Using google street view for systematic observation of the built environment: analysis of spatio-temporal instability of imagery dates

Abstract

BackgroundRecently, Google Street View (GSV) has been examined as a tool for remotely conducting systematic observation of the built environment. Studies have found it offers benefits over in-person audits, including efficiency, safety, cost, and the potential to expand built environment research to larger areas and more places globally. However, one limitation has been the lack of documentation on the date of imagery collection. In 2011, Google began placing a date stamp on images which now enables investigation of this concern. This study questions the spatio-temporal stability in the GSV date stamp. Specifically, is the imagery collected contemporaneously? If not, how frequently and where is imagery from different time periods woven together to represent environmental conditions in a particular place. Furthermore, how much continuity exists in imagery for a particular time period? Answering these questions will provide guidance on the use of GSV as a tool for built environment audits.MethodsGSV was used to virtually “drive” five sites that are a part of the authors’ ongoing studies. Each street in the sites was “driven” one mouse-click at a time while observing the date stamp on each image. Every time the date stamp changed, this “disruption” was marked on the map. Every street segment in the site was coded by the date the imagery for that segment was collected. Spatial query and descriptive statistics were applied to understand the spatio-temporal patterns of imagery dates.ResultsSpatio-temporal instability is present in the dates of GSV imagery. Of the 353 disruptions, 82.4% occur close to (<25 m) intersections. The remainder occurs inconsistently in other locations. The extent of continuity for a set of images collected with the same date stamp ranged from 3.13 m to 3373.06 m, though the majority of continuous segments were less than 400 m.ConclusionGSV offers some benefits over traditional built environment audits. However, this investigation empirically identifies a previously undocumented limitation in its application for research. Imagery dates can change often and without warning. Caution should be used at intersections where these disruptions are most likely to occur, though caution should be used everywhere when using GSV as a data collection tool.

Assessing Walking and Cycling Environments in the Streets of Madrid: Comparing On-Field and Virtual Audits

“…However, the differences shown for cycling infrastructure (cycle storage) may be a temporal issue, whereby new cycling infrastructure (e.g., bicycle parking) in Madrid were not present when the Google Street View imagery was taken. In summary, our findings are compatible with the work of other studies, 45 that have found that the more subjective characteristics (e.g., sidewalk conditions) have lower agreement between virtual and physical audits. However, in our findings view aesthetics and streetscape aesthetics showed an acceptable agreement.…”

Charting Disaster Recovery via Google Street View: A Social Science Perspective on Challenges Raised by the Fukushima Nuclear Disaster

“…Spatiotemporal instability (Curtis et al 2013) in the Fukushima GSV dataset makes this problematic, however. Signs and barriers at the entrances to highly contaminated areas may suddenly (re)appear or disappear as one transitions without warning from a set of photographs taken at one point in time to imagery of the same place shot months or years later, and other features may disappear completely as images are updated and replaced with newer ones.…”

“…Indeed, as outlined in Sect. 3 the possibility for GSV to chart recovery from tornadoes, hurricanes, and wildfires has been evaluated (Curtis et al 2013), with Curtis et al (2007) advocating the importance of tracking community return as a means of building resilience post-disaster. Given that the Japanese government is working towards the goal of decontamination in order to resettle at least some of those evacuated from their homes after the 2011 nuclear disaster (Ministry of Environment 2015), it is worth exploring whether GSV tracking over time could be extended to the decontamination and rehabilitation of radioactively-contaminated landscapes as well as natural disaster recovery in order to assess or at least keep abreast of progress.…”

“…Based on research of this nature carried out in the United States that explores recovery from tornadoes, hurricanes, and wildfires (Curtis and Mills 2012;Curtis et al 2013), Curtis et al (2013) suggest GSV has potential as a means of remotely tracking post-disaster recovery, but users should exercise caution and pay careful attention to the ''spatiotemporal instability'' (changes in image dates) that may introduce errors into tracking recovery. Curtis et al (2015) add that reliance on GSV restricts the researcher to the available imagery and discourages collection and integration of independent, field-based data.…”

“…There is therefore an emerging interest in the role that Google Street View (GSV) can play in remote assessment of recovery from disastrous events (Curtis et al 2013) in a less logistical-and cost-intensive way. This study evaluates the possibility of using GSV to track recovery from a disaster such as Fukushima where the risk to humans may not be immediately visible, where there is significant subjectivity around what constitutes adequate recovery, and where citizens' and decision makers' values and perceptions heavily influence how the issue is viewed.…”