Abstract
Neighborhood physical disorder manifests in many different ways, from litter and graffiti, to abandoned cars and broken windows. The effects of physical disorder are also varied, from limiting recreational activity for both young and elderly neighborhood residents, to creating a discount effect on housing prices. Methods for capturing physical disorder in neighborhoods often include in-person observation, the use of virtual street audits, windshield tours, and satellite imagery. The purpose of this chapter is to explore how small unmanned aerial systems can be used to capture physical disorder in neighborhoods. In addition, we discuss a basic analytical framework for quantifying disorder and detecting problematic areas within the community. Limitations and implications for urban and environmental planning are discussed.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Anselin, L. (2002). Under the hood Issues in the specification and interpretation of spatial regression models. Agricultural Economics, 27(3):247–267.
Anselin, L. (1995). Local indicators of spatial association—LISA. Geographical Analysis, 27(2), 93–115.
Anselin, L., & Rey, S. (2014). Modern spatial econometrics in practice: A guide to GeoDa, GeoDaSpace and PySAL. Chicago: GeoDa Press.
Brewer, C., & Campbell, A. J. (1998). Beyond graduated circles: Varied point symbols for representing quantitative data on maps. Cartographic Perspectives, (29):6–25.
Caughy, M. O., O’Campo, P. J., & Patterson, J. (2001). A brief observational measure for urban neighborhoods. Health & Place, 7(3), 225–236.
Charreire, H., Mackenbach, J. D., Ouasti, M., Lakerveld, J., Compernolle, S., Ben-Rebah, M., & Oppert, J. M. (2014). Using remote sensing to define environmental characteristics related to physical activity and dietary behaviours: A systematic review (the SPOTLIGHT project). Health & Place, 25, 1–9.
Cohen, D., Spear, S., Scribner, R., Kissinger, P., Mason, K., & Wildgen, J. (2000). “ Broken windows” and the risk of gonorrhea. American Journal of Public Health, 90(2), 230.
Douglas, J. A., Briones, M. D., Bauer, E. Z., Trujillo, M., Lopez, M., & Subica, A. M. (2018). Social and environmental determinants of physical activity in urban parks: Testing a neighborhood disorder model. Preventive Medicine, 109, 119–124.
Dykes, J., MacEachren, A. M., & Kraak, M. J. (2005). Exploring geovisualization. Amsterdam: Elsevier.
Estes, C. (2018). Can phoenix’s sunnyslope community become a tourist destination? KJZZ. Retrieved March 14, 2019, from https://tinyurl.com/ybcgs5j6
Fischer, H. (2016). New law allows drones to photograph people basking in their back yards. Arizona Capitol Times. Retrieved April 24, 2018, from https://tinyurl.com/y7vvxbnq
Franzini, L., Caughy, M. O. B., Nettles, S. M., & O’Campo, P. (2008). Perceptions of disorder: Contributions of neighborhood characteristics to subjective perceptions of disorder. Journal of Environmental Psychology, 28(1), 83–93.
Franzini, L., Elliott, M. N., Cuccaro, P., Schuster, M., Gilliland, M. J., Grunbaum, J. A., & Tortolero, S. R. (2009). Influences of physical and social neighborhood environments on children’s physical activity and obesity. American Journal of Public Health, 99(2), 271–278.
Getis, A., & Ord, J. K. (1996). Local spatial statistics: An overview. In Spatial analysis: Modelling in a GIS environment (Vol. 374, pp. 261–277). Bristol: GeoInformation International.
Grubesic, T. H. (2008). Zip codes and spatial analysis: Problems and prospects. Socio-Economic Planning Sciences, 42(2), 129–149.
Grubesic, T. H., Wallace, D., Chamberlain, A. W., & Nelson, J. R. (2018). Using unmanned aerial systems (UAS) for remotely sensing physical disorder in neighborhoods. Landscape and Urban Planning, 169, 148–159.
Hallgren, K. A. (2012). Computing inter-rater reliability for observational data: An overview and tutorial. Tutorials in Quantitative Methods for Psychology, 8(1), 23.
Harcourt, B.E. (2001). Illusion of Order. The False Promise of Broken Windows Policing. Harvard University Press, Cambridge, MA.
Herwig, C. (2016). Keeping Earth up to date and looking great. Googleblog. Retrieved May 16, 2018, from https://tinyurl.com/y9gj3dqb
Hill, T. D., Ross, C. E., & Angel, R. J. (2005). Neighborhood disorder, psychophysiological distress, and health. Journal of Health and Social Behavior, 46(2), 170–186.
Hoeben, E. M., Steenbeek, W., & Pauwels, L. J. (2018). Measuring disorder: Observer bias in systematic social observations at streets and neighborhoods. Journal of Quantitative Criminology, 34(1), 221–249.
Inzerillo, L., Di Mino, G., & Roberts, R. (2018). Image-based 3D reconstruction using traditional and UAV datasets for analysis of road pavement distress. Automation in Construction, 96, 457–469.
Janetsky, M. (2018). ‘Highway for bad things’: Phoenix tries closing alleys after neighbors complain of crime. Arizona Republic. Retrieved from https://tinyurl.com/y8tor8cl
Jelinski, D. E., & Wu, J. (1996). The modifiable areal unit problem and implications for landscape ecology. Landscape Ecology, 11(3), 129–140.
Jones, M., Pebley, A. R., & Sastry, N. (2011). Eyes on the block: Measuring urban physical disorder through in-person observation. Social Science Research, 40(2), 523–537.
Kelling, G. L., & Coles, C. M. (1997). Fixing broken windows: Restoring order and reducing crime in our communities. Simon and Schuster.
Keyes, K. M., McLaughlin, K. A., Koenen, K. C., Goldmann, E., Uddin, M., & Galea, S. (2012). Child maltreatment increases sensitivity to adverse social contexts: Neighborhood physical disorder and incident binge drinking in Detroit. Drug and Alcohol Dependence, 122(1–2), 77–85.
LaDeau, S. L., Allan, B. F., Leisnham, P. T., & Levy, M. Z. (2015). The ecological foundations of transmission potential and vector-borne disease in urban landscapes. Functional Ecology, 29(7), 889–901.
Leibler, J. H., Zakhour, C. M., Gadhoke, P., & Gaeta, J. M. (2016). Zoonotic and vector-borne infections among urban homeless and marginalized people in the United States and Europe, 1990–2014. Vector-Borne and Zoonotic Diseases, 16(7), 435–444.
Manfreda, S., McCabe, M. F., Miller, P. E., Lucas, R., Pajuelo Madrigal, V., Mallinis, G., & Müllerová, J. (2018). On the use of unmanned aerial systems for environmental monitoring. Remote sensing, 10(4), 641.
Molnar, B. E., Gortmaker, S. L., Bull, F. C., & Buka, S. L. (2004). Unsafe to play? Neighborhood disorder and lack of safety predict reduced physical activity among urban children and adolescents. American Journal of Health Promotion, 18(5), 378–386.
Mooney, S. J., Bader, M. D., Lovasi, G. S., Neckerman, K. M., Teitler, J. O., & Rundle, A. G. (2014). Validity of an ecometric neighborhood physical disorder measure constructed by virtual street audit. American Journal of Epidemiology, 180(6), 626–635.
Ogden, N. H. (2016). Emerging challenges of vector-borne diseases and cities: Vector-borne disease, climate change and urban design. Canada Communicable Disease Report, 42(10), 202.
Openshaw, S. (1984). Ecological fallacies and the analysis of areal census data. Environment and Planning A, 16(1), 17–31.
Paquet, C., Cargo, M., Kestens, Y., & Daniel, M. (2010). Reliability of an instrument for direct observation of urban neighbourhoods. Landscape and Urban Planning, 97(3), 194–201.
Park, Y., & Rogers, G. O. (2015). Neighborhood planning theory, guidelines, and research: Can area, population, and boundary guide conceptual framing? Journal of Planning Literature, 30(1), 18–36.
Patino, J. E., & Duque, J. C. (2013). A review of regional science applications of satellite remote sensing in urban settings. Computers, Environment and Urban Systems, 37, 1–17.
Pliakas, T., Hawkesworth, S., Silverwood, R. J., Nanchahal, K., Grundy, C., Armstrong, B., et al. (2017). Optimising measurement of health-related characteristics of the built environment: Comparing data collected by foot-based street audits, virtual street audits and routine secondary data sources. Health & Place, 43, 75–84.
Ross, C. E., & Mirowsky, J. (1999). Disorder and decay the concept and measurement of perceived neighborhood disorder. Urban Affairs Review, 34(3), 412–432.
Sampson, R. J., & Groves, W. B. (1989). Community structure and crime: Testing social-disorganization theory. American Journal of Sociology, 94(4), 774–802.
Sampson, R. J., & Raudenbush, S. W. (1999). Systematic social observation of public spaces: A new look at disorder in urban neighborhoods. American Journal of Sociology, 105(3), 603–651.
Sampson, R. J., & Raudenbush, S. W. (2004). Seeing disorder: Neighborhood stigma and the social construction of “broken windows”. Social Psychology Quarterly, 67(4), 319–342.
Schaefer-McDaniel, N., Caughy, M. O. B., O’Campo, P., & Gearey, W. (2010). Examining methodological details of neighbourhood observations and the relationship to health: A literature review. Social Science & Medicine, 70(2), 277–292.
Skogan, W. G. (1990). Disorder and decline: Crime and the spiral of decay in American neighborhoods. Berkeley: University of California Press.
Taylor, R. B. (2001). Breaking away from broken windows: Evidence from Baltimore neighborhoods and the nationwide fight against crime, grime, fear and decline. New York, NY: Westview.
Wallace, D., & Schalliol, D. (2015). Testing the temporal nature of social disorder through abandoned buildings and interstitial spaces. Social science research, 54, 177–194.
Weiss, L., Ompad, D., Galea, S., & Vlahov, D. (2007). Defining neighborhood boundaries for urban health research. American Journal of Preventive Medicine, 32(6), 154–S159.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Grubesic, T.H., Nelson, J.R. (2020). Capturing Neighborhood Physical Disorder Using Small, Unmanned Aerial Systems. In: UAVs and Urban Spatial Analysis. Springer, Cham. https://doi.org/10.1007/978-3-030-35865-5_7
Download citation
DOI: https://doi.org/10.1007/978-3-030-35865-5_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-35864-8
Online ISBN: 978-3-030-35865-5
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)