Exploring global migration: A high-resolution dataset

High-resolution dataset covering net migration patterns over the past two decades.

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The researchers from the University of Bologna discovered high emigration levels in regions in the middle of the HDI and aridity scales, such as Central America, northeast Brazil, Central Africa, and Southeast Asia. This shows that not only the poorest of the poor are escaping environmental calamities or changes, pointing to migration as an adaptation mechanism adopted by anyone who can move away.

The researchers created a high-resolution dataset covering net migration patterns over the past two decades (2000-2019). This dataset offers detailed insights that were impossible to obtain using national averages.

The new study shows that net migration patterns worldwide are more strongly linked with socioeconomic factors. It provides a new, high-resolution dataset on net migration over the last two decades, which may be used to inform policy and inspire future research. The new dataset is freely accessible and may be examined using an online interactive map.

The new study highlights human development factors’ importance over climate factors. It shows the complexity of migration patterns overlooked by national averages.

Study lead author Venla Niva, a postdoctoral researcher at Aalto University, said, “There was a real need for a dataset like this, but it didn’t exist. So, we decided to make it ourselves.” 

To estimate net migration, the researchers combined birth and death rates with overall population growth. They incorporated the Human Development Index (HDI) and the aridity index to understand migration patterns. They created a net-migration dataset with remarkable resolution by starting with sub-national death and birth rates and scaling them down to 10 km resolution. This allows the discussion of issues that cannot be resolved using national aggregates.

Study coauthor Raya Muttarak, a researcher in the IIASA Population and Just Societies Program at the University of Bologna, said, “The annual gridded migration data we produced can be useful to answer many relevant research questions such as climate-related migration and migration trends. The migration data can be combined with gridded environmental and socioeconomic data enabling comprehensive analysis of migration drivers.” 

Areas with a high HDI saw positive net migration regardless of climatic conditions. The Arabian Peninsula, North America, Australia, and the North Mediterranean are net recipients despite their aridity.

He said, “This finding is consistent with our previous work where we performed a meta-analysis of quantitative studies on environmental migration and found that migration response to environmental stress is more likely in middle-income countries.”

Matti Kummu, associate professor of global water and food issues at Aalto University and senior author of the study, said, “Decision-makers should pay attention to this. Rather than focusing solely on border closures and combatting migration, we should work to support and empower individuals in economically disadvantaged countries. That would help reduce the drivers that compel people to migrate for better opportunities.” 

Migration between the urban and rural areas also revealed unexpected patterns. According to the study, it is usually assumed that metropolitan regions attract individuals from rural areas. However, this was only sometimes the case. There are many countries, such as Europe, where the reverse is true. Migration from cities to rural regions was also observed in Congo, Indonesia, Pakistan, and Venezuela. When examined at the community level, the picture becomes even more complex.

The new dataset will allow researchers to understand more about migration than they could be using national averages, which only provide part of the story. Other researchers and worldwide organizations, like the UN International Organization for Migration, have already received the data from the team. Interested people can examine these patterns for themselves on the interactive map.

In a result, researchers can measure and analyze migration impacts in all countries in detail, which helps to provide a comprehensive picture of migration worldwide.

Journal Reference:

  1. Venla Niva,Alexander Horton,et al.World’s human migration patterns in 2000–2019 unveiled by high-resolution data. Nature human behavior. DOI: 10.1038/s41562-023-01689-4
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