Distributed Renewable Energy (DRE) Atlas: Settlements

Name: Distributed Renewable Energy (DRE) Atlas: Settlements
Creator: VIDA

Data powering the DRE Atlas Planning Platform - https://dre.energydata.info

Explore comprehensive datasets on communities across 58 countries from Sub-Saharan Africa, Asia & the Pacific, and Latin America & the Caribbean to enable informed investment decisions.

Product Details

Visibility: Public
Owner: VIDA
Created: 30 Apr 2026
Last Updated: 16 Jul 2026

Product Contents

root

Product Details

Product Contents

Distributed Renewable Energy (DRE) Atlas: Settlements

Data powering the DRE Atlas Planning Platform - https://dre.energydata.info

Explore comprehensive datasets on communities across 58 countries from Sub-Saharan Africa, Asia & the Pacific, and Latin America & the Caribbean to enable informed investment decisions.

Product Details

Visibility: Public
Owner: VIDA
Created: 30 Apr 2026
Last Updated: 16 Jul 2026

Product Contents

root

README

Distributed Renewable Energy (DRE) Atlas: Settlements

This repository hosts the underlying data for the DRE Atlas Planning Platform, hosted on energydata.info — produced by VIDA, commissioned and funded by the Energy Sector Management Assistance Program (ESMAP), the World Bank, and the International Finance Corporation (IFC).

Settlement-level data for distributed renewable energy (DRE) planning, covering over 1.9 million settlements across 58 countries in Sub-Saharan Africa, Asia, the Pacific, and the Americas.

Interactive platform: dre.energydata.info — User guide
Technical documentation: DRE Atlas Technical Documentation (PDF)

Countries covered

Region	Countries
Sub-Saharan Africa	Angola, Benin, Botswana, Burkina Faso, Burundi, Cameroon, Central African Republic, Chad, Comoros, Congo, Democratic Republic of the Congo, Djibouti, Equatorial Guinea, Eritrea, Eswatini, Ethiopia, Gabon, Gambia, Ghana, Guinea, Guinea-Bissau, Ivory Coast, Kenya, Lesotho, Liberia, Madagascar, Malawi, Mali, Mauritania, Mozambique, Namibia, Niger, Nigeria, Rwanda, São Tomé and Príncipe, Senegal, Sierra Leone, Somalia, South Africa, South Sudan, Sudan, Tanzania, Togo, Uganda, Zambia, Zimbabwe
Asia	Bangladesh, Cambodia, Myanmar, Pakistan
Pacific	Micronesia, Papua New Guinea, Solomon Islands, Timor-Leste, Vanuatu
Americas	Haiti, Honduras, Nicaragua

What's in this dataset

Every settlement in the dataset is a mapped population cluster identified using DBSCAN clustering on Google-Microsoft-OSM Open Buildings - combined by VIDA. Each settlement carries 50+ attributes covering:

Theme group	Covers
General settlement statistics	Boundary polygon, area, admin names (CGAZ boundaries), building counts by size class, distance to water, estimated population
Energy demand	Estimated connections, energy demand
Energy access	Nightlight coverage, grid distances (MV/HV lines, substations, mini-grids), solar potential
Accessibility	Road access, distance to regional hubs
Socio-economic indicators	Healthcare and education facilities, Meta Relative Wealth Index
Regional agriculture	Crop types, area, value and yield by admin subdivision (MapSPAM)
Security	Armed conflict fatalities and incidents by distance (ACLED)

Schema varies by country. Full field definitions in the DRE Atlas Technical Documentation (PDF) and the data dictionary.

STAC Collection

A STAC collection with per-country items is available at collection.json, and can be browsed interactively through STAC Browser.

Each item includes HTTPS and S3 asset URLs, bounding box, and settlement count. Per-country energy analytics (total connections, total energy demand, demand per connection) are exposed as dre: item properties.

File formats

GeoParquet

Per-country GeoParquet 1.1.0 files under by_country/country_iso=<ISO>/, following GeoParquet distribution best practices.

Given that schema varies by country, use schema merging when reading multiple countries together (e.g. union_by_name=true in DuckDB, schema=pa.unify_schemas(...) in PyArrow).

PMTiles

Per-country PMTiles under by_country/country_iso=<ISO>/.

A combined PMTiles file covering all 58 countries is available at dre_atlas.pmtiles. All layers are unified under the name dre_atlas.

CSV and GeoJSON

Traditional formats (CSV, GeoJSON) are available for download on energydata.info.

How to use

PMTiles — browser visualization

PMTiles enables scalable, serverless map visualization directly in the browser.

Combined PMTiles location: https://data.source.coop/vida/dre-atlas/dre_atlas.pmtiles

For QGIS and MapLibre, use the pmtiles:// prefix:

pmtiles://https://data.source.coop/vida/dre-atlas/dre_atlas.pmtiles

DuckDB — single country (HTTPS, no setup needed)

DuckDB — multi-country queries (S3 endpoint required for glob patterns)

Settlement counts by country

Unelectrified settlements with high demand

Adding a country_iso filter triggers Hive partition pruning — DuckDB reads only the matching files.

License

Creative Commons Attribution 4.0 International (CC BY 4.0)

You are free to share and adapt this data for any purpose, provided you give appropriate credit.

Contact

Malin Fischer, VIDA.place GmbH — malin@vida.place
Jessica La Costa, VIDA.place GmbH — jess@vida.place
Giorgio Basile, VIDA.place GmbH — giorgio@vida.place
Benjamin P. Stewart, World Bank Group — bstewart@worldbankgroup.org

README

Distributed Renewable Energy (DRE) Atlas: Settlements

Settlement-level data for distributed renewable energy (DRE) planning, covering over 1.9 million settlements across 58 countries in Sub-Saharan Africa, Asia, the Pacific, and the Americas.

Interactive platform: dre.energydata.info — User guide
Technical documentation: DRE Atlas Technical Documentation (PDF)

Countries covered

Region	Countries
Sub-Saharan Africa	Angola, Benin, Botswana, Burkina Faso, Burundi, Cameroon, Central African Republic, Chad, Comoros, Congo, Democratic Republic of the Congo, Djibouti, Equatorial Guinea, Eritrea, Eswatini, Ethiopia, Gabon, Gambia, Ghana, Guinea, Guinea-Bissau, Ivory Coast, Kenya, Lesotho, Liberia, Madagascar, Malawi, Mali, Mauritania, Mozambique, Namibia, Niger, Nigeria, Rwanda, São Tomé and Príncipe, Senegal, Sierra Leone, Somalia, South Africa, South Sudan, Sudan, Tanzania, Togo, Uganda, Zambia, Zimbabwe
Asia	Bangladesh, Cambodia, Myanmar, Pakistan
Pacific	Micronesia, Papua New Guinea, Solomon Islands, Timor-Leste, Vanuatu
Americas	Haiti, Honduras, Nicaragua

What's in this dataset

Theme group	Covers
General settlement statistics	Boundary polygon, area, admin names (CGAZ boundaries), building counts by size class, distance to water, estimated population
Energy demand	Estimated connections, energy demand
Energy access	Nightlight coverage, grid distances (MV/HV lines, substations, mini-grids), solar potential
Accessibility	Road access, distance to regional hubs
Socio-economic indicators	Healthcare and education facilities, Meta Relative Wealth Index
Regional agriculture	Crop types, area, value and yield by admin subdivision (MapSPAM)
Security	Armed conflict fatalities and incidents by distance (ACLED)

Schema varies by country. Full field definitions in the DRE Atlas Technical Documentation (PDF) and the data dictionary.

STAC Collection

A STAC collection with per-country items is available at collection.json, and can be browsed interactively through STAC Browser.

File formats

GeoParquet

Per-country GeoParquet 1.1.0 files under by_country/country_iso=<ISO>/, following GeoParquet distribution best practices.

Given that schema varies by country, use schema merging when reading multiple countries together (e.g. union_by_name=true in DuckDB, schema=pa.unify_schemas(...) in PyArrow).

PMTiles

Per-country PMTiles under by_country/country_iso=<ISO>/.

A combined PMTiles file covering all 58 countries is available at dre_atlas.pmtiles. All layers are unified under the name dre_atlas.

CSV and GeoJSON

Traditional formats (CSV, GeoJSON) are available for download on energydata.info.

How to use

PMTiles — browser visualization

PMTiles enables scalable, serverless map visualization directly in the browser.

Combined PMTiles location: https://data.source.coop/vida/dre-atlas/dre_atlas.pmtiles

For QGIS and MapLibre, use the pmtiles:// prefix:

pmtiles://https://data.source.coop/vida/dre-atlas/dre_atlas.pmtiles

DuckDB — single country (HTTPS, no setup needed)

DuckDB — multi-country queries (S3 endpoint required for glob patterns)

Settlement counts by country

Unelectrified settlements with high demand

Adding a country_iso filter triggers Hive partition pruning — DuckDB reads only the matching files.

License

Creative Commons Attribution 4.0 International (CC BY 4.0)

You are free to share and adapt this data for any purpose, provided you give appropriate credit.

Contact

Malin Fischer, VIDA.place GmbH — malin@vida.place
Jessica La Costa, VIDA.place GmbH — jess@vida.place
Giorgio Basile, VIDA.place GmbH — giorgio@vida.place
Benjamin P. Stewart, World Bank Group — bstewart@worldbankgroup.org

1import leafmap
2
3url = "https://data.source.coop/vida/dre-atlas/dre_atlas.pmtiles"
4m = leafmap.Map(center=[0, 45], zoom=3, basemap="CartoDB.DarkMatter")
5style = {
6    "version": 8,
7    "sources": {"dre_atlas": {"type": "vector", "url": f"pmtiles://{url}"}},
8    "layers": [{
9        "id": "dre_atlas", "source": "dre_atlas", "source-layer": "dre_atlas",
10        "type": "circle",
11        "paint": {"circle-color": "#e63946", "circle-radius": 1.5, "circle-opacity": 0.8},
12    }],
13}
14m.add_pmtiles(url, layer_name="DRE Atlas", style=style, fit_bounds=False)
15m

1import leafmap
2
3url = "https://data.source.coop/vida/dre-atlas/dre_atlas.pmtiles"
4m = leafmap.Map(center=[0, 45], zoom=3, basemap="CartoDB.DarkMatter")
5style = {
6    "version": 8,
7    "sources": {"dre_atlas": {"type": "vector", "url": f"pmtiles://{url}"}},
8    "layers": [{
9        "id": "dre_atlas", "source": "dre_atlas", "source-layer": "dre_atlas",
10        "type": "circle",
11        "paint": {"circle-color": "#e63946", "circle-radius": 1.5, "circle-opacity": 0.8},
12    }],
13}
14m.add_pmtiles(url, layer_name="DRE Atlas", style=style, fit_bounds=False)
15m

1┌──────────────┬────────────┬─────────────────┬───────────┬────────────────┬──────────────────┐
2│ village_name │ population │ num_connections │  demand   │ has_nightlight │ main_road_access │
3│   varchar    │   int64    │      int64      │  double   │    boolean     │     boolean      │
4├──────────────┼────────────┼─────────────────┼───────────┼────────────────┼──────────────────┤
5│ Lagos        │   12340311 │         2615455 │ 1427901.6 │ true           │ true             │
6│ Kan Karofi   │    6443921 │         1322903 │  509529.2 │ true           │ true             │
7│ Ibadan       │    4960925 │         1039198 │  621781.9 │ true           │ true             │
8│ Amurie       │    3837349 │          792307 │  466328.2 │ true           │ true             │
9│ Abuja        │    3576670 │          744894 │  383589.8 │ true           │ true             │
10└──────────────┴────────────┴─────────────────┴───────────┴────────────────┴──────────────────┘

1┌──────────────┬────────────┬─────────────────┬───────────┬────────────────┬──────────────────┐
2│ village_name │ population │ num_connections │  demand   │ has_nightlight │ main_road_access │
3│   varchar    │   int64    │      int64      │  double   │    boolean     │     boolean      │
4├──────────────┼────────────┼─────────────────┼───────────┼────────────────┼──────────────────┤
5│ Lagos        │   12340311 │         2615455 │ 1427901.6 │ true           │ true             │
6│ Kan Karofi   │    6443921 │         1322903 │  509529.2 │ true           │ true             │
7│ Ibadan       │    4960925 │         1039198 │  621781.9 │ true           │ true             │
8│ Amurie       │    3837349 │          792307 │  466328.2 │ true           │ true             │
9│ Abuja        │    3576670 │          744894 │  383589.8 │ true           │ true             │
10└──────────────┴────────────┴─────────────────┴───────────┴────────────────┴──────────────────┘

1┌─────────────┬─────────────┐
2│ country_iso │ settlements │
3│   varchar   │    int64    │
4├─────────────┼─────────────┤
5│ PAK         │      240903 │
6│ ETH         │      156500 │
7│ NGA         │      154319 │
8│ TZA         │      137431 │
9│ NER         │       80986 │
10└─────────────┴─────────────┘

1┌─────────────┬─────────────┐
2│ country_iso │ settlements │
3│   varchar   │    int64    │
4├─────────────┼─────────────┤
5│ PAK         │      240903 │
6│ ETH         │      156500 │
7│ NGA         │      154319 │
8│ TZA         │      137431 │
9│ NER         │       80986 │
10└─────────────┴─────────────┘

1┌─────────────┬────────────────────────────┬────────────┬─────────┐
2│ country_iso │        village_name        │ population │ demand  │
3│   varchar   │          varchar           │   int64    │ double  │
4├─────────────┼────────────────────────────┼────────────┼─────────┤
5│ COD         │ Ngandajika                 │     269702 │ 14685.5 │
6│ UGA         │ Kalitusi A                 │     144510 │ 11120.5 │
7│ COD         │ Kabinda                    │     168855 │  9613.9 │
8│ COD         │ Luputa                     │     162234 │  8841.9 │
9│ SDN         │ Sarafaya                   │      61372 │  8442.7 │
10└─────────────┴────────────────────────────┴────────────┴─────────┘

1┌─────────────┬────────────────────────────┬────────────┬─────────┐
2│ country_iso │        village_name        │ population │ demand  │
3│   varchar   │          varchar           │   int64    │ double  │
4├─────────────┼────────────────────────────┼────────────┼─────────┤
5│ COD         │ Ngandajika                 │     269702 │ 14685.5 │
6│ UGA         │ Kalitusi A                 │     144510 │ 11120.5 │
7│ COD         │ Kabinda                    │     168855 │  9613.9 │
8│ COD         │ Luputa                     │     162234 │  8841.9 │
9│ SDN         │ Sarafaya                   │      61372 │  8442.7 │
10└─────────────┴────────────────────────────┴────────────┴─────────┘

1INSTALL httpfs; LOAD httpfs;
2
3SELECT village_name, population, num_connections, demand, has_nightlight, main_road_access
4FROM read_parquet('https://data.source.coop/vida/dre-atlas/by_country/country_iso=NGA/NGA.parquet')
5ORDER BY num_connections DESC
6LIMIT 5;

1INSTALL httpfs; LOAD httpfs;
2
3SELECT village_name, population, num_connections, demand, has_nightlight, main_road_access
4FROM read_parquet('https://data.source.coop/vida/dre-atlas/by_country/country_iso=NGA/NGA.parquet')
5ORDER BY num_connections DESC
6LIMIT 5;

1INSTALL httpfs; LOAD httpfs;
2SET s3_endpoint = 'data.source.coop';
3SET s3_url_style = 'path';
4SET s3_region = 'us-east-1';

1INSTALL httpfs; LOAD httpfs;
2SET s3_endpoint = 'data.source.coop';
3SET s3_url_style = 'path';
4SET s3_region = 'us-east-1';

1SELECT country_iso, count(*) AS settlements
2FROM read_parquet(
3  's3://vida/dre-atlas/by_country/*/*.parquet',
4  hive_partitioning = true,
5  union_by_name = true
6)
7GROUP BY country_iso
8ORDER BY settlements DESC
9LIMIT 5;

1SELECT country_iso, count(*) AS settlements
2FROM read_parquet(
3  's3://vida/dre-atlas/by_country/*/*.parquet',
4  hive_partitioning = true,
5  union_by_name = true
6)
7GROUP BY country_iso
8ORDER BY settlements DESC
9LIMIT 5;

1SELECT country_iso, village_name, population, demand
2FROM read_parquet(
3  's3://vida/dre-atlas/by_country/*/*.parquet',
4  hive_partitioning = true,
5  union_by_name = true
6)
7WHERE country_iso IN ('COD', 'UGA', 'SDN')
8  AND has_nightlight = false
9  AND main_road_access = true
10  AND demand > 100
11ORDER BY demand DESC
12LIMIT 5;

1SELECT country_iso, village_name, population, demand
2FROM read_parquet(
3  's3://vida/dre-atlas/by_country/*/*.parquet',
4  hive_partitioning = true,
5  union_by_name = true
6)
7WHERE country_iso IN ('COD', 'UGA', 'SDN')
8  AND has_nightlight = false
9  AND main_road_access = true
10  AND demand > 100
11ORDER BY demand DESC
12LIMIT 5;