{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T10:03:49Z","timestamp":1769162629789,"version":"3.49.0"},"reference-count":70,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2022,6,23]],"date-time":"2022-06-23T00:00:00Z","timestamp":1655942400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"European Union","award":["952377"],"award-info":[{"award-number":["952377"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Background: Often combined with other traditional and non-traditional types of data, geospatial sensing data have a crucial role in public health studies. We conducted a systematic narrative review to broaden our understanding of the usage of big geospatial sensing, ancillary data, and related spatial data infrastructures in public health studies. Methods: English-written, original research articles published during the last ten years were examined using three leading bibliographic databases (i.e., PubMed, Scopus, and Web of Science) in April 2022. Study quality was assessed by following well-established practices in the literature. Results: A total of thirty-two articles were identified through the literature search. We observed the included studies used various data-driven approaches to make better use of geospatial big data focusing on a range of health and health-related topics. We found the terms \u2018big\u2019 geospatial data and geospatial \u2018big data\u2019 have been inconsistently used in the existing geospatial sensing studies focusing on public health. We also learned that the existing research made good use of spatial data infrastructures (SDIs) for geospatial sensing data but did not fully use health SDIs for research. Conclusions: This study reiterates the importance of interdisciplinary collaboration as a prerequisite to fully taking advantage of geospatial big data for future public health studies.<\/jats:p>","DOI":"10.3390\/rs14132996","type":"journal-article","created":{"date-parts":[[2022,6,23]],"date-time":"2022-06-23T22:43:00Z","timestamp":1656024180000},"page":"2996","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Big Geospatial Data or Geospatial Big Data? A Systematic Narrative Review on the Use of Spatial Data Infrastructures for Big Geospatial Sensing Data in Public Health"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7263-2697","authenticated-orcid":false,"given":"Keumseok","family":"Koh","sequence":"first","affiliation":[{"name":"Department of Geography, Faculty of Social Sciences, The University of Hong Kong, Hong Kong 999077, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4865-6482","authenticated-orcid":false,"given":"Ayaz","family":"Hyder","sequence":"additional","affiliation":[{"name":"Division of Environmental Health Sciences, College of Public Health, and Translational Data Analytics Institute, The Ohio State University, Columbus, OH 43210, USA"}]},{"given":"Yogita","family":"Karale","sequence":"additional","affiliation":[{"name":"Division of Environmental Health Sciences, College of Public Health, The Ohio State University, Columbus, OH 43210, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2400-6303","authenticated-orcid":false,"given":"Maged N.","family":"Kamel Boulos","sequence":"additional","affiliation":[{"name":"Institute for Preventive Medicine and Public Health, School of Medicine (FMUL), University of Lisbon, 1649-028 Lisbon, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2022,6,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1177\/0309132513481014","article-title":"Sonic geographies: Exploring phonographic methods","volume":"38","author":"Gallagher","year":"2014","journal-title":"Prog. 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