'Artificial Crime Analysis Systems' Puts Focus on Why, Where Crime Occurs
From real-life urban streets to academia to TVs CSI and all its offshoots, interest in the intersection of crime and geography is booming.
Now, that intersection is more visible, understandable and well-documented, thanks to a new book by Professor Lin Liu, Department of Geography head, and John Eck, professor of criminal justice.
Artificial Crime Analysis Systems: Using Computer Simulations and Geographic Information Systems explores research on the use of computer simulation of crime patterns to reveal hidden processes of urban crimes. And just as the book and research combine criminology, computer simulation and geographic information systems (GIS), Liu and Eck combine their expertise for what Liu says is a needed repository of experience.
Liu has been involved in joint research projects with a number of faculty members in criminal justice, including Lawrence Travis, Robin Engel and Eck. He has also worked with Francis Cullen to develop a joint graduate certificate program in crime mapping and analysis. The productive collaboration between the two departments will continue, Liu says.
In the last decade there has been a phenomenal growth in interest in crime pattern analysis, says Liu, whose area of expertise is GIS and its applications to urban-economic problems.
Geographic information systems are now widely used in urban police agencies throughout industrial nations. With this, scholarly interest in understanding crime patterns has grown considerably. The central problem of empirical crime analysis, both applied and academic, is that many of the underlying processes that give rise to crime patterns are not visible, and so are not well understood.
To address this problem, a number of crime researchers have drawn from the experience of other disciplines to create virtual cityscapes to model artificial crime patterns within a computing environment, Liu adds.
This new and exciting area has no guiding text or repository of experience, he says. Our book helps fill this need, and thus accelerate the rapid growth in this area.
A few questions:
Q) Please offer definitions of artificial crime analysis and crime simulation, and how it came to life as a research area.
A) In artificial crime analysis and crime simulation, we aim to develop models based on a set of theories to simulate the mechanism that generates crime events and crime patterns. Many of the data needed for crime analysis either are not available or contain significant errors. For example, many actors in the criminal justice systems have incentives to misrepresent the facts. Our simulation approach can help understand this problem from a different perspective.
Q) What factors helped spur the huge growth in interest in crime pattern analysis, and how effectively is it being used by police agencies, governments, etc.?
A) One is the rapid development of GIS, which enables police agencies to gather and analyze geographically referenced crime events. The other is the availability of vast geo-referenced socio-economic data, which can help us better understand process and distribution of crimes.
Q) Explain how you as a geographer got interested in this area of research, and how popular this field of study is becoming worldwide.
A) It kind of started by accident. Back in 1999, Dr. Lawrence Travis in the Criminal Justice Division at UC asked me if I was interested in a joint URC grant application. We submitted a proposal on applying GIS to study crime and the project was funded. We formed a team of six faculty members, three in the area of GIS and three in criminal justice. Dr. John Eck is one of the three members from criminal justice, and he and I have been collaborating ever since. One of our joint interests is crime simulation. He brings in crime theories, and I bring in GIS, spatial analysis and computer modeling. The combination of our expertise enables us to develop various crime simulation models. So far, we have been able to integrate cellular automaton models and agent-based models to simulate street robbery.
The book covers research in U.S., Canada, Great Britain, The Netherlands, Australia, Brazil and China. However, the field of crime simulation is still in its infancy. Our book is the very first book worldwide on this subject.
Q) For academics, what are some of the interdisciplinary benefits of this area of study?
A) The field of artificial crime analysis and crime simulation is inherently interdisciplinary. The knowledge of criminology, geography and computer science is absolutely necessary for this type of research. Our collaboration has led to joint external grants. Other benefits include students getting cross-trained in criminology and geography and co-advising of graduate students. We have been working on a new graduate certificate program on crime mapping and analysis. So far market analysis has indicated that there exists large demand for this type of certificate; we will submit a proposal to the graduate school this fall.
Q) What sparked your interest in urban-economic problems, and when did you begin to realize the potential for combining it with your interest and expertise in GIS?
A) Back in 1983, I used remote sensing to study coastlines in Northern China and became interested in the computer side of geography. In 1984, the first year of my graduate study at Peking University, I joined a project to develop GIS software. I continued to work on GIS software development until 1990, when I joined the PhD program in Geography at The Ohio State University. The PhD program required an area of specialization and a minor. My area of specialization was GIS, and I chose my minor in location analysis. So my interest in studying urban-economic problems started in early 1990s, and since then we have doing research related to the application of GIS to urban-economic problems.
Q) Who is the audience for this book, and how will they use it in their work?
There are multiple audiences. The first are criminologists interested in the spatial patterning of crime. These include academics who are not currently engaged in computer simulation. Indeed, one of the goals of this effort is to entice them into this field by providing them with a useful and comprehensive introduction. The second audience includes geographers interested in crime or simulations of other social processes (e.g., transportation systems are important for understanding crime so we would expect that a geographer interested in transportation system modeling would find this volume of interest). The third audience includes urban planners and others interested in urban systems. Simulation modeling is becoming an important part of urban research and is widely used in planning. There is also an eclectic mix of sociologists, psychologists, political scientists and economists whose research interests includes either crime or computer simulation.
Finally, computer scientists who develop computer simulations of social processes either for their own research or as members of teams should find the book useful. In short, because this volume touches on so many overlapping fields, we expect a larger than normal audience. It is also important to recognize that interest in this area is not confined to the U.S., so we expect our audience to be throughout the industrialized world.