- Boeing, Geoff;
- Higgs, Carl;
- Liu, Shiqin;
- Giles-Corti, Billie;
- Sallis, James F;
- Cerin, Ester;
- Lowe, Melanie;
- Adlakha, Deepti;
- Hinckson, Erica;
- Moudon, Anne Vernez;
- Salvo, Deborah;
- Adams, Marc A;
- Barrozo, Ligia V;
- Bozovic, Tamara;
- Delclos-Alio, Xavier;
- Dygryn, Jan;
- Ferguson, Sara;
- Gebel, Klaus;
- Ho, Thanh Phuong;
- Lai, Poh-Chin;
- Martori, Joan C;
- Nitvimol, Kornsupha;
- Queralt, Ana;
- Roberts, Jennifer D;
- Sambo, Garba H;
- Schipperijn, Jasper;
- Vale, David;
- Van de Weghe, Nico;
- Vich, Guillem;
- Arundel, Jonathan
Benchmarking and monitoring urban design and transport features is critical to achieving local and international health and sustainability goals. However, most urban indicator frameworks use coarse spatial scales that only allow between-city comparisons or require expensive, technical, local spatial analyses for within-city comparisons. This study developed a reusable open-source urban indicator computational framework using open data to enable consistent local and global comparative analyses. We demonstrate this framework by calculating spatial indicators—for 25 diverse cities in 19 countries—of urban design and transport features that support health and sustainability. We link these indicators to cities’ policy contexts and identify populations living above and below critical thresholds for physical activity through walking. Efforts to broaden participation in crowdsourcing data and to calculate globally consistent indicators are essential for planning evidence-informed urban interventions, monitoring policy impacts, and learning lessons from peer cities to achieve health, equity, and sustainability goals.