Combatting human trafficking is a complex global issue comprising of a multitude of risk factors. Federal, state, and local law enforcement are working on various angles in combating the multibillion-dollar criminal nexus.
With the ongoing advancements in technology and data sciences today, Geographic Information System (GIS) engineering can be applied to countering human trafficking operations through a data-driven model of mapping and analyzing the socioeconomic risk factors of human trafficking and tracking real-time metadata to influence law enforcing decisions.
Human trafficking
Human trafficking (or modern-day slavery) is one of the fastest growing crimes in the world today. Polaris “defines human trafficking as the use of force, fraud, or coercion to compel a person into commercial sex acts or labor against their will.”
Anyone can be a victim of human trafficking, but it is important to remember that some people are at a greater risk because of socioeconomic vulnerability factors.
Mapping the risk factors
To further understand human trafficking, it is important to understand the human trafficking kill chain, which encompasses the recruitment, transportation, entrapment, brokering, delivery, and exploitation of a victim(s).
The ideal solution to ending human trafficking is to prevent individuals from entering the initial vacuum into the recruitment phase of the human trafficking kill chain. To achieve this goal, it is vital to understand the correlating risk factors shared by victims of human trafficking.
Socioeconomic risk factors are what build the environment for human trafficking to thrive in, especially in areas of greater population densities, where there exists an ample supply of human capital and a foothold for a demand supplemented by the brokering of money in exchange for a human. Human trafficking is all about profiting from the sex, labor, and/or debt bondage of another human being.
Risk factors of human trafficking can include (but are not limited to) a low social vulnerability index, high unemployment rates, a deficiency of police presence, low household wages, insufficient healthcare or insurance, a lack of education or poor school systems, high violent crime rates, growing child poverty rates, homelessness, accessibility to drugs, work visas, language barriers, inadequate social programs, international boundaries, and a proximity to a numerous amount of transportation hubs (airports, seaports, highways, etc.) and hotels.
How can we build a concise understanding of how these risk factors correlate with one another? The answer is through a data-driven approach that paints the common operating picture of the environment with GIS systems such as QGIS.
QGIS is a free open-source software that anyone can use to display, view, and edit geospatial data. Images 1, 2, and 3 in this article showcase the utilization of publicly accessible, and georeferenced vector, raster, and attribute data to pair demographics with socioeconomic and spatial analysis; thus, helping to build correlations and patterns of both victims and criminals.
Advancements in geocoding and data analysis are enabling real-time mapping that can equip legislators, lawmakers, and social workers with the ability to identify risk factors and make educated decisions in their own communities.
Success of such applications is evident in the growing use of crime mapping. Notably, GIS companies such as Esri are working with local law enforcement to geospatially map and analyze georeferenced data trends in real-time to counter human trafficking operations.
GIS Applications to Combat Human Trafficking
Esri is a key influencing company behind modern GIS software development. Esri’s software, ArcGIS Pro Intelligence, is currently being utilized to equip government and civilian agencies in countering human trafficking operations through GIS analysis and data mapping in both space and time.
With data driven tools like ArcGIS Pro Intelligence, law enforcement agents and social workers can build cases with the help of GIS and metadata evidence to catch offenders, rescue survivors, and provide justice in endless and ongoing human trafficking court cases.
With a multitude of metadata being collected from web browsers and tracked through satellites and receivers, law enforcement agencies are better equipped to intervene during all phases of the human trafficking kill chain. GIS platforms are efficiently saving law enforcement time in gathering evidence and information, so that most of the energy can be tailored towards problem solving, decision making, and manning the force.
Combating human trafficking through GIS platforms does not solely have to be on the onus of law enforcement. Governments are building transparency with increasing ubiquitous access to socioeconomic geodata that everyday citizens can use in building a safer community and advocating for solutions to issues within the greater communities.
In the civilian sector, companies like Oracle are already syncing decentralized data from both social media and GIS databases and bringing them into one centralized database to help simplify data for law enforcement to utilize to stop traffickers and save victims.
Law enforcement cannot be geographically located everywhere all the time; it requires a substantial amount of community cooperation and intelligence sharing to promote the safety and welfare for all. This signifies the future of an evolving cloud-based collaboration in data driven and GIS approaches to mapping out socioeconomic issues and combating crimes such as human trafficking.
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