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Benchmarking and monitoring of urban design and transport features is crucial to achieving local and international health and sustainability goals. However, most urban indicator frameworks use coarse spatial scales that either 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 show 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 effects, and learning lessons from peer cities to achieve health, equity, and sustainability goals., Competing Interests: Declaration of interests GB reports grants from The Public Good Projects during the conduct of the study. BG-C reports Senior Principal Research Fellowship (GNT1107672) and grant support (numbers 1061404 and 9100003) from the Australian National Health and Medical Research Council (NHMRC) during the conduct of the study. CH reports grant support (numbers 1061404 and 9100003) from the NHMRC. SL reports an experiential fellowship from the College of Social Science and Humanities, Northeastern University during the conduct of this study. JFS reports personal fees from SPARK programmes of Gopher Sport, and serving on the board of directors for Rails to Trails Conservancy, outside the submitted work. JFS also has a copyright on SPARK physical activity programmes with royalties paid by Gopher Sport. EC and JFS report support from the Australian Catholic University during the conduct of this study. DS reports support from Washington University in St Louis, Center for Diabetes Translation Research (number P30DK092950 from the US National Institute of Diabetes and Digestive and Kidney Diseases [NIDDK] and the US National Institutes of Health [NIH]) and from the Centers for Disease Control and Prevention (cooperative agreement number U48DP006395) during the conduct of this study. MAA reports grants from the US National Cancer Institute at the NIH (R01CA198915) during the conduct of the study. LVB reports grants from Conselho Nacional de Desenvolvimento Científico e Tecnológico (grant number 304636/2020-7) during the conduct of the study. All other authors report no competing interests. The content of this article is solely the responsibility of the authors and does not represent the official views of any of the NIDDK, NIH, the Centers for Disease Control and Prevention, or of any of the funding agencies supporting this work., (Copyright © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)