244
Views
2
CrossRef citations to date
0
Altmetric
Articles

Crime Geosurveillance in Microscale Urban Environments: NetSurveillance

&
Pages 1386-1406 | Received 01 Apr 2017, Accepted 22 Aug 2018, Published online: 28 Jan 2020

References

  • Bernardinelli, L., D. Clayton, C. Pascutto, C. Montomoli, M. Ghislandi, and M. Songini. 1995. Bayesian analysis of space–time variation in disease risk. Statistics in Medicine 14 (21–22):2433–43. doi: 10.1002/sim.4780142112.
  • Bowers, K. J., and S. D. Johnson. 2005. Domestic burglary repeats and space–time clusters. European Journal of Criminology 2 (1):67–92. doi: 10.1177/1477370805048631.
  • Bradley, C. A., H. Rolka, D. Walker, and J. Loonsk. 2005. BioSense: Implementation of a national early event detection and situational awareness system. Morbidity and Mortality Weekly Report 54:11–20.
  • Braga, A. A. 2001. The effects of hot spots policing on crime. The Annals of the American Academy of Political and Social Science 455:104–25. doi: 10.1177/000271620157800107.
  • Braga, A. A., and B. J. Bond. 2008. Policing crime and disorder hot spots: A randomized controlled trial. Criminology 46 (3):577–608. doi: 10.1111/j.1745-9125.2008.00124.x.
  • Braga, A. A., A. V. Papachristos, and D. H. Hureau. 2010. The concentration and stability of gun violence at micro places in Boston, 1980–2008. Journal of Quantitative Criminology 26 (1):33–53. doi: 10.1007/s10940-009-9082-x.
  • Braga, A. A., A. V. Papachristos, and D. H. Hureau. 2014. The effects of hot spots policing on crime: An updated systematic review and meta-analysis. Justice Quarterly 31 (4):633–63. doi: 10.1080/07418825.2012.673632.
  • Braga, A. A., and D. L. Weisburd. 2010. Editors’ introduction: Empirical evidence on the relevance of place in criminology. Journal of Quantitative Criminology 26 (1):1–6. doi: 10.1007/s10940-009-9088-4.
  • Chang, W., D. Zeng, and H. Chen. 2005. Prospective spatio-temporal data analysis for security informatics. In IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC 2005: 1120-24 doi: 10.1109/ITSC.2005.1520208.
  • Chen, D., J. Cunningham, K. Moore, and J. Tian. 2011. Spatial and temporal aberration detection methods for disease outbreaks in syndromic surveillance systems. Annals of GIS 17 (4):211–20. doi: 10.1080/19475683.2011.625979.
  • Chen, H., D. Zeng, and P. Yan. 2010. Infectious disease informatics. New York: Springer.
  • Cheng, T., and M. Adepeju. 2014. Modifiable temporal unit problem (MTUP) and its effect on space–time cluster detection. PLoS One 9 (6):e100465. doi: 10.1371/journal.pone.0100465.
  • Clarke, R. V., and D. Weisburd. 1994. Diffusion of crime control benefits: Observations on the reverse of displacement. In Crime prevention studies, ed. R. V. Clarke, vol. 2, 5–32. Monsey, NY: Criminal Justice Press.
  • Cohen, J., W. L. Gorr, and A. M. Olligschlaeger. 2007. Leading indicators and spatial interactions: A crime-forecasting model for proactive policing deployment. Geographical Analysis 39 (1):105–27. doi: 10.1111/j.1538-4632.2006.00697.x.
  • Deadman, D. 2003. Forecasting residential burglary. International Journal of Forecasting 19 (4):567–78. doi: 10.1016/S0169-2070(03)00091-8.
  • Deadman, D., and D. J. Pyle. 1997. Forecasting recorded property crime using a time-series econometric model. British Journal of Criminology 37 (3):437–45. doi: 10.1093/oxfordjournals.bjc.a014179.
  • Duczmal, L., and D. L. Buckeridge. 2006. A workflow spatial scan statistic. Statistics in Medicine 25 (5):743–54. doi: 10.1002/sim.2403.
  • Felson, M., and R. V. Clarke. 1998. Opportunity makes the thief: Practical theory for crime prevention. Police Research Series, Paper 98. Home Office, London.
  • Friedman, L. S. 2009. Real-time surveillance of illicit drug overdoses using poison center data. Clinical Toxicology 47 (6):573–79. doi: 10.1080/15563650902967404.
  • Gorr, W., and R. Harries. 2003. Introduction to crime forecasting. International Journal of Forecasting 19 (4):551–55. doi: 10.1016/S0169-2070(03)00089-X.
  • Gorr, W., and Y. Lee. 2015. Early warning system for temporary crime hot spots. Journal of Quantitative Criminology 31 (1):25–47. doi: 10.1007/s10940-014-9223-8.
  • Gorr, W., and A. Olligschlaeger. 2002. Crime hot spot forecasting: Modeling and comparative evaluation, final project report. Washington, DC: Office of Justice Programs, National Institute of Justice.
  • Gorr, W., A. Olligschlaeger, and Y. Thompson. 2003. Short-term forecasting of crime. International Journal of Forecasting 19 (4):579–94. doi: 10.1016/S0169-2070(03)00092-X.
  • Groff, E. R., and N. G. LaVigne. 2002. Forecasting the future of predictive crime mapping. In Crime prevention studies, ed. N. Tilley, 29–57. Monsey, NY: Criminal Justice Press.
  • Groff, E. R., D. Weisburd, and N. Morris. 2009. Where the action is at places: Examining spatio-temporal patterns of juvenile crime at places using trajectory analysis and GIS. In Putting crime in its place: Units of analysis in spatial crime research, ed. D. L. Weisburd, W. Bernasco, and G. Bruinsma, 61–86. New York: Springer Verlag.
  • 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.
  • HunchLab. 2017. HunchLab: Under the hood. Accessed November 1, 2017. https://cdn.azavea.com/pdfs/hunchlab/HunchLab-Under-the-Hood.pdf.
  • Kennedy, L. W., J. M. Caplan, and E. Piza. 2011. Clusters, hotspots, and spatial intelligence: Risk terrain modeling as an algorithm for police resource allocation strategies. Journal of Quantitative Criminology 27 (3):339–62. doi: 10.1007/s10940-010-9126-2.
  • Kim, Y., and M. O’Kelly. 2008. A bootstrap based space–time surveillance model with an application to crime occurrences. Journal of Geographical Systems 10 (2):141–65. doi: 10.1007/s10109-008-0058-4.
  • Kleinman, K., R. Lazarus, and R. Platt. 2004. A generalized linear mixed models approach for detecting incident clusters of disease in small areas, with an application to biological terrorism. American Journal of Epidemiology 159 (3):217–24. doi: 10.1093/aje/kwh029.
  • Kulldorff, M. 1997. A spatial scan statistic. Communications in Statistics: Theory and Methods 26 (6):1481–96. doi: 10.1080/03610929708831995.
  • Kulldorff, M. 2001. Prospective time periodic geographical disease surveillance using a scan statistic. Journal of the Royal Statistical Society: Series A (Statistics in Society) 164 (1):61–72. doi: 10.1111/1467-985X.00186.
  • Kulldorff, M., R. Heffernan, J. Hartman, R. Assunção, and F. Mostashari. 2005. A space–time permutation scan statistic for the early detection of disease outbreaks. PLoS Medicine 2 (3):e59–24. doi: 10.1371/journal.pmed.0020059.
  • Kulldorff, M., and N. Nagarwalla. 1995. Spatial disease clusters: Detection and inference. Statistics in Medicine 14 (8):799–810. doi: 10.1002/sim.4780140809.
  • Lawson, A. B., and K. Kleinman, eds. 2005. Spatial and syndromic surveillance for public health. Chichester, UK: Wiley.
  • Lazarus, R., K. Kleinman, I. Dashevsky, C. Adams, P. Kludt, A. DeMaria, Jr., and R. Platt. 2002. Use of automated ambulatory-care encounter records for detection of acute illness clusters, including potential bioterrorism events. Emerging Infectious Diseases 8 (8):753–60. doi: 10.3201/eid0808.020239.
  • Martinez-Beneito, M. A., G. Garcia-Donato, and D. Salmeron. 2011. A Bayesian joinpoint regression model with an unknown number of break-points. The Annals of Applied Statistics 5 (3):2150–68. doi: 10.1214/11-AOAS471.
  • Mohler, G. O., M. B. Short, P. J. Brantingham, F. P. Schoenberg, and G. E. Tita. 2011. Self-exciting point process modeling of crime. Journal of the American Statistical Association 106 (493):100–108. doi: 10.1198/jasa.2011.ap09546.
  • Neill, D. B. 2009. Expectation-based scan statistics for monitoring spatial time series data. International Journal of Forecasting 25 (3):498–517. doi: 10.1016/j.ijforecast.2008.12.002.
  • Neill, D. B., and W. L. Gorr. 2007. Detecting and preventing emerging epidemics of crime. Advances in Disease Surveillance 4 (13).
  • Neill, D. B., and A. W. Moore. 2006. Methods for detecting spatial and spatiotemporal clusters. In Handbook of biosurveillance, ed. M. M. Wagner, A. W. Moore, and R. M. Aryel, 243–54. Burlington, MA: Elsevier.
  • Nordin, J. D., M. J. Goodman, M. Kulldorff, D. P. Ritzwoller, A. M. Abrams, K. Kleinman, M. J. Levitt, J. Donahue, and R. Platt. 2005. Simulated anthrax attacks and syndromic surveillance. Emerging Infectious Diseases 11 (9):1394–98. doi: 10.3201/eid1109.050223.
  • PredPol. 2017. How predictive policing works. Accessed November 1, 2017. http://www.predpol.com/how-predictive-policing-works/.
  • Rogerson, P. A. 1997. Surveillance systems for monitoring the development of spatial patterns. Statistics in Medicine 16 (18):2081–93. doi: 10.1002/(SICI)1097-0258(19970930)16:18<2081::AID-SIM638>3.0.CO;2-W.
  • Rogerson, P. A. 2001. Monitoring point patterns for the development of space–time clusters. Journal of the Royal Statistical Society: Series A (Statistics in Society) 164 (1):87–96. doi: 10.1111/1467-985X.00188.
  • Rogerson, P. A. 2005. A set of associated statistical tests for spatial clustering. Environmental and Ecological Statistics 12 (3):275–88. doi: 10.1007/s10651-005-1513-8.
  • Rogerson, P. A., and Y. Sun. 2001. Spatial monitoring of geographic patterns: An application to crime analysis. Computers, Environment and Urban Systems 25 (6):539–56. doi: 10.1016/S0198-9715(00)00030-2.
  • Rogerson, P. A., and I. Yamada. 2009. Statistical detection and surveillance of geographic clusters. Boca Raton, FL: Chapman and Hall/CRC.
  • Sherman, L. W., P. Gartin, and M. Buerger. 1989. Hot spots of predatory crime: Routine activities and the criminology of place. Criminology 27 (1):27–55. doi: 10.1111/j.1745-9125.1989.tb00862.x.
  • Sherman, L. W., and D. Weisburd. 1995. General deterrent effects of police patrol in crime “hot-spots”: A randomized, controlled trial. Justice Quarterly 12 (4):625–48. doi: 10.1080/07418829500096221.
  • Shiode, N., S. Shiode, E. Thatcher-Rod, S. Rana, and P. Vinten-Johansen. 2015. The mortality rates and the space–time patterns of John Snow’s cholera epidemic map. International Journal of Health Geographics 14 (1):21. doi: 10.1186/s12942-015-0016-6.
  • Shiode, S. 2011. Street-level spatial scan statistic and STAC for analyzing street crime concentrations. Transactions in GIS 15 (3):365–83. doi: 10.1111/j.1467-9671.2011.01255.x.
  • Shiode, S., and N. Shiode. 2013. Space–time network-based STAC for hotspot detection of street-level crime incidents. International Journal of Geographical Information Science 27 (5):866–82. doi: 10.1080/13658816.2012.724175.
  • Shiode, S., and N. Shiode. 2014. Micro-scale prediction of near-future crime concentrations with street-level geosurveillance. Geographical Analysis 46 (4):435–55. doi: 10.1111/gean.12065.
  • Takahashi, K., M. Kulldorff, T. Tango, and K. Yih. 2008. A flexibly shaped space–time scan statistic for disease outbreak detection and monitoring. International Journal of Health Geographics 7 (1):14. doi: 10.1186/1476-072X-7-14.
  • Taylor, B., C. Koper, and D. Woods. 2011. A randomized controlled trial of different policing strategies at hot spots of violent crime. Journal of Experimental Criminology 7 (2):149–81. doi: 10.1007/s11292-010-9120-6.
  • Weisburd, D. 2015. The law of crime concentrations and the criminology of place. Criminology 53 (2):133–57. doi: 10.1111/1745-9125.12070.
  • Weisburd, D., and S. Amram. 2014. The law of concentrations of crime at place: The case of Tel Aviv-Jaffa. Police Practice and Research 15 (2):101–14. doi: 10.1080/15614263.2013.874169.
  • Weisburd, D., G. J. N. Bruinsma, and W. Bernasco. 2009. Units of analysis in geographic criminology: Historical development, critical issues, and open questions. In Putting crime in its place: Units of analysis in geographic criminology, ed. D. Weisburd, G. J. N. Bruinsma, and W. Bernasco, 3–34. New York: Springer Verlag.
  • Weisburd, D., S. Bushway, C. Lum, and S.-M. Yang. 2004. Trajectories of crime at places: A longitudinal study of street segments in the City of Seattle. Criminology 42 (2):283–321. doi: 10.1111/j.1745-9125.2004.tb00521.x.
  • Weisburd, D., and L. Green. 1995. Policing drug hot spots: The Jersey City drug market analysis experiment. Justice Quarterly 12 (4):711–35. doi: 10.1080/07418829500096261.
  • Weisburd, D., E. R. Groff, and S. Yang. 2012. The criminology of place: Street segments and our understanding of the crime problem. New York: Oxford University Press.
  • Weisburd, D., and C. W. Telep. 2014. Hot spots policing: What we know and what we need to know. Journal of Contemporary Criminal Justice 30 (2):200–220. doi: 10.1177/1043986214525083.
  • Wheeler, A. P., R. E. Worden, and S. J. McLean. 2016. Replicating group-based trajectory models of crime at micro-places in Albany, NY. Journal of Quantitative Criminology 32 (4):589–612. doi: 10.1007/s10940-015-9268-3.
  • Woodall, W. H., J. B. Marshall, M. D. Joner, Jr., S. E. Fraker, and A. G. Abdel-Salam. 2008. On the use and evaluation of prospective scan methods for health-related surveillance. Journal of the Royal Statistical Society, Series A 171:223–37.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.