The Promise, Practicalities, and Perils of Virtually Auditing Neighborhoods Using Google Street View

Michael D. M. Bader, Stephen J. Mooney, Blake Bennett, Andrew Rundle

Tóm tắt

In-person audits to collect data on neighborhood characteristics offer opportunities to study the mechanisms that link neighborhood conditions to unequal outcomes for individuals and communities, but the expense and logistical difficulties associated with conducting neighborhood audits have limited their use. The images collected by Google Street View provide a promising alternative for researchers to measure neighborhood environments across cities and to examine how neighborhood conditions vary across a wider geographic scope. We describe the benefits of using “virtual” neighborhood audits and discuss the practicalities of collecting data from virtual audits. We provide an example of individual- and neighborhood-level inequality in the distribution of disorder for older adults across four cities: New York, San Jose, Philadelphia, and Detroit. Despite the promise of virtual audits, they also introduce perils that must be addressed as research progresses; we introduce and discuss those perils here.

Từ khóa


Tài liệu tham khảo

adaptlab. 2012. Google Street View Project. Available from http://adaptlab.org/gallery/104-2/.

10.1109/MC.2010.170

10.1177/0081175013516749

10.1016/j.healthplace.2014.10.012

10.2105/AJPH.2015.302951

10.15195/v3.a8

Bayer Ada-Helen, Harper Leon. 2000. Fixing to stay: A national survey of housing and home modification issues. Washington, DC: AARP. Available from http://assets.aarp.org/rgcenter/il/home_mod.pdf.

10.1177/0022427810365906

Carter Woody, 1995, Project on human development in Chicago neighborhoods (PHDCN): Systematic social observation, inter-university consortium for political and social research study 13578

10.1257/aer.20150572

10.1016/j.maturitas.2009.07.011

10.1093/aje/kwn185

10.1016/j.healthplace.2010.08.007

10.1016/j.landurbplan.2006.06.008

10.1559/152304010790588043

10.1093/jurban/jtg065

10.1111/j.1749-6632.2009.05333.x

Douglas Paul. 2009. Behind the scenes with Google Street View. TechRadar. Available from http://www.techradar.com.

10.1207/s15326985ep3401_3

Farber Nicholas, 2011, Aging in place: A state survey of livability policies and practices

10.1145/2470654.2470744

10.1145/2642918.2647403

10.1177/0003122414535774

Kennan Teresa A. 2010. Home and community preferences of the 45+ population. Washington, DC: AARP. Available from http://assets.aarp.org/rgcenter/general/home-community-services-10.pdf.

10.1016/S0749-3797(03)00021-7

Klinenberg Eric, 2003, Heat wave: A social autopsy of disaster in Chicago

Kneebone Elizabeth, 2015, Confronting suburban poverty in America

10.1126/science.1224648

10.1056/NEJMsa1103216

10.3928/19404921-20110802-01

10.1093/aje/kwu180

10.1097/EDE.0000000000000274

10.1093/aje/kwm040

10.1111/j.1469-7610.2012.02565.x

10.1007/BF02511883

10.1007/BF00922690

10.1016/S0749-3797(02)00498-1

10.1111/0081-1750.00059

10.2307/270816

10.1002/9780470316696

10.1016/j.amepre.2010.09.034

10.7208/chicago/9780226733883.001.0001

10.1086/210356

10.1177/019027250406700401

10.1111/j.1467-9531.2009.01221.x

Schafer Joseph L. 2015. Estimation/multiple imputation for mixed categorical and continuous data [software package]. Available from https://rdrr.io/cran/mix/.

10.1111/j.1745-9125.2010.00198.x

Shet Vinay. 2014. Go back in time with Street View. Available from https://blog.google/products/maps/go-back-in-time-with-street-view/.

10.1007/978-94-007-2309-2_3

10.1177/0022427884021004003

10.1123/jpah.9.5.689

10.1016/j.amepre.2008.01.024