Population Density Maps
Our Population Density Maps help nonprofit and multilateral agencies plan vaccination campaigns, respond to natural disasters, and evaluate rural electrification plans. These maps help researchers assess the ways in which climate change and urbanization impact where people live.

Features

Our Population Density Maps help nonprofit and multilateral agencies plan vaccination campaigns, respond to natural disasters, and evaluate rural electrification plans. These maps help researchers assess the ways in which climate change and urbanization impact where people live.
In partnership with the Center for International Earth Science Information Network (CIESIN) at Columbia University, we use state-of-the-art computer vision techniques to identify buildings from publicly accessible mapping services to create the world's most accurate population datasets. Our maps are available at 30-meter resolution — much more accurate than existing high-resolution maps, which are only available at a resolution of 100 meters.

Training data through neural networks
To map populations, Facebook's Spatial Computing team trains pattern-recognizing algorithms to identify buildings in commercially available satellite images from Maxar. Using hand-labeled data from diverse areas, these algorithms learn to understand varied landscapes, ensuring extremely accurate modeling anywhere on earth.

Combination with population data
Using building information from Facebook’s analysis, Columbia combines these insights with Census data to generate population estimates, which are then applied to the structures in the satellite imagery. As a final step, the team validates these estimates against more coarse-grained datasets including anonymized household surveys from USAID and the World Bank.
Who uses Population Density Maps
Facebook's high-resolution population density maps have been used by a range of nonprofit and multilateral agencies to plan vaccination campaigns, respond to natural disasters, and assess the feasibility of rural electrification plans. Researchers have also used these layers to analyze trends in urbanization and to assess the impact of climate change on where people live.

Public health institutions
Public health organizations have used these maps to improve the way they reach rural populations with health interventions. For example, in the Democratic Republic of Congo and Mozambique, the Gates Foundation is using Facebook's population maps to improve the way health workers reach households with information about forthcoming vaccine distributions, to procure the right number of vaccines, and to verify the number of children under five to be vaccinated. These maps are also helpful for volunteers distributing bed nets or performing indoor residual spraying for malaria control.
Disaster preparedness and response organizations
Aid organizations have used our settlement layer for disaster preparedness projects, mapping which areas are most likely to be affected by natural disaster and how populations are distributed within those areas.
Rural electrification planners
Rural electrification operators can use our population maps to analyze settlements in urban and rural areas through satellite imagery and prioritize locations for development.
Researchers
Researchers can use the Facebook high resolution settlement layer to help inform development programs that require sub-national population estimates, to understand trends in human mobility, and to accurately quantify urbanization rates.


A high resolution population density map layer for Pretoria, South Africa.

A high resolution population density map layer, for Accra, Ghana.


Case Studies
In the News
Get Involved
Check out our high resolution population density maps, available for download on the United Nations Office for the Coordination of Humanitarian Affairs (OCHA)’s Humanitarian Data Exchange. To reference this data, please use the following citation: Facebook Connectivity Lab and Center for International Earth Science Information Network - CIESIN - Columbia University. 2016. High Resolution Settlement Layer (HRSL). Source imagery for HRSL © 2016 DigitalGlobe. Accessed DAY MONTH YEAR."