Assessing urban sustainability in the Belt and Road region: a city-level analysis of SDG 11 indicators using earth observations
Tracking progress toward sustainable urban development requires detailed assessments of key indicators to support evidence-based policy and planning. However, data limitations often constrain evaluations of Sustainable Development Goal (SDG) indicators to national or sub-national levels. This study utilizes global urban spatial products derived from Earth observation data to evaluate the spatiotemporal dynamics of two urban SDG indicators – 11.3.1 (Land Use Efficiency, LUE) and 11.6.2 (annual average concentration of fine particulate matter in cities weighted by population or population-weighted PM₂.₅ concentrations, PPM₂.₅) – for over 7000 cities in the Belt and Road region between 2000 and 2020. The results show that 30.6% of cities improved LUE from 2010 to 2020 compared to 2000-2010, while 24.3% experienced deterioration. For PM₂.₅ exposure, 67.8% of cities experienced increased PPM₂.₅ by 2020 compared to 2000 levels, with the largest increases occurring in South Asia. The integrated assessment of the two indicators demonstrate the necessity for coordinated strategies that concurrently enhance land use efficiency and strengthen air pollution control measures. These findings demonstrate the value of Earth observation data for revealing regional disparities and informing localized SDG implementation strategies.
Authors
- Yifang Ban (ORCID: https://orcid.org/0000-0003-1369-3216)
- Linlin Lu (ORCID: https://orcid.org/0000-0003-1647-1950)
- Sebastian Häfner (ORCID: https://orcid.org/0000-0003-3560-638X)
- Huadong Guo (ORCID: https://orcid.org/0000-0003-0337-1862)
- Muhammad Fahad Baqa (ORCID: https://orcid.org/0000-0002-4165-6802)
- Xuting Liu (ORCID: https://orcid.org/0000-0003-3980-5386)
- Michele Melchiorri (ORCID: https://orcid.org/0000-0002-3009-8868)
- Martino Pesaresi (ORCID: https://orcid.org/0000-0003-0620-439X)
- Qingting Li (ORCID: https://orcid.org/0000-0002-6322-8307)
Institutions
- Chinese Academy of Sciences (CN)
- European Commission (BE)
- Beijing Institute of Big Data Research (CN)
- Aerospace Information Research Institute (CN)
- University of Chinese Academy of Sciences (CN)
- KTH Royal Institute of Technology (SE)
Publication Details
- Journal
- International Journal of Digital Earth
- Published
- 2025-06-27
- DOI
- https://doi.org/10.1080/17538947.2025.2522395
- Citations
- 1
- Primary Topic
- Land Use and Ecosystem Services
- Type
- article
- Field-Weighted Citation Impact
- 1.11
Funders
- National Natural Science Foundation of China