A recent study published in the International Journal of Digital Earth offers the first city-level analysis of urban sustainability trends across over 7,000 urban centers in the Belt and Road Initiative (BRI) region.
Using multi-temporal Earth observation (EO) data, the study assesses two indicators tied to Sustainable Development Goal 11 (SDG 11)-Land Use Efficiency (LUE, SDG 11.3.1) and population-weighted PM2.5 concentrations (PPM2.5, SDG 11.6.2)-from 2000 to 2020. It delivers a spatiotemporal breakdown of how urban expansion and environmental exposure intersect with sustainability.
Between 2010 and 2020, roughly 30.6% of cities showed improvements in LUE compared to the prior decade, while 24.3% recorded declines. Over the same period, 67.8% of cities saw higher PPM2.5 exposure than in 2000. The most severe deterioration was observed in Southern Asia, where annual average concentrations hit 53.9 μg/m3 by 2020. A key finding from the integrated analysis: 38.2% of sampled cities-particularly in South Asia-exhibited a dominant pattern of uncoordinated urban growth, characterized by sprawling expansion alongside rising pollution exposure.
By contrast, 22.6% of cities-mostly in East Asia-proved that decoupling urban expansion from worsening air quality is feasible. These cities saw improved air quality despite sprawling land development. The results underscore the need for region-specific urban and environmental policies. Notably, "shrinking cities" (where LUE < 0) did not consistently show better air quality, highlighting that population decline alone fails to reduce environmental exposure without structural reforms.
This study draws on satellite-derived built-up area data (GHS-BUILT-S), population grids (WorldPop), and a globally validated PM2.5 dataset with approximately 1-kilometer spatial resolution. These were used to calculate city-level Land Consumption Rate to Population Growth Rate ratio (LCRPGR) and PPM2.5 indicators. Urban boundaries were defined using the GHSL-OECD Functional Urban Areas framework, ensuring consistent long-term comparisons.
Furthermore, the researchers developed a two-dimensional classification system to group cities into eight urban development types based on changes in LUE and PPM2.5. This categorization provides a diagnostic tool for evaluating trade-offs between spatial expansion and environmental exposure, with practical applications for SDG monitoring and urban sustainability planning, the researchers noted.
The study highlights the value of open EO data for subnational SDG indicator tracking, especially in regions with limited statistical infrastructure. It calls for integrated strategies combining compact urban design, effective air quality management, and data-driven governance.
