On paper, Arcelia looks like a poor-but-average Mexican town. It sits in Guerrero, Mexico's second-poorest state. 

Official data gives it a score of 0.714 — firmly in the "high development" band on the United Nations' Human Development Index (HDI).   

Then a satellite looks at Arcelia. Using artificial intelligence to analyze what it sees, it returns a lower score of 0.617. 

By the UN's own classification, that is no longer high but medium development — a different development tier and a different policy-reality for 33,000 people. 

Arcelia is not a special case. More than half (58%) of the global population is in the wrong development tier, because official data averages too broadly to see them. That is the central finding of a study published in the journal Nature Communications by researchers from Stanford University in the US and the UN's Development Programme.  

"There hasn't been a census in the last 10 years in about half of the world's poorest countries," said Hannah Druckenmiller, a co-author of the study, highlighting the necessity of up-to-date and accurate information to ensure public policy matches people's day-to-day needs.

An accurate HDI score matters for aid delivery

The Human Development Index is not merely a ranking. It "can determine allocations of global resources," the study's authors note. That shapes which regions are prioritized for aid.

Getting it wrong at the local level means resources may miss the people who need them most. The problem is that the HDI only provides a score for entire countries. It wasn't originally conceived to differentiate between provinces or even municipalities within a country.

But in a simulated aid program for Mexico, one that targeted the poorest 10% of the country's population, researchers found that adding data from the municipal-level improved their understanding about the state of people's development — levels of poverty and wealth, education and health — by more than 11 percentage points. 

The HDI fixed one blind spot — and created another 

For decades, measuring development meant measuring Gross Domestic Product (GDP) — a country's total economic output. The problem is that GDP can rise, benefiting only some people, while others remain illiterate, sick, or poor.  

In 1990, the UN introduced the Human Development Index to fix that. 

"[HDI] looks at the average Gross National Income per capita, the average completed years of schooling or expected years of schooling, and the average life expectancy of each country, and combines them to come up with an indicator of well-being that runs from 0 to 1," said Sabina Alkire, director of the University of Oxford's Poverty and Human Development Initiative. Alkire was not part of the new study. 

HDI is based on data from the UN's own agencies, the World Bank, and national household and census surveys. It has become the world's most widely used alternative to GDP. 

But the researchers in the 2026 study felt the HDI still falls short of an accurate measure — the national averages presented in the HDI reveal little about what is happening inside a country at a local level. 

Take a look at the map below, for example. 

This map presents one color per country. More developed nations are blue. Large parts of Africa and South Asia are orange and red. It's a useful visualization of global human development — but a very basic one. 

Take Mexico: At the national level, that's 130 million people represented by one color — blue. One development score for all.

But development levels can differ from province to province.

In 2019, a team led by Jeroen Smits and Inaki Permanyer took the HDI to the province-level, detailing 1,739 provinces in 159 countries. They called it the Subnational Human Development Index. 

That changed Mexico's outlook: It now had 32 scores instead of just one. 

The north and center of Mexico still came out blue. The south, meanwhile — particularly, Guerrero, Oaxaca, Chiapas — had gone a shade of light blue.

It was more granular than the original HDI, but each block still only showed a single average. And we now know that even within a province, development scores can differ.

Guerrero alone has 81 municipalities — all assigned the same number in the SHDI. The 2026 study set out to go a step further and reveal the truth about life in each of those municipalities, using satellite data. 

What satellites can and cannot see 

The Stanford team fed satellite images into a machine learning model alongside known province level HDI scores and let the algorithm find patterns. 

What emerged were statistical correlations about road density, building patterns and nighttime light — human-made signatures of income and education. Health outcomes, less visible from space, proved harder to capture. 

The map below shows what the model predicted — an HDI score for each of Mexico's 2,500 municipalities, on the same scale as the previous two maps. The difference from Map 2 is what matters. 

What looked like uniform light blue in Guerrero broke down into a patchwork of many more shades of blue — and local realities. 

Take Arcelia again. With data at the province level, Arcelia had a score of 0.714 — "high development." However, with the satellite data, it gets a score of 0.617 — "medium development." That's potentially a big difference for 33,000 people. 

A step forward — but not the whole picture

As director of the Oxford Poverty and Human Development Initiative, Alkire has spent two decades developing poverty measurement tools used by governments worldwide. 

Alkire called the new Stanford study a step forward: "We as a community working on measurement are in a time of innovation," Alkire told DW. "These kinds of studies are brilliant because they're pushing the envelope." 

But both Alkire and the study's authors note that satellites also only see part of the story. They don't deliver good data on health development. 

"An undernourished child isn't visible from nightlights," Alkire said. The authors themselves said their estimates explain only 29% of within-province HDI variation in Mexico.

So, it's unlikely that satellites alone will provide a full picture of human development. "Solely based on satellite, I don't think so," Alkire said. 

But satellite data have been shown to be a valuable addition, especially where surveys are too expensive or too slow — satellites complement ground-level data but cannot replace it.

Edited by: Zulfikar Abbany