Abstract
City offices are constantly responding to public service requests. The efficiency at which they can do this depends on gathering data about where and to what extent a particular service is needed. For example, if a tree limb has fallen and blocks a roadway, the office responsible for removing the limb will not know its existence until someone files a report. One mechanism for reporting these events is via 311 (or a web-based version of the same service). The city can then determine when and where to deploy resources to fulfill the service request. Some 311 calls are specific to city code violations on private property, such as the presence of abandoned cars, vacant or deteriorating buildings, or overgrown vegetation. For code violations, UAVs can be an essential tool for quickly and efficiently verifying the violation and assessing if the violation impacts surrounding properties. In this chapter, we demonstrate the efficacy of using UAVs in conjunction with 311 property code calls for service to explore property violation issues at multiple spatial scales in Phoenix, Arizona.
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References
Accordino, J., & Johnson, G. T. (2000). Addressing the vacant and abandoned property problem. Journal of Urban Affairs, 22(3), 301–315.
Acolin, A., Walter, R. J., Tillyer, M. S., Lacoe, J., & Bostic, R. (2021). Spatial spillover effects of crime on private investment at nearby micro-places. Urban Studies, 59(4), 834–850. https://doi.org/10.1177/0042098021102976
Anselin, L. (1995). Local indicators of spatial association—LISA. Geographical Analysis, 27(2), 93–115. https://doi.org/10.1111/j.1538-4632.1995.tb00338.x
Anselin, L., & Rey, S. J. (2014). Modern spatial econometrics in practice: A guide to GeoDa, GeoDaSpace and PySAL. GeoDa Press.
Article II. Maintenance Standards, 1 (2023).
Braga, A. A., Welsh, B. C., & Schnell, C. (2015). Can policing disorder reduce crime? A systematic review and meta-analysis. Journal of Research in Crime and Delinquency, 52(4), 567–588. https://doi.org/10.1177/0022427815576576
Bravo, D. T., Lima, G. A., Alves, W. A. L., Colombo, V. P., Djogbénou, L., Pamboukian, S. V. D., Quaresma, C. C., & de Araujo, S. A. (2021). Automatic detection of potential mosquito breeding sites from aerial images acquired by unmanned aerial vehicles. Computers, Environment and Urban Systems, 90, 101692. https://doi.org/10.1016/j.compenvurbsys.2021.101692
City of Phoenix. (2023). Property maintenance data. Neighborhood Services Department. https://www.phoenixopendata.com/dataset/property-maintenance-data
Feng, T., Du, H., Lin, Z., & Zuo, J. (2020). Spatial spillover effects of environmental regulations on air pollution: Evidence from urban agglomerations in China. Journal of Environmental Management, 272, 110998. https://doi.org/10.1016/j.jenvman.2020.110998
FindLaw. (2021). Drone laws by state. https://www.findlaw.com/consumer/consumer-transactions/drone-laws-by-state.html
Getis, A., & Ord, J. K. (1992). The analysis of spatial association by use of distance statistics. Geographical analysis, 24(3), 189–206.
Gleiser, R. M., & Zalazar, L. P. (2010). Distribution of mosquitoes in relation to urban landscape characteristics. Bulletin of Entomological Research, 100(2), 153–158.
Grubesic, T. H., & Nelson, J. R. (2020). Capturing neighborhood physical disorder using small, unmanned aerial systems. In UAVs and urban spatial analysis: An introduction (1st ed., pp. 117–141). Springer. https://doi.org/10.1007/978-3-030-35865-5_7
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. https://doi.org/10.1016/j.landurbplan.2017.09.001
Hardy, A., Makame, M., Cross, D., Majambere, S., & Msellem, M. (2017). Using low-cost drones to map malaria vector habitats. Parasites & Vectors, 10(1), 1–13.
Long Lake Township v Maxon (2021).
Murray, M. H., Fyffe, R., Fidino, M., Byers, K. A., RÃos, M. J., Mulligan, M. P., & Magle, S. B. (2018). Public complaints reflect rat relative abundance across diverse urban neighborhoods. In Frontiers in ecology and evolution (Vol. 6) https://www.frontiersin.org/articles/10.3389/fevo.2018.00189
Passos, W. L., Araujo, G. M., de Lima, A. A., Netto, S. L., & da Silva, E. A. B. (2022). Automatic detection of Aedes aegypti breeding grounds based on deep networks with spatio-temporal consistency. Computers, Environment and Urban Systems, 93, 101754. https://doi.org/10.1016/j.compenvurbsys.2021.101754
Skogan, W. G. (1992). Disorder and decline: Crime and the spiral of decay in American neighborhoods. University of California Press.
Spader, J., Schuetz, J., & Cortes, A. (2016). Fewer vacants, fewer crimes? Impacts of neighborhood revitalization policies on crime. Regional Science and Urban Economics, 60, 73–84. https://doi.org/10.1016/j.regsciurbeco.2016.07.005
Tamayo-Uria, I., Mateu, J., Escobar, F., & Mughini-Gras, L. (2014). Risk factors and spatial distribution of urban rat infestations. Journal of Pest Science, 87, 107–115.
Wei, E., Hipwell, A., Pardini, D., Beyers, J. M., & Loeber, R. (2005). Block observations of neighbourhood physical disorder are associated with neighbourhood crime, firearm injuries and deaths, and teen births. Journal of Epidemiology & Community Health, 59(10), 904–908.
Xu, L., Kwan, M.-P., McLafferty, S., & Wang, S. (2017). Predicting demand for 311 non-emergency municipal services: An adaptive space-time kernel approach. Applied Geography, 89, 133–141.
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Grubesic, T.H., Nelson, J.R., Wei, R. (2024). UAVs for Monitoring Property Code Violations. In: UAVs for Spatial Modelling and Urban Informatics. Springer, Cham. https://doi.org/10.1007/978-3-031-54114-8_3
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