Transportation investments in developing nations are often made in data-scarce environments, hampering effective urban development and project planning.

Widespread mobile phone adoption and authorities' maintenance of location data create new opportunities for passive collection of people's movement data. High-resolution mobile phone signal data enables derivation of key mobility metrics including per capita trip rate, hourly trip volumes, origin-destination patterns, and congestion detection.

This session will present findings on deriving mobility patterns using mobile phone signal data from Nepal and will demonstrate application to urban development and transportation planning. The Nepal case study will be used as reference to discuss potential applicability in Asian Development Bank projects including metro rail financing, bus service improvements, and digital twins.

By the end of the session, participants will:

1. Understand the benefits of using mobile phone data in decision making for urban planning and transport investments.
2. Gain practical knowledge of approaches to utilize insights from mobile phone data in different project and urban contexts.