From data inconsistency to reliable SDG 11.3.1 monitoring: A global multi-dataset assessment of land use efficiency

This study assesses the reliability of land use efficiency (LUE) as a primary Sustainable Development Goal (SDG) indicator 11.3.1, the land consumption rate to population growth rate, using six built-up area datasets and four population datasets for 176 countries during 2000∼2020. Specifically, this study aims to answer (1) How consistent are global LUE estimates across different built-up and population datasets? and (2) Which data sources and metrics are responsible for such inconsistencies. We quantified consistency with intra-class correlation and Fleiss’ Kappa and developed an ensemble LUE score framework that integrates multiple datasets to evaluate both LUE status and LUE trends systematically. Our analysis shows pronounced discrepancies among built-up area datasets, especially the land consumption rate derived from these datasets, while population datasets exhibit much higher consistency. Meanwhile, datasets exhibited substantial disagreements in Africa and Western Asia. Taken together, LUE scores derived from these two kinds of datasets shown substantial uncertainty. The score indicates that, although LUE improved in about 30% of countries, datasets consistently agreed on the failure to achieve good LUE status in over half of the countries. These findings demonstrate the limitations of relying on single datasets and underscore the importance of multi-source data integration for monitoring. The integrated analysis further suggests that global progress toward SDG 11.3.1 remains uncertain, which reflects not only the inconsistencies among datasets but also the limited progress observed so far, suggesting that achieving SDG 11.3.1 by 2030 remains challenging. Moreover, the analysis reveals a development-dependent divergence: in many developing countries, the main challenge is rapid urban expansion, whereas in many developed ones, lower LUE scores are more often associated with persistent urban sprawl and population decline. These findings highlight the urgent need for differentiated land use policies to achieve sustainable urbanization. • Quantified consistency among six built-up and four population datasets globaly. • Revealed large discrepancies among built-up datasets causing high SDG 11.3.1 uncertainty. • Developed a consistency-based integration framework for reliable LUE assessment. • Found uncertain progress of SDG 11.3.1 with over half of countries inefficient. • Showed developed countries tend to have lower land-use efficiency than developing ones.