Tashkent, Uzbekistan (UzDaily.com) — The Center for Economic Research and Reforms (CERR) has, for the first time, employed NASA’s nighttime light (NTL) satellite data to evaluate economic activity across Uzbekistan’s regions and cities.

The analysis was carried out using machine learning and artificial intelligence methods.

This approach, widely used in international practice, is considered an efficient and independent tool for measuring welfare and spatial development. Applied in Uzbekistan for the first time, the methodology showed a high degree of consistency with official statistics.

Independent Data Confirms GDP Growth

According to NTL data, Uzbekistan’s GDP per capita grew by 63.5% between 2020 and 2024 — from US$2,011 to US$3,287. This is in line with official figures, which recorded growth of 59.4%.

The largest increase was observed in the capital: Tashkent’s gross regional product (GRP) per capita rose by US$3,200, reaching US$7,200. In some districts of the city — including Mirabad, Yakkasaray, and Yunusabad — this figure exceeded US$9,000, nearly double the average level in other major cities of the country.

City Leaders

The highest GRP per capita levels in 2024 were recorded in:
Navoi — US$8,300
Zarafshan — US$6,800
Samarkand — US$5,700
Kokand — US$5,600
Andijan — US$5,100
Yangiyul — US$5,000
Karshi — US$4,800

High levels were also noted in Termez (US$4,500), Urgench, Margilan, Kattakurgan (US$4,300), and Chirchik (US$4,000).

At the regional level, significant growth was observed in Navoi, Namangan, Fergana, and Samarkand regions, with increases ranging from US$1,400 to US$1,500 over the analyzed period.

Urbanization: 27 Districts Shift Toward Urban Development

The satellite data analysis also helped track urbanization trends. The number of territories with high lighting levels (NTL > 10), typical of urban agglomerations, grew from 21 to 26. Meanwhile, the number of low‑lit rural areas decreased from 129 to 102.

This indicates that 27 districts are shifting toward an urban model of development — an important indicator of the economy’s structural transformation.