Web data mining: validity of data from google earth for food retail evaluation

dc.creatorMariana Carvalhode Menezes
dc.creatorLetícia de Oliveira Cardoso
dc.creatorVanderlei Pascoal de Matos
dc.creatorMaria de Fátima de Pina
dc.creatorBruna Vieira de Lima Costa
dc.creatorLarissa Loures Mendes
dc.creatorMilene Cristine Pessoa
dc.creatorPaulo Roberto Borges de Souza-Junior
dc.creatorAmélia Augusta de Lima Friche
dc.creatorWaleska Teixeira Caiaffa
dc.date.accessioned2024-03-27T19:57:21Z
dc.date.accessioned2025-09-08T22:48:25Z
dc.date.available2024-03-27T19:57:21Z
dc.date.issued2020-11-23
dc.description.sponsorshipCNPq - Conselho Nacional de Desenvolvimento Científico e Tecnológico
dc.description.sponsorshipOutra Agência
dc.format.mimetypepdf
dc.identifier.doi10.1007/s11524-020-00495-x
dc.identifier.issn1468-2869
dc.identifier.urihttps://hdl.handle.net/1843/66672
dc.languageeng
dc.publisherUniversidade Federal de Minas Gerais
dc.relation.ispartofJournal of Urban Health
dc.rightsAcesso Aberto
dc.subjectCuradoria de Dados
dc.subjectAlimentação no Contexto Urbano
dc.subjectFatores Socioeconômicos
dc.titleWeb data mining: validity of data from google earth for food retail evaluation
dc.typeArtigo de periódico
local.citation.epage295
local.citation.spage285
local.citation.volume98
local.description.resumoTo 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.
local.publisher.countryBrasil
local.publisher.departmentENF - DEPARTAMENTO DE NUTRIÇÃO
local.publisher.initialsUFMG
local.url.externahttps://link.springer.com/article/10.1007/s11524-020-00495-x

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