Nepal Turns to Mobile Phone Data for Smarter Transport and City Planning

A new report by the Asian Development Bank (ADB) has revealed how mobile phone data could transform transportation and urban planning in developing countries like Nepal. Prepared by researchers Sin Wai Chong, Saugata Dasgupta, Ravi Gadepalli, Mriganka Saxena, and Matthew Webster, the study shows how anonymous telecom data can help governments better understand how people travel through cities and regions.

The report comes at a time when countries across Asia are struggling with rapid urban growth, traffic congestion, and rising infrastructure costs. According to the study, Asia and the Pacific will need around $43 trillion in transportation investment between 2020 and 2035. Yet many governments still rely on traditional travel surveys that are expensive, slow, and often outdated.

The Nepal study argues that mobile phone data offers a faster and more accurate way to understand real travel behavior. Since almost everyone carries a phone, telecom networks constantly record movement patterns as devices connect to mobile towers. By analyzing this anonymous data, researchers can track millions of trips across cities without directly surveying people.

Why Traditional Transport Surveys Fall Short

For decades, transportation planning has depended on household interviews, roadside traffic counts, and census data. These methods usually cover only a small sample of the population and often miss short trips, walking journeys, or irregular travel patterns.

The report says such surveys are especially difficult in developing countries where cities are expanding rapidly. By the time a survey is completed, urban growth and traffic conditions may already have changed.

Mobile phone data solves many of these problems because it captures movement continuously and on a much larger scale. Unlike surveys that rely on people remembering where they traveled, telecom data records actual movement in near real time.

Researchers explain that there are two main types of mobile phone data. Smartphone GPS data comes from apps that track location, but this often represents only wealthier smartphone users. Telecom network data, however, includes signals from almost all active mobile phones connected to cell towers, making it far more useful for large-scale planning.

Inside Nepal’s Massive Mobility Study

The ADB study analyzed anonymized telecom data collected across Nepal during October 2023. Researchers focused on Kathmandu Valley, Pokhara, and the Lumbini–Butwal–Siddharthnagar corridor.

After removing incomplete or unreliable records, the team studied around 11.6 million trips. The researchers combined telecom data with satellite images, land-use maps, road networks, and building density information to understand how urban development affects travel demand.

The findings showed that movement in Nepal is heavily concentrated in dense urban areas. In Kathmandu, nearly 90% of trips occur within just 30% of the metropolitan area. In the Lumbini corridor, fewer than 10% of urban zones account for almost 70% of total travel demand.

Pokhara showed a more spread-out pattern. While the city center generated most trips, the surrounding areas also contributed significantly to overall mobility.

According to the report, these insights could help governments focus investments in roads, buses, and mobility services where they are needed most instead of spreading resources evenly across entire cities.

Surprising Travel Patterns in Nepal

The report also uncovered several unexpected trends about daily travel behavior in Nepal.

Researchers found that the average person makes about 1.61 trips per day across the three study locations. Surprisingly, travel demand remained fairly similar on weekdays and weekends. This differs from many developed countries, where weekday commuting creates much heavier traffic.

The daily travel pattern was also unusual. Instead of clear morning and evening rush hours, Nepal’s cities showed one long travel peak between 8 a.m. and noon. Nearly half of all trips happened between 8 a.m. and 2 p.m., while most movement ended before 7 p.m.

Researchers believe tourism activity, mixed land-use neighborhoods, and reduced travel after sunset in mountainous regions may explain these patterns.

The study also found that many trips were relatively short. Around one-fifth of all trips lasted less than 15 minutes, suggesting strong potential for walking and improved public transport systems.

A New Future for Urban Planning

Mobile phone data could become one of the most powerful tools for transportation planning in developing countries. Instead of depending only on occasional surveys, governments could continuously monitor mobility patterns and make faster, evidence-based decisions.

Beyond transportation, telecom data could also help identify growing commercial centers, improve tourism planning, monitor congestion, and guide future urban expansion.

However, the report also warns about challenges. Access to telecom data is tightly controlled in many countries because of privacy concerns. Processing billions of telecom signals also requires advanced technology and computing power. In addition, mobile phone data cannot fully capture groups without phones, including many children and elderly people.

Despite these limits, the Nepal study shows that mobile phone analytics can provide a far clearer picture of how cities function than traditional planning methods. For governments trying to manage rapid urban growth with limited resources, the report suggests that the future of transportation planning may lie in the invisible digital signals generated every day by millions of mobile phones.