Geographical Profiling for Counter Terrorism
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Private Sector Counter Terrorism Practitioners
(21st Century Security Management)
Understand Who Lives, Works, and Moves Through a Place and What That Means for Security
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The Why
Geographical profiling (GP) isn’t just for catching serial offenders. The same principles can help private sector counter terrorism practitioners understand places and how people use an area, where they travel from, and whether a particular location might attract activities linked to terrorism or hybrid threats (Rossmo, 1999; Chainey, 2019).
In basic terms, GP looks at where things happen, who’s around when they happen, and how people move through those spaces (Knabe‑Nicol, 2024).
Once you see those patterns on a map, you can make better decisions, whether that’s opening a new store, improving site security, or training staff to spot risks earlier.
A Geographic Profile extends beyond a Micro Environment Analysis, offering a complete view of the landscape surrounding an organisation. After initial development, it can be maintained and refreshed as conditions evolve.
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The What
The Core Idea ➔ Nodes and Movement
Think of every town or city as a network of nodes. A node is any place where people spend time or pass through, homes, workplaces, schools, pubs, bus stations, shopping centres, or transient housing (Rossmo, 1999).
People travel between these nodes every day. Those journeys, home to work, cultural sites to market, bar to nightclub, form paths. Together, nodes and paths show how communities live, move, and mix (Willmott et al., 2021).
Hybrid threats and terrorists move through these same networks. They usually act in areas they know, near home, work, or along regular routes (Bouhana et al., 2020). That’s why mapping movement patterns can help identify which places are most at risk or most attractive to hostile activity.
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The How
Gathering the Right Information
It’s not rocket science, and you don’t need secret data. Most information for a GP style environmental analysis is publicly accessible..
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Step 1
Local Demographics
Use local census data via the Office for National Statistics (ONS). This shows how many people live in an area, their age, occupation, nationality, and language. Compare this with population mobility, local authorities publish migration or housing‑turnover rates.
Areas with high short term tenancy or large seasonal workforce turnover show higher movement and uncertainty.
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Step 2
Crime and Incident Data
Use crime data for street level crime. Look at violent crime, public order, and anti social behaviour near your site. Cross reference with Home Office Prevent information for radicalisation or extremist incidents.
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Step 3
Social and Transit Nodes
Open Google Maps and mark:
Transport hubs (bus, rail, airport, ports)
Late night venues
Cash based or high traffic businesses (markets, exchanges, fast food etc)
Religious or community centres
Hostels/hotels, transient or student accommodation
These are convergence nodes, places where different people meet and where anonymity can be high (Mitrovic, 2024).
Step 4
Country of Origin or Conflict Exposure
The ONS provides international migration data. This isn’t for profiling, it’s to understand context.
For example, if new residents arrive from countries with ongoing insurgency problems, that doesn’t make them a threat, but such links can be exploited by hostile actors (Bouhana et al., 2020).
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Step 5
Economic and Social Activity
Check local business listings or Companies House for small business growth and warehouse activity. Look for unregulated labour sectors, cash‑in‑hand jobs or informal logistics, which can overlap with illicit networks (Mitrović, 2024).
Step 6
Making Sense of the Data
Once mapped, patterns emerge (Rossmo, 1999):
High mobility zones attract those wanting to blend in.
Transport corridors double as legitimate and illicit routes.
Cultural nodes are social assets but can be misused by extremists (UK Home Office, 2023).
Cash economies, markets and takeaways, can be used for money laundering or covert logistics.
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Step 7
Turning Findings into Action
After mapping your nodes and paths:
1. Overlay crime and demographic data.
2. Identify high probability zones of exposure.
3. Plan mitigations, lighting, access control, police liaison, or adjusted hours.
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Basic Example
Distribution Hub Assessment
A supermarket chain plans to open a 24 hour distribution hub on a UK city’s edge.
Before signing, the security manager/practitioner conducts a GP assessment.
Findings:
Transport nodes. Dual‑carriageway linking towns and airport; constant worker transit.
Population turnover. High turnover and short term housing.
Crime pattern. Theft from vehicles and suspicious package reports within 5 mile.
Convergence nodes. Multiple 24 hour food and fuel outlets attracting transient crowds.
Cultural mix. ONS data shows a diverse, cohesive population with arrivals from regions recently facing instability.
Interpretation
Three overlapping rings, the transport corridor, housing areas, and night time economy, form a dynamic convergence zone. It’s not dangerous, but it’s a space that could be exploited if unmanaged.
Mitigation
Install ANPR cameras; redesign entrances; liaise with Prevent officers; brief night staff; improve lighting and sight-lines (CPTED).
Outcome
The company proceeds with understanding, smarter design, stronger engagement, and active liaison, demonstrating how GP supports 21st century security management.
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Why It Matters
GP converts open data into practical information.
It helps practitioners ask:
Who uses this area?
What routines occur here?
How might a hostile actor exploit it?
Used correctly, it helps business leaders balance risk with opportunity, not labelling communities but understanding environments, movement, and exposure (Willmott et al., 2021).
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References
Bouhana, N. et al. (2020). Lone‑Actor Terrorists: A Residence‑to‑Crime Approach. University College London. Available at: https://discovery.ucl.ac.uk/id/eprint/10112115/
Chainey, S. (2019). Introducing Geographic Profiling Analysis in Mexico. UCL/IDB. Available at: https://discovery.ucl.ac.uk/id/eprint/10082812/
Knabe‑Nicol, S. (2024). Existing Understanding of Geographic Profiling Principles. Crime, Law & Social Change. Available at: https://www.tandfonline.com/doi/full/10.1080/23311886.2024.2313275
Mitrović, L. M. (2024). Application of GIS Criminalistics Techniques in Counter‑Terrorism. Croatia Review of Security Studies. Available at: https://hrcak.srce.hr/file/468257
Office for National Statistics (2023). UK Census Data and International Migration Statistics. Available at: https://www.ons.gov.uk/
Willmott, D., Hunt, D. & Mojtahedi, D. (2021). Criminal Geography and Geographical Profiling – A Brief Introduction. Available at: https://research.edgehill.ac.uk/en/publications/criminal-geography-and-geographical-profiling-a-brief-introduction
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