Assessing Google Street View Image Availability in Latin American Cities

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Abstract

Virtual audits using Google Street View are an increasingly popular method of assessing neighborhood environments for health and urban planning research. However, the validity of these studies may be threatened by issues of image availability, image age, and variance of image age, particularly in the Global South. This study identifies patterns of Street View image availability, image age, and image age variance across cities in Latin America and assesses relationships between these measures and measures of resident socioeconomic conditions. Image availability was assessed at 530,308 near-road points within the boundaries of 371 Latin American cities described by the SALURBAL (Salud Urbana en America Latina) project. At the subcity level, mixed-effect linear and logistic models were used to assess relationships between measures of socioeconomic conditions and image availability, average image age, and the standard deviation of image age. Street View imagery was available at 239,394 points (45.1%) of the total sampled, and rates of image availability varied widely between cities and countries. Subcity units with higher scores on measures of socioeconomic conditions had higher rates of image availability (OR = 1.11 per point increase of combined index, p < 0.001) and the imagery was newer on average (− 1.15 months per point increase of combined index, p < 0.001), but image capture date within these areas varied more (0.59-month increase in standard deviation of image age per point increase of combined index, p < 0.001). All three assessed threats to the validity of Street View virtual audit studies spatially covary with measures of socioeconomic conditions in Latin American cities. Researchers should be attentive to these issues when using Street View imagery.

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Inference and Missing Data

Donald B Rubin (1976)

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Using Google Street View to audit neighborhood environments.

Julien O Teitler, Kathryn Neckerman, Michael Bader … (2010)

Research indicates that neighborhood environment characteristics such as physical disorder influence health and health behavior. In-person audit of neighborhood environments is costly and time-consuming. Google Street View may allow auditing of neighborhood environments more easily and at lower cost, but little is known about the feasibility of such data collection. To assess the feasibility of using Google Street View to audit neighborhood environments. This study compared neighborhood measurements coded in 2008 using Street View with neighborhood audit data collected in 2007. The sample included 37 block faces in high-walkability neighborhoods in New York City. Field audit and Street View data were collected for 143 items associated with seven neighborhood environment constructions: aesthetics, physical disorder, pedestrian safety, motorized traffic and parking, infrastructure for active travel, sidewalk amenities, and social and commercial activity. To measure concordance between field audit and Street View data, percentage agreement was used for categoric measures and Spearman rank-order correlations were used for continuous measures. The analyses, conducted in 2009, found high levels of concordance (≥80% agreement or ≥0.60 Spearman rank-order correlation) for 54.3% of the items. Measures of pedestrian safety, motorized traffic and parking, and infrastructure for active travel had relatively high levels of concordance, whereas measures of physical disorder had low levels. Features that are small or that typically exhibit temporal variability had lower levels of concordance. This exploratory study indicates that Google Street View can be used to audit neighborhood environments. Copyright © 2011 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.

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Can virtual streetscape audits reliably replace physical streetscape audits?

Robin Kearns, Karen Witten, Simon Opit … (2010)

There is increasing recognition that the neighborhood-built environment influences health outcomes, such as physical activity behaviors, and technological advancements now provide opportunities to examine the neighborhood streetscape remotely. Accordingly, the aims of this methodological study are to: (1) compare the efficiencies of physically and virtually conducting a streetscape audit within the neighborhood context, and (2) assess the level of agreement between the physical (criterion) and virtual (test) audits. Built environment attributes associated with walking and cycling were audited using the New Zealand Systematic Pedestrian and Cycling Environment Scan (NZ-SPACES) in 48 street segments drawn from four neighborhoods in Auckland, New Zealand. Audits were conducted physically (on-site) and remotely (using Google Street View) in January and February 2010. Time taken to complete the audits, travel mileage, and Internet bandwidth used were also measured. It was quicker to conduct the virtual audits when compared with the physical audits (χ = 115.3 min (virtual), χ = 148.5 min (physical)). In the majority of cases, the physical and virtual audits were within the acceptable levels of agreement (ICC ≥ 0.70) for the variables being assessed. The methodological implication of this study is that Google Street View is a potentially valuable data source for measuring the contextual features of neighborhood streets that likely impact on health outcomes. Overall, Google Street View provided a resource-efficient and reliable alternative to physically auditing the attributes of neighborhood streetscapes associated with walking and cycling. Supplementary data derived from other sources (e.g., Geographical Information Systems) could be used to assess the less reliable streetscape variables.

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Author and article information

Contributors

Dustin Fry: dtf34@drexel.edu

Stephen J. Mooney: sjm2186@u.washington.edu

Daniel A. Rodríguez: danrod@berkeley.edu

Waleska T. Caiaffa: caiaffa.waleska@gmail.com

Gina S. Lovasi: gsl45@drexel.edu

Journal

Journal ID (nlm-ta): J Urban Health

Journal ID (iso-abbrev): J Urban Health

Title: Journal of Urban Health : Bulletin of the New York Academy of Medicine

Publisher: Springer US (New York )

ISSN (Print): 1099-3460

ISSN (Electronic): 1468-2869

Publication date (Electronic): 3 January 2020

Publication date PMC-release: 3 January 2020

Publication date (Print): August 2020

Volume: 97

Issue: 4

Pages: 552-560

Affiliations

[1 ]GRID grid.166341.7, ISNI 0000 0001 2181 3113, Department of Epidemiology and Biostatistics, , Drexel University Dornsife School of Public Health, ; 3600 Market Street 7th Floor, Philadelphia, PA 19104 USA

[2 ]GRID grid.34477.33, ISNI 0000000122986657, Department of Epidemiology, , University of Washington School of Public Health, ; 1959 NE Pacific Street, Seattle, WA 98195 USA

[3 ]GRID grid.47840.3f, ISNI 0000 0001 2181 7878, Department of City & Regional Planning, , University of California–Berkeley College of Environmental Design, ; 230 Wurster Hall, Berkeley, CA 94720 USA

[4 ]GRID grid.8430.f, ISNI 0000 0001 2181 4888, Department of Preventive and Social Medicine, , Federal University of Minas Gerais Observatory for Urban Health in Belo Horizonte, ; Av. Alfredo Balena, 190, Belo Horizonte, CEP: 30130-100 Brazil

Article

Publisher ID: 408

DOI: 10.1007/s11524-019-00408-7

PMC ID: 7392983

PubMed ID: 31900840

SO-VID: 85ccfc30-e239-496c-8374-f3cb486007d9

License:

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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Funding

Funded by: FundRef http://dx.doi.org/10.13039/100004440, Wellcome Trust;

Award ID: 205177/Z/16/Z

Funded by: U.S. National Library of Medicine (US)

Award ID: 4R00LM012868

Award Recipient : Stephen J. Mooney

Custom metadata

ScienceOpen disciplines: Public health

Keywords: latin america,google street view,virtual audit,social observation,image availability

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ScienceOpen disciplines: Public health

Keywords: latin america, google street view, virtual audit, social observation, image availability

Assessing Google Street View Image Availability in Latin American Cities

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Special issue: Revolution and Counterrevolution in Latin America: an Aleatory Dialectic

Most cited references 11

Inference and Missing Data

Using Google Street View to audit neighborhood environments.

Can virtual streetscape audits reliably replace physical streetscape audits?

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