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Analyzing Terrorism Using Spatial Analysis Techniques: A Case Study of Turkish Cities

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Evidence-Based Counterterrorism Policy

Part of the book series: Springer Series on Evidence-Based Crime Policy ((SSEBCP,volume 3))

Abstract

This chapter examines techniques for studying terrorism attacks based on high risk locations within Turkey. According to the literature, spatial correlates that might aggravate terrorism risk include target vulnerability, population characteristics, crime, and physical infrastructure. Risk layers computed from these correlates were used along with actual terrorism incidents to calculate location quotients (LQs). LQs were mapped to identify cities in Turkey with the highest likelihood of attack. This analysis advocates the view that counterterrorism efforts can be based on a sound understanding of spatial attributes and structural qualities of a target area using standard geographic units. We discuss the importance of improving data for the development of more robust and accurate analysis.

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Notes

  1. 1.

    For reference purposes, in other articles or studies, cities in Turkey have also been called provinces but the data was obtained from our Turkish sources who advised that these were deemed cities.

  2. 2.

    Domestic terrorism indicates terrorist activity by a group or groups within the country of attack.

  3. 3.

    This analysis was provided to the authors by the Turkish National Police, as were the data for city development, population, and numbers for assembly members, mosques, and murder convictions.

  4. 4.

    Hamm (2005) examined crimes ranging from motor vehicle violations, immigration fraud, and manufacturing illegal firearms to counterfeiting, armed bank robbery, smuggling weapons of mass destruction, and transnational organized crime.

  5. 5.

    Please keep in mind that these steps are for use of RTM without address level or XY coordinate data; if you have that coordinate information, use the steps in Caplan & Kennedy RTM Manual from (http://www.riskterrainmodeling.com).

  6. 6.

    “No risk” was not a categorization as no city lacked data that could plausibly aggravate terrorism risk according to the available empirical literature.

  7. 7.

    Osmaniye, Duzce, Kilis, Karabuk, and Yalova did not have a risk value calculated (data were missing for each of these cities in one or more risk terrain).

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Author information

Authors and Affiliations

  1. School of Criminal Justice, Rutgers University, Newark, NJ, USA

    Danielle M. Rusnak M.A, Leslie W. Kennedy Ph.D, Ibrahim S. Eldivan & Joel M. Caplan Ph.D

  2. Rutgers Center on Public Security, Rutgers University, Newark, NJ, USA

    Leslie W. Kennedy Ph.D, Ibrahim S. Eldivan & Joel M. Caplan Ph.D

Authors
  1. Danielle M. Rusnak M.A
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  2. Leslie W. Kennedy Ph.D
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  3. Ibrahim S. Eldivan
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  4. Joel M. Caplan Ph.D
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Corresponding author

Correspondence to Danielle M. Rusnak M.A .

Editor information

Editors and Affiliations

  1. Center for Evidence- Based Crime Policy, Criminology, Law, and Society, George Mason University, University Blvd. 10900, Fairfax, 20110, Virginia, USA

    Cynthia Lum

  2. School of Criminal Justice, Rutgers University, Washington Street 123, Newark, 07102, New Jersey, USA

    Leslie W. Kennedy

Appendix

Appendix

Cities’ Risk Index, LQ Value, and Number of 2006 Terrorist Incidents

City

Risk

LQ

Incidents

Istanbul

21

12.544

23

Van

14

5.702

8

Ankara

16

4.989

0

Mardin

14

3.991

1

Adana

11

3.628

3

Sirnak

13

3.070

4

Izmir

12

2.661

3

Batman

13

2.456

2

Hakkari

13

2.456

1

Kocaeli

10

2.395

0

Mersin/Icel

10

2.395

5

Tunceli

12

1.996

0

Diyarbakir

14

1.711

5

Gaziantep

11

1.451

2

Elazig

12

1.330

2

Bingöl

13

1.228

4

Gümüshane

13

1.228

0

Mus

13

1.228

0

Siirt

13

1.228

0

Mugla

10

0.798

0

Hatay

11

0.726

1

Sakarya

11

0.726

0

Bursa

12

0.665

0

Agri

13

0.614

3

Bitlis

13

0.614

0

Konya

13

0.614

0

Trabzon

13

0.614

3

Adiyaman

12

0.000

0

Afyon

12

0.000

0

Aksaray

12

0.000

0

Amasya

11

0.000

0

Antalya

11

0.000

1

Ardahan

13

0.000

0

Artvin

12

0.000

0

Aydin

10

0.000

0

Balikesir

11

0.000

0

Bartin

12

0.000

0

Bayburt

13

0.000

0

Bilecik

 9

0.000

0

Bolu

10

0.000

0

Burdur

10

0.000

0

Çanakkale

 9

0.000

0

Çankiri

12

0.000

0

Çorum

12

0.000

0

Denizli

10

0.000

0

Edirne

 9

0.000

0

Erzincan

12

0.000

4

Erzurum

13

0.000

1

Eskisehir

 9

0.000

0

Giresun

13

0.000

0

Igdir

13

0.000

1

Isparta

10

0.000

0

K.maras

13

0.000

0

Karaman

11

0.000

0

Kars

13

0.000

0

Kastamonu

15

0.000

0

Kayseri

10

0.000

0

Kirikkale

11

0.000

1

Kirklareli

 9

0.000

0

Kirsehir

11

0.000

0

Kütahya

12

0.000

0

Malatya

12

0.000

3

Manisa

11

0.000

0

Nevsehir

11

0.000

0

Nigde

12

0.000

0

Ordu

14

0.000

1

Rize

12

0.000

0

Samsun

14

0.000

0

Sanliurfa

14

0.000

0

Sinop

13

0.000

0

Sivas

13

0.000

0

Tekirdag

 9

0.000

0

Tokat

13

0.000

0

Usak

10

0.000

0

Yozgat

13

0.000

0

Zonguldak

10

0.000

0

  1. Italicized and bold cities could indicate type I error; Italicized, bold, and underlined could indicate type II error

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Rusnak, D.M., Kennedy, L.W., Eldivan, I.S., Caplan, J.M. (2012). Analyzing Terrorism Using Spatial Analysis Techniques: A Case Study of Turkish Cities. In: Lum, C., Kennedy, L. (eds) Evidence-Based Counterterrorism Policy. Springer Series on Evidence-Based Crime Policy, vol 3. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-0953-3_8

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