and IWUMD, incl. attributes and assign unique code.
- based on the reference data location maps and textual location information, identification of sluice gate cooridinates on Google/Bing imagery.
- addition of sluice gate data based on local knowledge
- cleanup of data, standardization of attributes and correcting typos

Known issues: 
- dataset may be out of date (GAD township profiles from 2019, IWUMD data from 2023)
- for 65 (out of 339 known sluice gates) no geographic coordinates could be determined
- for 42 sluice gates, the geographic coordinates are &quot;best-guess&quot;, meaning that there is a possibility that the reference data from GAD/IWUMD and the sluice gate identified in google/bing imagery may not indicate the same sluice gate
- reference data from GAD and IWUMD may be incomplete, thus leading to missing sluice gates in this dataset
- for some sluice gates, attribute data is missing or incomplete
- some sluice gates may be non-functional or destroyed</Abstract>
            
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