Research and practice method
Using Google Street View to Audit Neighborhood Environments

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Background

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.

Purpose

To assess the feasibility of using Google Street View to audit neighborhood environments.

Methods

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.

Results

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.

Conclusions

This exploratory study indicates that Google Street View can be used to audit neighborhood environments.

Introduction

The past decade has seen a rapid expansion of research on the health implications of neighborhood environment features such as aesthetics, physical disorder, social activities, and pedestrian safety. Studies have found associations between specific neighborhood characteristics and cardiovascular disease1; self-rated health2; walking and other forms of physical activity3; obesity4, 5, 6, 7, 8; lower-body functional limitations9, 10; symptoms of depression, anxiety, and conduct disorders11, 12, 13; asthma14, 15; and crime and violence.1, 16, 17

Neighborhood environment studies present practical challenges, especially in studies using large and geographically dispersed samples. Neighborhood features are commonly inventoried using survey respondent self-report, administrative data, or observer audits, and each of these strategies has benefits and limitations. Survey-based measures can be useful for assessing how residents perceive their neighborhoods; however, using respondent reports of neighborhood conditions can introduce bias because outcomes may be correlated with measurement error on the independent variable (i.e., the same-source bias problem).18 One way to address same-source bias is to field a parallel survey, administered to an independent sample, to measure neighborhood conditions.19, 20 However, the additional sample increases survey costs substantially.

Alternatively, some researchers use administrative data and GIS tools to characterize urban environments. Although spatially referenced administrative data are becoming more widely available and are clearly useful for neighborhood health studies,21 such data are usually collected to meet local administrative priorities, such as needs assessment and evaluation of service quality. Although some cities are making administrative data publicly available, data are often inconsistently available or collected using different methodologies across jurisdictions. Even in areas with rich administrative geospatial data resources, the data often do not include many neighborhood features of interest to researchers.22

Because of these disadvantages, many researchers17, 23, 24, 25, 26 have relied on neighborhood audits, also called systematic social observation. Neighborhood audits enable researchers to define theoretically relevant measures and allow assessment of reliability and validity. However, audits are time-consuming and expensive to conduct largely because of the costs of travel; as a result, they are typically limited to small, geographically circumscribed study areas.27, 28, 29 Audits may also be perceived by local residents as intrusive and can involve safety problems for research staff.30 Some studies17, 31, 32 have conducted neighborhood “windshield surveys,” in which researchers drive through a neighborhood to make observations, sometimes recording videotape for later coding. Windshield surveys may reduce concerns about the safety of research staff, but coding neighborhood characteristics from a moving vehicle provides less detail than coding on foot. Although videotape recording allows more detailed and careful coding, it also increases costs substantially.

Google Street View represents an alternative source of data on neighborhood environments. Street View, available from Google's online Maps application (maps.google.com) is a library of video footage captured by cars driven down the street. The images have been processed to provide panoramic, street-level views of city streets, in which the user can navigate forward or backward along the street, pan 360 degrees, rotate the camera vertically 290 degrees, and zoom in and out (see Figure 1). Google Street View was introduced in 2007 with coverage of a handful of cities but is being extended to new cities at a rapid pace. The image resolution varies depending on when the images were taken, with places photographed more recently being of higher resolution.

Using Google Street View, researchers can conduct “virtual” field audits of neighborhoods. The idea builds on older studies using videotaped images,17 but leverages Google's industrial-scale collection of images and information technology infrastructure.31 Street View audits can be implemented in multiple cities from one central location, eliminating travel costs as well as concerns about intrusiveness and research staff safety. Audit sessions conducted from a central computer lab also allow for better oversight and quality control because supervisors can be on-site to monitor the auditors and images of the auditor's screens (screen-shots) can be captured and archived for later quality-control review.

Little is known, however, about the feasibility of using Street View to audit neighborhood environments. To explore whether larger-scale deployment would be possible, data coded from Street View images were compared to data from a previous field audit of New York City streets.33 The objectives of this research were to identify constructs that can be measured using Google Street View, identify barriers to its use, and to build an experience base with the Street View interface on which viewing protocols can be developed. The validity of Street View was compared by neighborhood environment construct (e.g., physical disorder, social activity, support for active travel) and by the size and temporal variability of neighborhood features.

Section snippets

Methods

This study compared neighborhood measures coded from Street View images with those based on field observation in a prior study of 38 high-walkability block segments in New York City; 19 blocks from poor (≥20% poverty) and 19 blocks from nonpoor (<20% poverty) census tracts matched on neighborhood walkability.33 The use of high-walkability blocks was efficient for this exploratory study because such blocks tend to have a high density of the features typically included in neighborhood audits.

The

Results

Field audit items that are intrinsically impossible to evaluate with static video images, including noises, odors, and traffic speeds, could not be evaluated with Street View. In addition, several items from the field audit—such as a 10-minute pedestrian count, and sidewalk width—could not be replicated as administered in the field and were also excluded. Because the field audits included measures not performed in the Street View sessions, the length of time required for each audit method

Discussion

This exploratory study evaluated the feasibility, including barriers and limitations, of using Google Street View to audit neighborhood environments. Although Street View is generally limited to public spaces viewable from automobile-accessible streets, few barriers to the use of Street View were identified. Only one of the sampled 38 block faces was unavailable within Street View. Relatively few items from the field protocol—those measuring noise, odors, exact distances, and measures with a

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