A Multiscale Assessment of the Impact of Perceived Safety from Street View Imagery on Street Crime

References

• Andresen, M. A., and N. Malleson. 2013. Spatial heterogeneity in crime analysis. In Crime modeling and mapping using geospatial technologies, ed. M. Leitner, 3–23. Dordrecht, The Netherlands: Springer.
   Google Scholar
• Austin, D., L. Furr, and M. Spine. 2002. The effects of neighborhood conditions on perceptions of safety. Journal of Criminal Justice 30 (5):417–27. doi: 10.1016/S0047-2352(02)00148-4.
   Web of Science ®Google Scholar
• Bernasco, W., and R. Block. 2011. Robberies in Chicago: A block-level analysis of the influence of crime generators, crime attractors, and offender anchor points. Journal of Research in Crime and Delinquency 48 (1):33–57. doi: 10.1177/0022427810384135.
   Web of Science ®Google Scholar
• Bernasco, W., and H. Elffers. 2010. Statistical analysis of spatial crime data. In Handbook of quantitative criminology, ed. A. R. Piquero and D. Weisburd, 699–724. New York: Springer.
   Google Scholar
• Biljecki, F., and K. Ito. 2021. Street view imagery in urban analytics and GIS: A review. Landscape and Urban Planning 215:104217. doi: 10.1016/j.landurbplan.2021.104217.
   Web of Science ®Google Scholar
• Brantingham, P., and P. Brantingham. 1995. Criminality of place. European Journal on Criminal Policy and Research 3 (3):5–26. doi: 10.1007/BF02242925.
   Google Scholar
• Braungart, M. M., R. G. Braungart, and W. J. Hoyer. 1980. Age, sex, and social factors in fear of crime. Sociological Focus 13 (1):55–66. doi: 10.1080/00380237.1980.10570360.
   Web of Science ®Google Scholar
• Browning, C. R. 2002. The span of collective efficacy: Extending social disorganization theory to partner violence. Journal of Marriage and Family 64 (4):833–50. doi: 10.1111/j.1741-3737.2002.00833.x.
   Web of Science ®Google Scholar
• Brunton‐Smith, I., and P. Sturgis. 2011. Do neighborhoods generate fear of crime? An empirical test using the British Crime Survey. Criminology 49 (2):331–69. doi: 10.1111/j.1745-9125.2011.00228.x.
   Web of Science ®Google Scholar
• Bursik, R. J., Jr. 1988. Social disorganization and theories of crime and delinquency: Problems and prospects. Criminology 26 (4):519–52. doi: 10.1111/j.1745-9125.1988.tb00854.x.
   Web of Science ®Google Scholar
• Chiricos, T. G. 1987. Rates of crime and unemployment: An analysis of aggregate research evidence. Social Problems 34 (2):187–212. doi: 10.2307/800715.
   Web of Science ®Google Scholar
• Cho, G., D. A. Rodríguez, and A. J. Khattak. 2009. The role of the built environment in explaining relationships between perceived and actual pedestrian and bicyclist safety. Accident; Analysis and Prevention 41 (4):692–702. doi: 10.1016/j.aap.2009.03.008.
   PubMed Web of Science ®Google Scholar
• Clark, C. R., I. Kawachi, L. Ryan, K. Ertel, M. E. Fay, and L. F. Berkman. 2009. Perceived neighborhood safety and incident mobility disability among elders: The hazards of poverty. BMC Public Health 9 (1):162. doi: 10.1186/1471-2458-9-162.
   PubMed Web of Science ®Google Scholar
• Clarke, R. V., and M. Felson. 2017. Introduction: Criminology, routine activity, and rational choice. In Routine activity and rational choice, ed. R. V. Clarke and M. Felson, 1–14. London and New York: Routledge.
   Google Scholar
• Cook, P. J. 1983. Robbery in the United States—An analysis of recent trends and patterns. Accessed July 18, 2022. https://www.ojp.gov/pdffiles1/Digitization/91149NCJRS.pdf.
   Google Scholar
• Cordts, M., M. Omran, S. Ramos, T. Rehfeld, M. Enzweiler, R. Benenson, U. Franke, S. Roth, and B. Schiele. 2016. The cityscapes dataset for semantic urban scene understanding. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 3213–23. https://openaccess.thecvf.com/content_cvpr_2016/papers/Cordts_The_Cityscapes_Dataset_CVPR_2016_paper.pdf
   Google Scholar
• Cozens, P. M. 2011. Urban planning and environmental criminology: Towards a new perspective for safer cities. Planning Practice and Research 26 (4):481–508. doi: 10.1080/02697459.2011.582357.
   Google Scholar
• Curtis, J. W., E. Shiau, B. Lowery, D. Sloane, K. Hennigan, and A. Curtis. 2014. The prospects and problems of integrating sketch maps with geographic information systems to understand environmental perception: A case study of mapping youth fear in Los Angeles gang neighborhoods. Environment and Planning B: Planning and Design 41 (2):251–71. doi: 10.1068/b38151.
   Web of Science ®Google Scholar
• Day, K. 2001. Constructing masculinity and women’s fear in public space in Irvine, California. Gender, Place and Culture: A Journal of Feminist Geography 8 (2):109–27. doi: 10.1080/09663690120050742.
   Google Scholar
• Diez Roux, A. V. 2003. The examination of neighborhood effects on health: Conceptual and methodological issues related to the presence of multiple levels of organization. In Neighborhoods and health, ed. I. Kawachi and L. F. Berkman, 45–64. Oxford, UK: Oxford University Press.
   Google Scholar
• Doran, B. J., and B. G. Lees. 2005. Investigating the spatiotemporal links between disorder, crime, and the fear of crime. The Professional Geographer 57 (1):1–12. doi: 10.1111/j.0033-0124.2005.00454.x.
   Web of Science ®Google Scholar
• Dubey, A., N. Naik, D. Parikh, R. Raskar, and C. A. Hidalgo. 2016. Deep learning the city: Quantifying urban perception at a global scale. In Computer Vision – ECCV 2016. ECCV 2016. Lecture notes in computer science, ed. B. Leibe, J. Matas, N. Sebe, and M. Welling, 196–212. Cham, Switzerland: Springer.
   Google Scholar
• Farrall, S. 2004. Revisiting crime surveys: Emotional responses without emotions? Or look back at anger. International Journal of Social Research Methodology 7 (2):157–71. doi: 10.1080/1304557021000024767.
   Google Scholar
• Fattah, E. A., and V. F. Sacco. 2012. Crime and victimization of the elderly. New York: Springer-Verlag.
   Google Scholar
• FBI. 2010. Report. Accessed July 25, 2019. http://os.cqpress.com/citycrime/2011/City_Lo-Hi_2011.pdf.
   Google Scholar
• Ferraro, K. F., and R. LaGrange. 2017. The measurement of fear of crime. In The fear of crime, ed. J. Ditton and S. Farrall, 277–308. London and New York: Routledge.
   Google Scholar
• Fisher, B. S., and J. L. Nasar. 1992. Fear of crime in relation to three exterior site features: Prospect, refuge, and escape. Environment and Behavior 24 (1):35–65. doi: 10.1177/0013916592241002.
   Web of Science ®Google Scholar
• Foster, S., B. Giles-Corti, and M. Knuiman. 2010. Neighbourhood design and fear of crime: A social-ecological examination of the correlates of residents’ fear in new suburban housing developments. Health & Place 16 (6):1156–65. doi: 10.1016/j.healthplace.2010.07.007.
   PubMed Web of Science ®Google Scholar
• Fotheringham, A. S., and D. W. S. Wong. 1991. The modifiable areal unit problem in multivariate statistical analysis. Environment and Planning A: Economy and Space 23 (7):1025–44. doi: 10.1068/a231025.
   Web of Science ®Google Scholar
• Fox, A. 2017. The FBI’s 10 most dangerous cities, by region. Gov1. Accessed July 15, 2022. https://www.gov1.com/public-safety/articles/the-fbis-10-most-dangerous-cities-by-region-b8bvKm2v4rP8Zynz/.
   Google Scholar
• Fuhrmann, S., N. T. Huynh, and R. Scholz. 2013. Comparing fear of crime and crime statistics on a university campus. In Crime modeling and mapping using geospatial technologies, ed. M. Leitner, 319–37. Dordrecht, The Netherlands: Springer.
   Google Scholar
• Gabriel, U., and W. Greve. 2003. Fear of crime: Towards a psychological approach. British Journal of Criminology 43 (3):600–14. doi: 10.1093/bjc/43.3.600.
   Web of Science ®Google Scholar
• Garofalo, J. 1981. The fear of crime: Causes and consequences. The Journal of Criminal Law and Criminology 72 (2):839. doi: 10.2307/1143018.
   Web of Science ®Google Scholar
• Groff, E. R., and B. Lockwood. 2014. Criminogenic facilities and crime across street segments in Philadelphia: Uncovering evidence about the spatial extent of facility influence. Journal of Research in Crime and Delinquency 51 (3):277–314. doi: 10.1177/0022427813512494.
   Web of Science ®Google Scholar
• Groff, E. R., D. Weisburd, and S.-M. Yang. 2010. Is it important to examine crime trends at a local “micro” level? A longitudinal analysis of street to street variability in crime trajectories. Journal of Quantitative Criminology 26 (1):7–32. doi: 10.1007/s10940-009-9081-y.
   Web of Science ®Google Scholar
• Guo, J., H. He, T. He, L. Lausen, M. Li, H. Lin, X. Shi, C. Wang, J. Xie, and S. Zha. 2020. GluonCV and GluonNLP: Deep learning in computer vision and natural language processing. Journal of Machine Learning Research 21 (23):1–7.
   PubMedGoogle Scholar
• Haberman, C. P., and J. H. Ratcliffe. 2015. Testing for temporally differentiated relationships among potentially criminogenic places and census block street robbery counts. Criminology 53 (3):457–83. doi: 10.1111/1745-9125.12076.
   Web of Science ®Google Scholar
• Haberman, C. P., E. T. Sorg, and J. H. Ratcliffe. 2018. The seasons they are a changin’: Testing for seasonal effects of potentially criminogenic places on street robbery. Journal of Research in Crime and Delinquency 55 (3):425–59. doi: 10.1177/0022427818758375.
   Web of Science ®Google Scholar
• Hale, C. 1996. Fear of crime: A review of the literature. International Review of Victimology 4 (2):79–150. doi: 10.1177/026975809600400201.
   Google Scholar
• Hamilton, M., F. Salim, E. Cheng, and S. L. Choy. 2011. Transafe: A crowdsourced mobile platform for crime and safety perception management. ACM SIGCAS Computers and Society 41 (2):32–37. doi: 10.1145/2095272.2095275.
   Google Scholar
• Hanslmaier, M. 2013. Crime, fear and subjective well-being: How victimization and street crime affect fear and life satisfaction. European Journal of Criminology 10 (5):515–33. doi: 10.1177/1477370812474545.
   Web of Science ®Google Scholar
• Harvey, C., L. Aultman-Hall, S. E. Hurley, and A. Troy. 2015. Effects of skeletal streetscape design on perceived safety. Landscape and Urban Planning 142:18–28. doi: 10.1016/j.landurbplan.2015.05.007.
   Web of Science ®Google Scholar
• Heider, F. 1982. The psychology of interpersonal relations. Hillsdale, NJ: Lawrence Erlbaum.
   Google Scholar
• Hinkle, J. C. 2015. Emotional fear of crime vs. perceived safety and risk: Implications for measuring “fear” and testing the broken windows thesis. American Journal of Criminal Justice 40 (1):147–68. doi: 10.1007/s12103-014-9243-9.
   Web of Science ®Google Scholar
• Hipp, J. R. 2007. Block, tract, and levels of aggregation: Neighborhood structure and crime and disorder as a case in point. American Sociological Review 72 (5):659–80. doi: 10.1177/000312240707200501.
   Web of Science ®Google Scholar
• Hipp, J. R., S. Lee, D. Ki, and J. H. Kim. 2022. Measuring the built environment with Google Street View and machine learning: Consequences for crime on street segments. Journal of Quantitative Criminology 38 (3):537–65. doi: 10.1007/s10940-021-09506-9.
   Web of Science ®Google Scholar
• Innes, M. 2004. Signal crimes and signal disorders: Notes on deviance as communicative action 1. The British Journal of Sociology 55 (3):335–55. doi: 10.1111/j.1468-4446.2004.00023.x.
   PubMed Web of Science ®Google Scholar
• Jackson, J. 2004. Experience and expression: Social and cultural significance in the fear of crime. British Journal of Criminology 44 (6):946–66. doi: 10.1093/bjc/azh048.
   Web of Science ®Google Scholar
• Jackson, J., and E. Gray. 2010. Functional fear and public insecurities about crime. British Journal of Criminology 50 (1):1–22. doi: 10.1093/bjc/azp059.
   Web of Science ®Google Scholar
• Jiang, B., C. N. S. Mak, H. Zhong, L. Larsen, and C. J. Webster. 2018. From broken windows to perceived routine activities: Examining impacts of environmental interventions on perceived safety of urban alleys. Frontiers in Psychology 9:2450. doi: 10.3389/fpsyg.2018.02450.
   PubMed Web of Science ®Google Scholar
• Jing, F., L. Liu, S. Zhou, Z. Li, J. Song, L. Wang, R. Ma, and X. Li. 2023. Exploring large-scale spatial distribution of fear of crime by integrating small sample surveys and massive street view images. Environment and Planning B: Urban Analytics and City Science 50 (4):1104–20. doi: 10.1177/23998083221135608.
   Google Scholar
• Keizer, K., S. Lindenberg, and L. Steg. 2008. The spreading of disorder. Science 322 (5908):1681–85. doi: 10.1126/science.1161405.
   PubMed Web of Science ®Google Scholar
• Kim, Y.-A., and J. R. Hipp. 2018. Physical boundaries and city boundaries: Consequences for crime patterns on street segments? Crime & Delinquency 64 (2):227–54. doi: 10.1177/0011128716687756.
   Web of Science ®Google Scholar
• Kinney, J. B., P. L. Brantingham, K. Wuschke, M. G. Kirk, and P. J. Brantingham. 2008. Crime attractors, generators and detractors: Land use and urban crime opportunities. Built Environment 34 (1):62–74. doi: 10.2148/benv.34.1.62.
   Google Scholar
• Kneeshaw-Price, S. H., B. E. Saelens, J. F. Sallis, L. D. Frank, D. E. Grembowski, P. A. Hannon, N. L. Smith, and K. C. G. Chan. 2015. Neighborhood crime-related safety and its relation to children’s physical activity. Journal of Urban Health: Bulletin of the New York Academy of Medicine 92 (3):472–89. doi: 10.1007/s11524-015-9949-0.
   PubMed Web of Science ®Google Scholar
• Kohm, S. A. 2009. Spatial dimensions of fear in a high-crime community: Fear of crime or fear of disorder? Canadian Journal of Criminology and Criminal Justice 51 (1):1–30. doi: 10.3138/cjccj.51.1.1.
   Web of Science ®Google Scholar
• Kruse, J., Y. Kang, Y.-N. Liu, F. Zhang, and S. Gao. 2021. Places for play: Understanding human perception of playability in cities using street view images and deep learning. Computers, Environment and Urban Systems 90:101693. doi: 10.1016/j.compenvurbsys.2021.101693.
   Web of Science ®Google Scholar
• Kubrin, C. E., and R. Weitzer. 2003. New directions in social disorganization theory. Journal of Research in Crime and Delinquency 40 (4):374–402. doi: 10.1177/0022427803256238.
   Web of Science ®Google Scholar
• Kyttä, M., J. Kuoppa, J. Hirvonen, E. Ahmadi, and T. Tzoulas. 2014. Perceived safety of the retrofit neighborhood: A location-based approach. Urban Design International 19 (4):311–28. doi: 10.1057/udi.2013.31.
   Web of Science ®Google Scholar
• Lan, M., L. Liu, and J. E. Eck. 2021. A spatial analytical approach to assess the impact of a casino on crime: An example of JACK Casino in downtown Cincinnati. Cities 111:103003. doi: 10.1016/j.cities.2020.103003.
   Web of Science ®Google Scholar
• Legewie, J. 2018. Living on the edge: Neighborhood boundaries and the spatial dynamics of violent crime. Demography 55 (5):1957–77. doi: 10.1007/s13524-018-0708-1.
   PubMed Web of Science ®Google Scholar
• Liu, L. 2022. Progresses and challenges of crime geography and crime analysis. In New thinking in GIScience, ed. B. Li, X. Shi, AX. Zhu, C. Wang, and H. Lin, 349–53. Singapore: Springer.
   Google Scholar
• Liu, L., H. Zhou, and M. Lan. 2022. Agglomerative effects of crime attractors and generators on street robbery? An assessment by Luojia 1-01 satellite nightlight. Annals of the American Association of Geographers 112 (2):350–67. doi: 10.1080/24694452.2021.1933888.
   Web of Science ®Google Scholar
• Lopez, N., and C. Lukinbeal. 2010. Comparing police and residents’ perceptions of crime in a Phoenix neighborhood using mental maps in GIS. Yearbook of the Association of Pacific Coast Geographers 72:33–55.
   Google Scholar
• Loukaitou-Sideris, A., and J. E. Eck. 2007. Crime prevention and active living. American Journal of Health Promotion 21 (Suppl. 4):380–89, iii. doi: 10.4278/0890-1171-21.4s.380.
   PubMed Web of Science ®Google Scholar
• Ma, L., and J. Cao. 2019. How perceptions mediate the effects of the built environment on travel behavior? Transportation 46 (1):175–97. doi: 10.1007/s11116-017-9800-4.
   Web of Science ®Google Scholar
• Maier, S. L., and B. T. DePrince. 2020. College students’ fear of crime and perception of safety: The influence of personal and university prevention measures. Journal of Criminal Justice Education 31 (1):63–81. doi: 10.1080/10511253.2019.1656757.
   Web of Science ®Google Scholar
• Mason, P., A. Kearns, and M. Livingston. 2013. “Safe going”: The influence of crime rates and perceived crime and safety on walking in deprived neighbourhoods. Social Science & Medicine 91:15–24. doi: 10.1016/j.socscimed.2013.04.011.
   PubMed Web of Science ®Google Scholar
• May, D. C., N. E. Rader, and S. Goodrum. 2010. A gendered assessment of the “threat of victimization”: Examining gender differences in fear of crime, perceived risk, avoidance, and defensive behaviors. Criminal Justice Review 35 (2):159–82. doi: 10.1177/0734016809349166.
   Google Scholar
• Mayne, S. L., K. A. Moore, T. M. Powell-Wiley, K. R. Evenson, R. Block, and K. N. Kershaw. 2018. Longitudinal associations of neighborhood crime and perceived safety with blood pressure: The Multi-Ethnic Study of Atherosclerosis (MESA). American Journal of Hypertension 31 (9):1024–32. doi: 10.1093/ajh/hpy066.
   PubMed Web of Science ®Google Scholar
• Miles, R. 2008. Neighborhood disorder, perceived safety, and readiness to encourage use of local playgrounds. American Journal of Preventive Medicine 34 (4):275–81. doi: 10.1016/j.amepre.2008.01.007.
   PubMed Web of Science ®Google Scholar
• Moore, M. H., and R. C. Trojanowicz. 1988. Policing and the fear of crime. Washington, DC: U.S. Department of Justice, National Institute of Justice.
   Google Scholar
• O’Brien, R. M. 2007. A caution regarding rules of thumb for variance inflation factors. Quality & Quantity 41 (5):673–90. doi: 10.1007/s11135-006-9018-6.
   Web of Science ®Google Scholar
• Osgood, D. W. 2000. Poisson-based regression analysis of aggregate crime rates. Journal of Quantitative Criminology 16 (1):21–43. doi: 10.1023/A:1007521427059.
   Web of Science ®Google Scholar
• Pain, R. 2000. Place, social relations and the fear of crime: A review. Progress in Human Geography 24 (3):365–87. doi: 10.1191/030913200701540474.
   Web of Science ®Google Scholar
• Pánek, J., V. Pászto, and L. Marek. 2017. Mapping emotions: Spatial distribution of safety perception in the city of Olomouc. In The rise of big spatial data. Lecture notes in geoinformation and cartography, ed. I. Ivan, A. Singleton, J. Horák, and T. Inspektor, 211–24. Cham, Switzerland: Springer.
   Google Scholar
• Pánek, J., V. Pászto, and P. Šimáček. 2018. Spatial and temporal comparison of safety perception in urban spaces: Case study of Olomouc, Opava and Jihlava. In Dynamics in GIscience GIS OSTRAVA 2017. Lecture notes in geoinformation and cartography, ed. I. Ivan, A. Singleton, J. Horák, and T. Inspektor. Cham, Switzerland: Springer.
   Google Scholar
• Perkins, C. 2009. Performative and embodied mapping. International Encyclopedia of Human Geography 8:126–32.
   Google Scholar
• Peterson, R. D., L. J. Krivo, and M. A. Harris. 2000. Disadvantage and neighborhood violent crime: Do local institutions matter? Journal of Research in Crime and Delinquency 37 (1):31–63. doi: 10.1177/0022427800037001002.
   Web of Science ®Google Scholar
• Raphael, S., and R. Winter-Ebmer. 2001. Identifying the effect of unemployment on crime. The Journal of Law and Economics 44 (1):259–83. doi: 10.1086/320275.
   Web of Science ®Google Scholar
• Rountree, P. W., and K. C. Land. 1996. Perceived risk versus fear of crime: Empirical evidence of conceptually distinct reactions in survey data. Social Forces 74 (4):1353–76. doi: 10.2307/2580354.
   Web of Science ®Google Scholar
• Salesses, P., K. Schechtner, and C. A. Hidalgo. 2013. The collaborative image of the city: Mapping the inequality of urban perception. PLoS ONE 8 (7):e68400. doi: 10.1371/journal.pone.0068400.
   PubMed Web of Science ®Google Scholar
• Schweitzer, J. H., J. W. Kim, and J. R. Mackin. 1999. The impact of the built environment on crime and fear of crime in urban neighborhoods. Journal of Urban Technology 6 (3):59–73. doi: 10.1080/10630739983588.
   Web of Science ®Google Scholar
• Shaw, C. R., and H. D. McKay. 1942. Juvenile delinquency and urban areas. In Understanding deviance: Connecting classical and contemporary perspectives, ed. T. L. Anderson, 106–27. London and New York: Routledge/Taylor & Francis Group.
   Google Scholar
• Shaw, C. R., and H. D. McKay. 2010. Juvenile delinquency and urban areas: A study of rates of delinquency in relation to differential characteristics of local communities in American cities (1969). London and New York: Routledge.
   Google Scholar
• Solymosi, R., K. Bowers, and T. Fujiyama. 2015. Mapping fear of crime as a context‐dependent everyday experience that varies in space and time. Legal and Criminological Psychology 20 (2):193–211. doi: 10.1111/lcrp.12076.
   Google Scholar
• Solymosi, R., D. Buil-Gil, L. Vozmediano, and I. S. Guedes. 2021. Towards a place-based measure of fear of crime: A systematic review of app-based and crowdsourcing approaches. Environment and Behavior 53 (9):1013–44. doi: 10.1177/0013916520947114.
   Web of Science ®Google Scholar
• Su, N., W. Li, and W. Qiu. 2023. Measuring the associations between eye-level urban design quality and on-street crime density around New York subway entrances. Habitat International 131:102728. doi: 10.1016/j.habitatint.2022.102728.
   Web of Science ®Google Scholar
• Toet, A., and M. G. van Schaik. 2012. Effects of signals of disorder on fear of crime in real and virtual environments. Journal of Environmental Psychology 32 (3):260–76. doi: 10.1016/j.jenvp.2012.04.001.
   Web of Science ®Google Scholar
• Traunmueller, M., P. Marshall, and L. Capra. 2016. “ … When you’re a stranger” evaluating safety perceptions of (un) familiar urban places. In Proceedings of the Second International Conference on IoT in Urban Space, 71–77. New York: ACM. doi: 10.1145/2962735.2962761.
   Google Scholar
• U.S. Census Bureau 2019. Unemployment rate: 67. Accessed September 1, 2021. https://www2.census.gov/programs-surveys/acs/tech_docs/subject_definitions/2019_ACSSubjectDefinitions.pdf.
   Google Scholar
• Valentine, G. 1990. Women’s fear and the design of public space. Built Environment 16 (4):288–303.
   Google Scholar
• Wakefield, A., and J. Fleming. 2008. The Sage dictionary of policing. London: Sage.
   Google Scholar
• Wilson, J. Q., and G. L. Kelling. 1982. Broken windows. Atlantic Monthly 249 (3):29–38.
   Google Scholar
• Wong, D. W. S. 2004. The modifiable areal unit problem (MAUP). In WorldMinds: Geographical perspectives on 100 problems: Commemorating the 100th anniversary of the Association of American Geographers 1904–2004, ed. D. G. Janelle, B. Warf, and K. Hansen, 571–75. Dordrecht, The Netherlands: Springer.
   Google Scholar
• Zhang, F., Z. Fan, Y. Kang, Y. Hu, and C. Ratti. 2021. “Perception bias”: Deciphering a mismatch between urban crime and perception of safety. Landscape and Urban Planning 207:104003. doi: 10.1016/j.landurbplan.2020.104003.
   Web of Science ®Google Scholar
• Zhang, F., B. Zhou, L. Liu, Y. Liu, H. H. Fung, H. Lin, and C. Ratti. 2018. Measuring human perceptions of a large-scale urban region using machine learning. Landscape and Urban Planning 180:148–60. doi: 10.1016/j.landurbplan.2018.08.020.
   Web of Science ®Google Scholar
• Zhang, Y., L. Cai, G. Song, L. Liu, and C. Zhu. 2022. From residential neighborhood to activity space: The effects of educational segregation on crime and their moderation by social context. Annals of the American Association of Geographers 112 (8):2393–2412. doi: 10.1080/24694452.2022.2060793.
   Web of Science ®Google Scholar
• Zhao, H., J. Shi, X. Qi, X. Wang, and J. Jia. 2017. Pyramid scene parsing network. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2881–90. https://openaccess.thecvf.com/content_cvpr_2017/html/Zhao_Pyramid_Scene_Parsing_CVPR_2017_paper.html
   Google Scholar
• Zhou, H., L. Liu, M. Lan, B. Yang, and Z. Wang. 2019. Assessing the impact of nightlight gradients on street robbery and burglary in Cincinnati of Ohio State, USA. Remote Sensing 11 (17):1958. doi: 10.3390/rs11171958.
   Web of Science ®Google Scholar
• Zhou, H., L. Liu, M. Lan, W. Zhu, G. Song, F. Jing, Y. Zhong, Z. Su, and X. Gu. 2021. Using Google Street View imagery to capture micro built environment characteristics in drug places, compared with street robbery. Computers, Environment and Urban Systems 88:101631. doi: 10.1016/j.compenvurbsys.2021.101631.
   Web of Science ®Google Scholar
• Zhou, H., J. Wang, and K. Wilson. 2022. Impacts of perceived safety and beauty of park environments on time spent in parks: Examining the potential of street view imagery and phone-based GPS data. International Journal of Applied Earth Observation and Geoinformation 115:103078. doi: 10.1016/j.jag.2022.103078.
   Web of Science ®Google Scholar