Land Use Influencing the Spatial Distribution of
Urban Crime: A Case Study of Szczecin, Poland
Natalia Sypion-Dutkowska
Spatial Management Unit, Faculty of Geosciences, University of Szczecin, Mickiewicza 18 Street, 70-383 Szczecin, Poland
Michael Leitner
Department of Geography and Anthropology, Louisiana State University, E-104 Howe-Russell-Kniffen Geoscience Complex, Baton Rouge, LA 70803, USA; mleitne@lsu.edu
ISPRS International Journal of Geo-Information. 2017, 6, 74; doi:10.3390/ijgi6030074
Acknowledgments: This research was funded by the National Science Centre (NCN) of Poland under grant agreement no N N306 786840. The authors also thank the City Police Department of Szczecin for making available the data on crime, and the City Office of Szczecin for making available some data on land use. Author Contributions: Natalia Sypion-Dutkowska conceived the idea for this research and designed and performed the statistical analysis; Natalia Sypion-Dutkowska wrote major parts of the paper; Michael Leitner wrote minor parts of the paper and language-edited the final version of the manuscript. Conflicts of Interest: The authors declare no conflict of interest.
Abstract:
This paper falls into a common field of scientific research and its practical applications at the interface of urban geography, environmental criminology, and Geographic Information Systems (GIS). The purpose of this study is to identify types of different land use which influence the spatial distribution of a set of crime types at the intra-urban scale. The originality of the adopted approach lies in its consideration of a large number of different land use types considered as hypothetically influencing the spatial distribution of nine types of common crimes, geocoded at the address-level: car crimes, theft of property—other, residential crimes, property damage, commercial crimes, drug crimes, burglary in other commercial buildings, robbery, and fights and battery. The empirical study covers 31,319 crime events registered by the Police in the years 2006–2010 in the Polish city of Szczecin with a population ca. 405,000. Main research methods used are the GIS tool “multiple ring buffer” and the “crime location quotient (LQC)”. The main conclusion from this research is that a strong influence of land use types analyzed is limited to their immediate surroundings (i.e., within a distance of 50 m), with the highest concentration shown by commercial crimes and by the theft of property—other crime type. Land use types strongly attracting crime in this zone are alcohol outlets, clubs and discos, cultural facilities, municipal housing, and commercial buildings. In contrast, grandstands, cemeteries, green areas, allotment gardens, and depots and transport base are land use types strongly detracting crime in this zone.
Keywords: urban crime; land use; multiple ring buffer; crime location quotient
1. Introduction
Issues of public security, including the threat of crime, belong to the most important problems of the present. Scientific knowledge of the spatial aspects of crime, especially in big cities, is crucial for the containment and improving public security. Crime in big cities is of interest to various disciplines, including urban geography, urban sociology, and especially social ecology, but also criminology, and especially environmental criminology. Each discipline examines the phenomenon of crime from its own perspective and using its specific terms and methods. However, the importance of spatial, also known as environmental or geographic, determinants of crime is recognized and empirically analyzed in these disciplines, e.g., Rice and Smith [1] in sociology, Roh and Leipning [2] in criminology, and Herbert [3] in geography. Most urban criminal events occur in areas characterized by specific land use features, facilities, or population.
The purpose of this study is to identify types of different land use which influence the spatial distribution of a set of common crime types at the intra-urban scale, taking a big Polish city as an example. Having this general aim in mind, the following research questions are formulated: Which kinds of land use influence the spatial distribution of crime? Do they generate, attract, or detract particular crime types? What is the range of this influence? Which crime types are most influenced by particular land use types? These questions will be answered by using the crime and land use data collected for this research and with appropriate GIS tools.
2. Empirical Research on Spatial Determinants of Urban Crime
Numerous research papers, carried out in approximately the last 30 years on spatial determinants of urban crime, have been reviewed for the purpose of this study. For each of these papers, the study area, time-frame of study, influencing land use crime types, applied methods, and main conclusions were identified.
The reviewed papers could be divided into the four categories of research approach, focusing on: (1) The influence of one land use type on one crime type; (2) The influence of one land use type on several crime types; (3) The influence of several land use types on one crime type; and (4) The influence of several land use types on several crime types.
Most studies belong to category (2), followed by papers in category (3), and category (1), which is the least prominent of all categories, except category (4). The studies in category (4), similar to the approach applied in this research, have been discussed rarely in the reviewed literature.
The outcome of this literature review shows that the majority of research concentrated on the influence of one particular land use type on several crime types (category (2) from above). Roncek, Bell, and Francik [4] in their research in Cleveland, OH in 1970, analyzed the influence of housing project blocks on seven types of property and violent crimes. Using the multiple regression analysis and the t-test, they find out that housing project blocks have significantly more index crimes across all types. Roncek and Maier [5] in their investigation in Cleveland, OH in 1979–1981 investigated the influence of taverns and cocktail lounges on seven crime types. Research methods used were mostly multiple regression analysis. The authors detected that the amount of every crime type is significantly higher on residential blocks with taverns or cocktail lounges than on residential blocks without taverns or cocktail lounges. Poister [6] carried out his research in Atlanta, GA in 1990–1994. He analyzed how the last two stations of MARTA’s (Metropolitan Rapid Rail) East Line influence eleven types of Parts I and II crimes. Using multiple regression analysis he discovered that robbery, burglary, and auto theft increased when MARTA’s stations were opened after they were built. Block and Block [7] in their investigation in Chicago, IL in 1993 analyzed how alcohol distribution facilities (taverns, bars, and liquor stores) effect seventeen crime types. Applying density and hot spot analyses, they discovered that the influence of these facilities on the crime distribution depends on the local level of crime. McNulty and Holloway [8] did a study on Atlanta, GA in 1990–1992. The authors examined social characteristics of public housing and their influence on six crime types (murder, rape, assault, public nuisance, robbery, and property crime). Employing the multivariate analysis they discovered that the influence of public housing on the crime distribution is determined by social characteristics of neighborhoods. Crewe [9] in a study of Boston, MA in 1996–1998 analyzed the Boston South-West Corridor (urban linear park) and its influence on police calls from private households to bodily harm and property crime incidents. Using simple statistical analysis, she discovered that urban linear parks and their neighborhoods show slightly lower levels of property crime. Loukaitou-Sideris et al. [10] in their investigation of Los Angeles, CA in 1998–1999 researched how the fourteen Green Line (light urban rail) stations and their neighborhoods influence six Parts I and II crime types. Applying density, proximity, and multiple regression analyses, they assessed that the influence of light urban rail stations on the crime distribution is differentiated and connected with the characteristics of the station and its neighborhood. Holzman et al. [11] analyzed three anonymous towns in the US in 1998 during a six months observation period. They researched the impact of public housing on five Part I crime types. Employing density and proximity analyses for a zone 300 m the authors observed that public housing attracts all crime types stronger than the zone 300 m around it, with the number of crimes in this zone still higher compared to the entire city. Ratcliffe and Taniguchi [12] in their investigation in Camden, NJ from 2005–2006 searched for drug gang corners and their influence on violent crime, property crime, burglary, drug crime, and robbery. They used Intensity Value Analysis (IVA) and Thiessen polygon analysis to detect that the crime level around drug gang corners is higher, but their influence is spatially differentiated. Groff and McCord [13] in their study of Philadelphia, PA in 2002–2003 analyzed the influence of neighborhood parks on three crime types, including violent, against property, and public order. Using location quotients and the Analysis of Variance (ANOVA), they concluded that these parks attract only the last type of crime, although not all of them.
Quite a few of research concentrated on the influence of numerous, different land use types on one, mainly socially relevant, crime type. This line of research started in the early 1980s and continued until today. For example, Brantingham and Brantingham [14] in their early study on Cambridge, UK in 1971, tested density and rank analysis to explore the crime pattern of burglary in 31 types of land use. They observed that the most frequently burgled land uses were sports clubs, youth clubs, and restaurants. In contrast, the least frequently burgled land uses were identified to include ironmongers, doctor offices, college hostels, pubs, and tailor shops. The same authors [15] in another study on New Westminster, Canada analyzed the influence of commercial landmarks (fast food outlets, restaurants, supermarkets, department stores, and pubs) on the spatial distribution of commercial burglary. Using the density analysis, they concluded that commercial landmarks have a stronger attraction on crimes than other commercial land uses. Kinney et al. [16] in a study on Burnaby, Canada in 2005 considered the influence of different land use types (commercial, residential, civic, institutional, and recreational) on assaults and motor vehicle thefts (MVT). Applying the density and rank analysis they detected that multi-family apartment blocks, big shopping centers, schools, and universities attract assaults and MVT. Roman [17] did some research in Prince George’s County, a suburb of Washington D.C., from 1997–2000, and analyzed the influence that schools, youth hangouts, retail properties, and neighborhood disorganization have on violent crimes. The author used instrumental variables regression analysis to discover that schools, youth hangouts, retail properties, and neighborhood disorganization attract violent crimes during the whole year. Schools and youth hangouts attract violent crimes stronger during the school year. Retail properties attract violent crime on weekends. Kennedy and Caplan [18] in their investigation in Newark, NJ in 2010 were investigating the influence of residential parcels, at-risk housing, commercial and industrial parcels, residences known to burglars, pawnshops, drug markets, and public transportation nodes on residential burglary. They used regression analysis to find out that residential parcels, at-risk housing, pawnshops, known burglar residences, and drug markets host significantly more residential burglaries than other places.
Only a limited number of researchers focused on the relationship between one particular land use type and one particular crime type. For instance, McCord and Ratcliffe [19] did some research in Philadelphia, PA in 2002–2003. In this study, they analyzed the influence of 22 subway stations on street robbery. Applying the engaging Intensity Value Analysis (IVA), they observed that subway stations attract street robberies. These studies are rather narrow but allow a more in-depth analysis. Similarly, few studies analyze the influence of numerous different land use types on a set of crime types, which is also the approach followed in this current study. Greenberg et al. [20] in their exploration of Atlanta, GA in 1978 researched the interaction between eight Part I crime types and land use (housing and street types), territoriality, social cohesion, and informal territorial control in three pairs of neighborhoods. They used simple statistical analysis and observed that differences in physical characteristics distinguished between low and high crime neighborhoods to a far greater extent than did differences in informal territorial control. LaGrange [21] in his analysis in Edmonton, Canada in 1992 examined demographic characteristics of neighborhoods, shopping malls, and public and Catholic high schools and their influence on three crime types (mischief, transit vandalism, and park vandalism). In his study, he used multiple regression analysis and determined that areas containing high schools or malls and those with higher unemployment concentrate property crime. DeMotto and Davies [22] made an investigation in the state of Kansas in 2002. They tried to assess the influence of 40 parks, resource deprivation, and physical disorder in surrounding neighborhoods on many crime types. As a research method they used density analysis and found out that parks in areas of extreme resource deprivation did not serve beneficial social roles. Leitner and Helbich [23] in a study of Houston, TX in 2005 analyzed eleven socio-economic and housing variables at the census tract level before the landfall of Hurricanes Rita and Katrina and their influence on three selected crime types, including burglary, burglary of a motor vehicle, and auto theft. Applying the kernel density analysis, and spatio-temporal regression models they discovered that the short-term increase of crime, caused by the mandatory evacuation order of the city due to the approaching Hurricane Rita, was most pronounced in areas of high percentage of African Americans, persons living below the poverty level, and longer distances to the nearest police station.
These aforementioned examples analyzed mainly serious crimes, including Part I crimes. Often, indexes of total crime and broad groups of crime types were applied, for example, with the usage of violence, against property, and against public order. Some papers concentrated on an analysis of only one type of crime, e.g., breaking into houses or retail facilities, but also street crimes. Land use types, objects, facilities and areas potentially attracting crime were generally selected based on the current theoretical and empirical knowledge, including retail-service objects, buildings and areas of public utility, local traffic junctions, as well as residential areas inhabited by groups of a lower economic and social status. Despite the use of standard statistical analysis, especially in recent research, conclusions seem to be ambiguous. Researchers often state that further research taking into consideration other conditions is needed.
To conclude, it can be stated that the existing empirical research of land use and facilities influencing the spatial distribution of urban crime provides only fragmentary knowledge. The literature review has shown that the local increase in the crime level is influenced by places of concentration of people, especially potential victims and stolen objects, or neighborhoods of potential criminals, especially those under the influence of alcohol and drugs. Places of residence of deprived groups also show an increased level of local crime. The main weakness of existing research is primarily the lack of comparison between a larger number of land use and crime types.
Background Theories
Within a broad and diverse perspective of environmental criminology the following three approaches are predominant, including crime pattern theory, rational choice theory, and routine activities theory [24–26]. The crime pattern theory is now a pillar of environmental criminology and accepts the findings of the theory of rational choice and routine activities theory, however, by introducing new concepts [27]. The first is the so-called “action space”, an area in which the offender enjoys his/her everyday life. This space can be identified by nodal points, including shopping centers, workplaces, schools, recreation, and entertainment areas, which are connected with each other by paths. Both paths and nodes create an “awareness space”. Activities in space are reflected in the minds of criminals in the form of cognitive maps. Edges or lines dividing areas with different forms of land use and property are also important for offenders.
According to the crime pattern theory, rationally and reasonably motivated offenders, during daily routine activities, are in contact with a relatively small part of the city. Among the perceived and unconscious nodes, paths, and edges offenders select the appropriate objects or victims of a crime in a multistage decision-making process. The spatial distribution of crime in a city depends on its spatial pattern, land use, transport system, and the street network. Crimes are pulled by generators and attractors, and are pushed by detractors [16,27].
A crime generator is a nodal area with a high concentration of people or objects where a large number of people are drawn to for non-criminal behavior but potentially could become the subject of criminal activity. Generators attract both potential offenders living nearby, as well as offenders coming from a distant area. They indirectly influence criminal behavior with different strength. Typical generators are service-commercial streets, sports facilities, transport nodes, etc. [14].
Crime attractors are objects, areas, settlements, or districts where a high number of (potential) offenders are drawn to for criminal behavior. These targets also form the nodes of the activity of repeat offenders. They strongly and directly influence crime behavior. Typical attractors are catering services with alcohol outlets, drug trafficking places, entertainment areas of nightlife, but also large shopping malls, especially those located near transport hubs and unguarded parking areas [14].
Crime detractors are objects or areas that, for various reasons, discourage and repulse potential offenders. These include areas that are guarded or monitored, difficult to access, free of potential victims or objects of crimes, covered by cultural taboos, etc. They either directly, in case of churches, shrines and crosses, police stations, or indirectly, in case of schools, universities, cemeteries, green areas, and allotment gardens, detract crime at different levels.
One specific, deliberately formed type of detractor is the so-called defensible space, designed and organized to reduce the possibility of crimes to be carried out [14]. This concept, introduced in the early 1970s by Oscar Newman, became the basis of a number of measures aimed at creating detractors of crime [28]. Hillier [29] in his book on configurational aspects of urban space strongly influencing human behavior, suggest “that what really happens is that the natural movement of moving strangers maintains natural surveillance on space, while the static inhabitants, through their dwelling entrances and windows, maintain natural surveillance of moving strangers”. In a much earlier book, Jacobs [30] analyzed many problems of great American cities, among them the sidewalks safety. Her conclusions and proposals for solutions improving the safety in public spaces are still valid today, by stating that “First, there must be a clear demarcation between what is public space and what is private space; Second: there must be eyes upon the street, eyes belonging to those we might call the natural proprietors of the street; Third: the sidewalk must have users on it fairly continuously, both to add to the number of effective eyes on the street and to induce the people in buildings along the street to watch the sidewalks in sufficient numbers”. It would be an interesting topic to investigate the crime density on streets which meet these requirements in comparison with streets that do not meet these requirements.
The research presented in this paper is built upon concepts of crime pattern theory and routine activity theory. The approach taken in this paper introduces specific terms such as attractors, generators, and detractors of crime [16,25]. The spatial distribution of crime in a big city largely depends on its land use structure. The 30 types of land use collected for the analysis in this paper are regarded as attracting or detracting crime events and hypothetically determining the spatial distribution of crime in the city.
3. Research Area, Data, and Methods
3.1. The Case Study Area
The case study area is the Commune of the City of Szczecin, situated in the northwest of Poland, next to the Polish–German border, on the Odra River. In 2015, Szczecin had ca. 405,000 inhabitants. The total area of the city is ca. 300 km2, of which ca. 78 km2 are forest or wooded areas, ca. 70 km2 are water areas, and only ca. 45 km2 are built-up and inhabited areas (Figure 1).
Since 1989, Poland’s economic, political, and social systems have been changing rapidly. This caused the unprecedented economic growth and spread of wealth but led to some negative effects, as well, including the rapid declines of the industrial sector, state-owned farms, and, for sea-side regions, the maritime sector. This resulted in massive unemployment and emigration (see [31]), which would theoretically create a favorable crime environment for Szczecin, which was affected by these developments, as well. In fact, the crime rate in Szczecin is rather moderate in comparison with other big cities in Poland, with 34 crime incidents per 1000 inhabitants in 2010. In this context Szczecin is a good research field to study urban crime, because of the crime rate level representative for other large cities in Poland, the differentiated structure of the built-up areas (the midtown was built at the end of 19th century and was not destroyed in WWII), sea and inland port areas, industrial and postindustrial areas, vast green areas of different type (e.g., forest, large cemetery, parks, allotment gardens), single-family houses of different types and built at different times, block of flats areas build mainly in the socialist period from 1945–1990, and new gated residential areas developed in the last 15 years, serving as residences for mostly upper-class inhabitants of Szczecin. Last, but not least, the relatively high quality of the collected crime data, and the willingness by the City Police Department to cooperate is also an important factor of choosing Szczecin as the study area for this research.
6. Conclusions and Future Work
In general, the most important conclusions from this research are first that a strong influence of every land use type, of either an attracting or a detracting nature, is limited to the distance zone 0–50 m. This influence, impacts a building, an object, or an area and their immediate neighborhood. Second, land use types strongly influencing all crimes in the distance zone 0–50 m are directly acting as generators and include alcohol outlets, clubs and discos, cultural facilities, and municipal housing. One other land use type, namely commercial buildings, is indirectly acting as an attractor. Third, land use types strongly detracting all crimes in the distance zone 0–50 m are only indirectly acting detractors and include grandstands, cemeteries, green areas, allotment gardens, and depots and transport base. Fourth, the strong influence of directly acting generators of crime, namely alcohol outlets is stable throughout the entire observation period, despite the fact that the number of these facilities grew substantially from 179 in 2006 to 461 in 2010.
We believe that the results of this research are representative for other large Polish cities with crime rates averaging 30 to 40 registered offences per 1000 inhabitants (2010), such as Gdansk, Lodz, and Lublin. The main commonalities among these cities are the existence of a historical downtown area that is largely owned by the municipality and which exhibits the main tourist attractions. This area is densely populated by a socially disadvantaged population and intensively visited by tourists (especially Cracow). A further common characteristic of these cities are the large residential areas in the form of blocks of flats, as well as, single-family houses found outside the downtown area. Of course, all cities possess new shopping malls, built in the last 20 years. The capital city Warsaw, as well as Cracow, and to some extend Poznan and Wroclaw developed new metropolitan functions, and changed the structure of their downtown areas towards Central Business Districts (CBDs) in the last 25 years [47–51]. The post-industrial Silesian conurbation, including the main city Katowice, has a much higher level of crime (above 500 registered offences per 10,000 inhabitants in 2009) and a very different urban structure with a larger proportion of socially disadvantaged population, living in deprived residential and mixed areas what are “mixed” areas, as well as vast industrial and post-industrial areas.
Policy implications and limitations derived from the findings of this research are threefold. First, the downtown area of Szczecin is a spatial hot spot for many different types of crime which is caused by many land uses that serve as attractors or generators of crime, but also by social and economic factors. This area would require public security improvement programs, in addition to already existing urban regenerations programs. The main limitation to introduce such improvement programs is the territorial organization of the City Police Department of Szczecin, since the downtown area is divided into two police stations. Second, the rapidly growing number of alcohol outlets which have been identified as strong crime attractors, should be more comprehensively monitored through public security efforts. Third, an effective urban public security policy requires an improved system of crime registration, supported by mobile geocoding devices in the field and GIS-based analysis in the police headquarter and police stations around the city. The main barriers of such a system are limited financial resources and routine behavior of the police based on traditional solutions.
Future research should address the question of how social conditions together with land use types cumulatively influence the spatial distribution of different crime types in a large urban area. In addition, urban crime should be investigated at different geographic scales, namely at the global (i.e., entire city) and local (city’s neighborhoods). This requires that more advanced GIS tools and geostatistical methods have to be applied.
The population of Polish cities is diverse in terms of gender and age, education, income, and housing conditions, whereas other dimensions of diversity, including cultural, racial, ethnic, and religious that strongly condition crime in many big cities all over the world, are not important in Poland [49,52]. The population in Polish cities is segregated by education, income, and housing conditions, which is reflected in the emergence of relatively homogeneous social areas. Social areas, in turn, have different levels and intensity of crime that is committed inside their territories.
The main goal of future work should investigate whether spatial clusters (hot spots) of crime at different urban scales (global and local) are determined by social factors. A full understanding and explanation of the distribution of crime in big Polish cities requires the combined use of both land use and socioeconomic variables applying the abovementioned approaches to the same data for different cities. Neighborhoods with different social areas determine in different ways the range and strength of the influence of generators, attractors, and detractors of crime. In addition, land use types have a significant influence on social areas in which they occur. These relationships have not yet been fully understood in Poland, partly, due to the lack of relevant empirical data and appropriate research methods. Point data on crime, GIS tools and geo-statistics would allow the significant growth of knowledge in this field.
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