Web Data Mining: Validity of Data from Google Earth for Food Retail Evaluation.
To overcome the challenge of obtaining accurate data on community food retail, we developed an innovative tool to automatically capture food retail data from Google Earth (GE). The proposed method is relevant to non-commercial use or scholarly purposes. We aimed to test the validity of web sources d...
| Published in: | Journal of Urban Health Vol. 98; no. 2; pp. 285 - 296 |
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| Main Authors: | , , , , , , , , , |
| Format: | journal article |
| Published: |
Springer Nature
Apr2021
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| Subjects: | |
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=150023706&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 150023706 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 10993460 GMF jtl: Journal of Urban Health issn: 10993460 maglogo: N pubinfo: dt: Apr2021 vid: 98 iid: 2 pid: 237 pub: Springer Nature artinfo: ui: 150023706 10.1007/s11524-020-00495-x ppf: 285 ppct: 11 formats: fmt: – @attributes: type: T – @attributes: type: P size: 852KB tig: atl: Web Data Mining: Validity of Data from Google Earth for Food Retail Evaluation. aug: au: de Menezes, Mariana Carvalho de Matos, Vanderlei Pascoal de Pina, Maria de Fátima de Lima Costa, Bruna Vieira Mendes, Larissa Loures Pessoa, Milene Cristine de Souza-Junior, Paulo Roberto Borges de Lima Friche, Amélia Augusta Caiaffa, Waleska Teixeira de Oliveira Cardoso, Letícia affil: National School of Public Health, Fiocruz-RJ, Rua Leopoldo Bulhões, 1480- Manguinhos, 21041-210, Rio de Janeiro, Brazil Instituto de Comunicação e Informação Científica e Tecnológica em Saúde, Fiocruz-RJ, Av. Brasil, 4.365 - Manguinhos, 21040-900, Rio de Janeiro, Brazil Department of Nutrition, Universidade Federal de Minas Gerais, Av. Alfredo Balena 190, 30130-100, Belo Horizonte, MG, Brazil Faculdade de Medicina, Universidade Federal de Minas Gerais. Observatório de Saúde Urbana, Av. Alfredo Balena 190, 30130-100, Belo Horizonte, MG, Brazil su: Belo Horizonte (Brazil) Rio de Janeiro (Brazil) Google Earth (Web resource) Retail industry Data mining Web services Convenience stores Test validity sug: subj: Retail industry Belo Horizonte (Brazil) Rio de Janeiro (Brazil) Convenience Stores All other miscellaneous general merchandise stores All Other Miscellaneous Store Retailers (except Tobacco Stores) All other miscellaneous store retailers (except beer and wine-making supplies stores) Data Processing, Hosting, and Related Services Data mining Web services Convenience stores Test validity Google Earth (Web resource) keyword: Food environment Food retail Geocoding services Google Earth Urban health Validation study Food environment Food retail Geocoding services Google Earth Urban health Validation study ab: To overcome the challenge of obtaining accurate data on community food retail, we developed an innovative tool to automatically capture food retail data from Google Earth (GE). The proposed method is relevant to non-commercial use or scholarly purposes. We aimed to test the validity of web sources data for the assessment of community food retail environment by comparison to ground-truth observations (gold standard). A secondary aim was to test whether validity differs by type of food outlet and socioeconomic status (SES). The study area included a sample of 300 census tracts stratified by SES in two of the largest cities in Brazil, Rio de Janeiro and Belo Horizonte. The GE web service was used to develop a tool for automatic acquisition of food retail data through the generation of a regular grid of points. To test its validity, this data was compared with the ground-truth data. Compared to the 856 outlets identified in 285 census tracts by the ground-truth method, the GE interface identified 731 outlets. In both cities, the GE interface scored moderate to excellent compared to the ground-truth data across all of the validity measures: sensitivity, specificity, positive predictive value, negative predictive value and accuracy (ranging from 66.3 to 100%). The validity did not differ by SES strata. Supermarkets, convenience stores and restaurants yielded better results than other store types. To our knowledge, this research is the first to investigate using GE as a tool to capture community food retail data. Our results suggest that the GE interface could be used to measure the community food environment. Validity was satisfactory for different SES areas and types of outlets. pubtype: Academic Journal doctype: journal article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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