A method to estimate population densities and electricity consumption from mobile phone data in developing countries

Area of Science:

• Demography
• Mobile Network Analysis
• Geospatial Data Science

Background:

• High-quality census data is often unavailable in developing nations.
• Mobile phone data is increasingly used as a proxy for population characteristics.
• Existing methods using average phone activity show limitations in accuracy.

Purpose of the Study:

• To develop a more accurate method for estimating population density and activity using mobile phone data.
• To address the limitations of direct correlation methods.
• To provide vital information for development and infrastructure planning in data-scarce regions.

Main Methods:

• Analyzing daily, weekly, and yearly phone activity curves.
• Incorporating mobile network characteristics.
• Ensuring privacy preservation throughout the process.

Main Results:

• The proposed method demonstrates higher accuracy in estimating population density and activity compared to direct correlation.
• Identified limitations in using average phone activity due to market share heterogeneity and cell tower distribution.
• The approach effectively utilizes temporal and network features of mobile data.

Conclusions:

• Mobile phone data, when analyzed with advanced methods, can reliably estimate population characteristics.
• This approach offers a cost-effective solution for data collection in developing countries.
• The findings support improved development and infrastructure planning through innovative data utilization.