4.7 Article

Remote Sensing in Human Health: A 10-Year Bibliometric Analysis

期刊

REMOTE SENSING
卷 9, 期 12, 页码 -

出版社

MDPI
DOI: 10.3390/rs9121225

关键词

bibliometric analysis; remote sensing; healthcare; medicine

资金

  1. North Portugal Regional Operational Programme (NORTE) under PORTUGAL [NORTE-01-0145-FEDER-000016]
  2. European Regional Development Fund (ERDF)

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A mixed methods bibliometric analysis was performed to ascertain the characteristic of scientific literature published in a 10-year period (2007-2016) regarding the application of remote sensing data in human health. A search was performed on the Scopus database, followed by manual revision using synthesis studies' techniques, requiring the authors to sort through more than 8000 medical concepts to create the query, and to manually select relevant papers from over 2000 documents. From the initial 2752 papers identified, 520 articles were selected for analysis, showing that the United States ranked first, with a total of 250 (48.1% of the total) documents, followed by France and the United Kingdom, with 67 (12.9% of the total) and 54 (10.4% of the total) documents, respectively. When considering authorship, the top three authors were Vounatsou P (22 articles), Utzinger J (19 articles), and Vignolles C (13 articles). Regarding disease-specific keywords, malaria, dengue, and schistosomiasis were the most frequent keywords, occurring 142, 34, and 24 times, respectively. For some infectious diseases and other highly pathogenic or emerging infectious diseases, remote sensing has become a very powerful instrument. Also, several studies relate different environmental factors retrieved by remote sensing data with other diseases, such as asthma exacerbations. Health-related remote sensing publications are increasing and this paper highlights the importance of these related technologies toward better information and, ideally, better provision of healthcare. On the other hand, this paper provides an overall picture of the state of the research regarding the application of remote sensing data in human health and identifies the most active stakeholders e.g., authors and institutions in the field, informing possible new collaboration research groups.

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