Full metadata record
DC FieldValueLanguage
dc.date.accessioned2026-04-16T21:31:18Z-
dc.date.available2026-04-16T21:31:18Z-
dc.date.issued2023-
dc.identifier.urihttp://item.bettergrids.org/handle/1001/760-
dc.description.abstractThis dataset gives a full overview of the current (up to 2022) transmission grid infrastructure of Liberia including power plants, power stations, power towers and power lines with attributes such as length, assumed voltage level etc.. The dataset was produced by using smart tracing algorithms developed by NEO in house which uses grid probability map for determining areas to look for power towers and a deep learning model for power tower automatic detection. The power plants and (sub)stations collected from open source (Global power plant database, Global dam dataset, OpenStreetMap and Energydata.info etc.) as well as some existing power towers from OpenStreetMap dataset were used as starting point for smart tracing alogirthm, and Mapbox 50cm Very High Resolution imagery was used as input for detecting power towers using the trained deep learning model. The OSM points are also included into the dataset to make best use of existing dataset to achieve complete grid mapping coverage as much as possible in an efficient and effective way. The probability map and path finder is adapted based on Global Grid Finder approach :https://gridfinder.org/ Global power plant database: https://datasets.wri.org/dataset/globalpowerplantdatabase Global dam dataset: http://globaldamwatch.org/data/en_US
dc.titleLiberia electricity transmission network 2023en_US
dc.typeGrid Model Dataseten_US
grid.formatUnspecifieden_US
grid.identifier.urlhttps://opennetzero.org/neo/liberia-electricity-transmission-network-2023-
Appears in Collections:Integrated Transmission and Distribution. Steady State



User Comments

Average user rating

0.0 / 5

Rating breakdown

5
80% Complete (danger)
0%
4
80% Complete (danger)
0%
3
80% Complete (danger)
0%
2
80% Complete (danger)
0%
1
80% Complete (danger)
0%

Items in BetterGrids are protected by copyright, with all rights reserved, unless otherwise indicated.