{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T05:08:01Z","timestamp":1790140081782,"version":"4.0.1"},"reference-count":47,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T00:00:00Z","timestamp":1790121600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Big Data"],"abstract":"<jats:p>Cities invest in social infrastructure to improve well-being, but the benefits depend on who can use these spaces and who actually does. Access is therefore not only a matter of whether people live close enough to reach a facility, but also of who travels to it and from how far. We examine this realized access using high-resolution human mobility data from Location-Based Services (LBS) for the Utop\u00edas, a network of thirteen community centers offering free recreation, culture, and care in Iztapalapa, an underserved borough of 1.8 million residents in eastern Mexico City. We combine six months of mobility traces with public transit data (GTFS), a georeferenced crime registry, and a catalog of facility activities to identify the factors associated with each site's visitors. Three factors capture distinct dimensions of reach. Transit connectivity tracks the number of visitors a site draws. Facilities with more distinctive activities, such as a planetarium or a dinosaur park, show a greater increase in visitor travel distance at weekends. By contrast, a higher share of violent crime in the surrounding area is associated with more localized and lower-income visitor catchments. Together, these findings show that the reach of social infrastructure varies not only with proximity, but also with transport, the distinctiveness of what facilities offer, and local safety.<\/jats:p>","DOI":"10.3389\/fdata.2026.1942458","type":"journal-article","created":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T04:50:43Z","timestamp":1790139043000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Evaluating the reach and equity of public spaces in Mexico City using mobility data: the case of the Utop\u00edas in Iztapalapa"],"prefix":"10.3389","volume":"9","author":[{"given":"Ollin D.","family":"Langle-Chimal","sequence":"first","affiliation":[{"name":"Department of Civil and Environmental Engineering, University of California","place":["Berkeley, Berkeley, CA, United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Natalia","family":"Cadavid-Aguilar","sequence":"additional","affiliation":[{"name":"Tecnologico de Monterrey, Center for the Future of Cities","place":["Mexico City, Mexico"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alberto","family":"Meouchi-V\u00e9lez","sequence":"additional","affiliation":[{"name":"Tecnologico de Monterrey, Center for the Future of Cities","place":["Mexico City, Mexico"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Roberto","family":"Ponce-L\u00f3pez","sequence":"additional","affiliation":[{"name":"Tecnologico de Monterrey, Center for the Future of Cities","place":["Mexico City, Mexico"]},{"name":"Tecnologico de Monterrey, School of Government and Public Transformation","place":["Monterrey, Mexico"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,9,23]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"e2026160118","DOI":"10.1073\/pnas.2026160118","article-title":"Estimating experienced racial segregation in US cities using large-scale GPS data","volume":"118","author":"Athey","year":"2021","journal-title":"Proc. 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