Skip to main content
SpringerLink
Log in

How to Prevent Crimes Using Earthquakes

  • Chapter
  • First Online:
Imagine Math 6

  • 1016 Accesses

Abstract

In this chapter the author describes how techniques coming from earthquakes prediction has been used to produce successful mathematical models useful in preventing crimes.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 69.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 89.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. http://www4.stat.ncsu.edu/~reich/st733/Journal/Logan3.pdf

  2. http://www.predpol.com

  3. K. Henning, Residential burglary hotspot, 1 November 2017. Retrieved from http://www.pdx.edu/crime-data/

  4. http://www.transcrime.it

  5. http://www.share-eu.org

  6. G.O. Mohler, M.B. Short, P.J. Brantigham, F.P. Schoenberg, G.E. Tita, Self-exciting point process modeling of crime. J. Am. Stat. Assoc. 106, 100–108 (2011)

    Article  MathSciNet  Google Scholar 

  7. G.O. Mohler, Modeling and estimation of multi-source clustering in crime and security data. Ann. Appl. Stat. 7, 1525–1539 (2013)

    Article  MathSciNet  Google Scholar 

  8. M.B. Short, G.O. Mohler, P.J. Brantigham, G.E. Tita, Gang rivalry dynamics via coupled point process networks. Discrete Contin. Dyn. Syst., Ser. B 19, 1459–1477 (2014)

    Article  MathSciNet  Google Scholar 

  9. J.T. Woodworth, G.O. Mohler, A.L. Bertozzi, P.J. Brantigham, Non-local crime density estimation incorporating housing information. Philos. Trans. R. Soc. A 372, 20130403 (2014)

    Article  MathSciNet  Google Scholar 

  10. G.O. Mohler, M.B. Short, S. Malinowski, M. Johnson, G.E. Tita, A.L. Bertozzi, P.J. Brantigham, Randomized controlled field trials of predictive policing. J. Am. Stat. Assoc. 110, 1399–1411 (2015)

    Article  MathSciNet  Google Scholar 

  11. http://www.hunchlab.com

  12. http://www.civicscape.com

  13. G.O. Mohler, Marked point process hotspot maps for homicide and gun crime prediction in Chicago. Int. J. Forecast. 30, 491–497 (2014)

    Article  Google Scholar 

  14. http://www.predpol.com/results/

  15. http://www.nature.com/news/reform-predictive-policing-1.21338

  16. http://singularityhub.com/2017/02/02/could-predictive-policing-lead-to-a-real-life-minority-report/

  17. http://github.com/CivicScape/CivicScape

Download references

Author information

Authors and Affiliations

  1. Dipartimento di Matematica, Università di Pisa, Largo Pontecorvo 5, 56127, Pisa, Italy

    Marco Abate

Authors
  1. Marco Abate
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Marco Abate .

Editor information

Editors and Affiliations

  1. Roma, Italy

    Michele Emmer

  2. Mathematics Department, University of Pisa , Pisa, Italy

    Marco Abate

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG, part of Springer Nature

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Abate, M. (2018). How to Prevent Crimes Using Earthquakes. In: Emmer, M., Abate, M. (eds) Imagine Math 6. Springer, Cham. https://doi.org/10.1007/978-3-319-93949-0_9

Download citation

Publish with us

Policies and ethics

Search

Navigation