Sparsely built houses in the fishing village of Arnarstapi in Iceland - Photo: BUSTRAVEL ICELAND/DANNI ARNDT
The reason, according to researchers at Aalto University (Finland), is that most datasets significantly underestimate the number of people living in rural areas - areas that are difficult to track and report accurate data.
The research team analyzed five of the most widely used global population datasets, including WorldPop, GWP, GRUMP, LandScan, and GHS-POP, and concluded that they likely undercount the rural population by 53% to 84%, according to IFLScience on March 21.
They came to this conclusion after comparing global datasets with resettlement data from more than 300 rural dam projects in 35 countries. The team then compared the information obtained with information from satellite images.
When dams are built, large areas are flooded and people need to be relocated, according to the research team. Resettlement populations are often accurately counted because dam companies must compensate those affected. Meanwhile, global data sets can be inaccurate due to some ambiguity related to administrative boundaries.
Even the most reliable datasets from 2010 were found to underestimate rural populations by between a third and three-quarters. The researchers say there is good reason to believe similar errors are occurring in global population datasets from 2015 and 2020.
Since an estimated 43 percent of people currently live in rural areas, it is likely that the current world population estimate of 8.2 billion is an underestimate. How much lower? That is the big question that researchers are not yet ready to answer.
Location of 307 rural areas in the study - Photo: AALTO UNIVERSITY
“For the first time, our study provides evidence that a significant proportion of the rural population may be undercounted in global population datasets,” said Josias Lang-Ritter, one of the study’s authors.
The team was also surprised to find that the actual population living in rural areas was much higher than the number recorded in global population data. Depending on the dataset, the rural population was underestimated by 53% to 84% over the study period.
This result is noteworthy because the aforementioned datasets are used in thousands of studies and support relevant government decisions, but their accuracy has not yet been systematically evaluated.
However, not everyone is convinced by this study. Stuart Gietel Basten, working at the Hong Kong University of Science and Technology (China), said that this finding cannot be applied globally because many data are concentrated in China and other places in Asia and countries such as Finland, Australia, Sweden ... have sophisticated population registration systems.
Still, the study also highlights problems with how to collect population data from rural areas, especially in developing countries and crisis-hit and non-industrialized areas.
Addressing such data gaps is essential if we are to better understand our planet. More accurate population mapping can lead to better resource allocation, improved infrastructure planning, and a deeper understanding of human life.
The study was published in the journal Nature Communications.
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