November 11, 2020
| Dataset date: Nov 21, 2020-May 23, 2026
This data is by request only
Contains data crowdsourced from Venezuelans through the Premise Data mobile application. The booklet included HERE provides more details on how crowdsourcing works. The data tracks delivery indicators for electricity, cooking gas, and garbage disposal at a weekly granularity.
Community facilities surveys for Gihembe, Kigeme and Nyabiheke refugee camps in Rwanda. The surveys contain information on community facility type and operations, energy for lighting and other uses, access to electricity technologies, respondent needs and priorities, and other energy-related issues.
Enterprise surveys for Gihembe, Kigeme and Nyabiheke refugee camp in Rwanda. The datasets contain information on enterprise type and operations, energy for lighting and productive uses, access to electricity technologies, respondent needs and priorities, and other energy-related issues.
Household surveys for Gihembe, Kigeme and Nyabiheke refugee camps in Rwanda. The surveys contain information on household demographics, energy use for lighting and cooking, access to electricity technologies, respondent needs and priorities, and other energy-related issues.
The dataset contains the full data collected in the field related to energy access. The assessment used the "Beyond Connection" methodology, developed by ESMAP (World Bank).
The full sample is based on 210 interviews at the household level in 68 different communities within the Hebron Governorate. All the households are in Area C.
As soon the data are fully analyzed, an open version will be released.
March 19, 2019
| Dataset date: Jan 24, 2019
This dataset updates: Never
Facebook has produced a model to help map global medium voltage (MV) grid infrastructure, i.e. the distribution lines which connect high-voltage transmission infrastructure to consumer-serving low-voltage distribution. The data found here are model outputs for six select African countries: Malawi, Nigeria, Uganda, DRC, Cote D’Ivoire, and Zambia. The grid maps are produced using a new methodology that employs various publicly-available datasets (night time satellite imagery, roads, political boundaries, etc) to predict the location of existing MV grid infrastructure. The model documentation and code are also available , so data scientists and planners globally can replicate the model to expand model coverage to other countries where this data is not already available. You can find the model code and documentation here: https://github.com/facebookresearch/many-to-many-dijkstra
Note: current model accuracy is approximately 70% when compared to existing ground-truthed data. Accuracy can be further improved by integrating other locally-relevant information into the model and running it again.
Resolution: geotiff is provided at Bing Tile Level 20
El suministro eléctrico forma parte de la infraestructura fundamental para el funcionamiento de los aparatos de comunicación para la difusión de las alertas tempranas y coordinación de las actividades de preparación y de emergencia.