Methods of Regional Analysis: An Introduction to Regional Science.

Machine learning is useful for grid-based crime prediction. Many previous studies have examined factors including time, space, and type of crime, but the geographic characteristics of the grid are rarely discussed, leaving prediction models unable to predict crime displacement. This study incorporates the concept of a criminal environment in grid-based crime prediction modeling, and establishes a range of spatial-temporal features based on 84 types of geographic information by applying the Google Places API to theft data for Taoyuan City, Taiwan. The best model was found to be Deep Neural Networks, which outperforms the popular Random Decision Forest, Support Vector Machine, and K-Near Neighbor algorithms. After tuning, compared to our design’s baseline 11-month moving average, the F1 score improves about 7% on 100-by-100 grids. Experiments demonstrate the importance of the geographic feature design for improving performance and explanatory ability. In addition, testing for crime displacement also shows that our model design outperforms the baseline.

https://www.mdpi.com/2220-9964/7/8/298/pdf

Grid-Based Crime Prediction Using Geographical Features

Most studies of spatial colocation patterns of crime and land-use features in geographical information science and environmental criminology employ global measures, potentially obscuring spatial inhomogeneity. This study investigated the relationships of three types of crime with 22 types of land-use in Wuhan, China. First, global colocation patterns were examined. Then, local colocation patterns were examined based on the recently-proposed local colocation quotient, followed by a detailed comparison of the results. Different types of crimes were encouraged or discouraged by different types of land-use features with varying intensity, and the local colocation patterns demonstrated spatial inhomogeneity.

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The Local Colocation Patterns of Crime and Land-Use Features in Wuhan, China

Managing Service Operations: Design and Implementation

In the spatial analysis of crime, the residential population has been a conventional measure of the population at risk. Recent studies suggest that the ambient population is a useful alternative measure of the population at risk that can better capture the activity patterns of a population. However, current studies are limited by the availability of high precision demographic characteristics, such as social activities and the origins of residents. In this research, we use spatially referenced mobile phone data to measure the size and activity patterns of various types of ambient population, and further investigate the link between urban larceny-theft and population with multiple demographic and activity characteristics. A series of crime attractors, generators, and detractors are also considered in the analysis to account for the spatial variation of crime opportunities. The major findings based on a negative binomial model are three-fold. (1) The size of the non-local population and people’s social regularity calculated from mobile phone big data significantly correlate with the spatial variation of larceny-theft. (2) Crime attractors, generators, and detractors, measured by five types of Points of Interest (POIs), significantly depict the criminality of places and impact opportunities for crime. (3) Higher levels of nighttime light are associated with increased levels of larceny-theft. The results have practical implications for linking the ambient population to crime, and the insights are informative for several theories of crime and crime prevention efforts.

https://www.mdpi.com/2220-9964/9/6/342/pdf

Ambient Population and Larceny-Theft: A Spatial Analysis Using Mobile Phone Data

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.

https://www.mdpi.com/2220-9964/6/3/74/pdf

Land Use Influencing the Spatial Distribution of Urban Crime: A Case Study of Szczecin, Poland

Public transportation in cities is crucial for their sustainable development. The attractiveness of public transport for city residents depends largely on whether they are able to access the nearest stop on foot. The actual time of walking to the nearest stop and the distance covered can be measured using the band method or the circular buffer method. The accuracy of the two methods was compared for the city of Szczecin and one of its residential areas, Pomorzany (ca. 20,000 inhabitants, ca. 7 km2 area). The city provides public tram and bus transportation and has 90 km of streets and pedestrian paths. As shown by the results, the band method proved more accurate in measuring public transport stop accessibility. It showed 53.8% of the stops to be highly accessible, whereas 37.8%, 7.8%, and 0.5% were classified as moderately accessible, poorly accessible, and inaccessible, respectively; the latter would be hardly expected to be used by pedestrians in the Pomorzany neighborhood. The band method allowed also to indicate potential location of a new bus stop which would significantly improve accessibility of public transportation to residents of a housing estate (3000 inhabitants) in the area.

Walking Access to Public Transportation Stops for City Residents. A Comparison of Methods

Changes in the health situation of the population of Poland following the accession to the European Union (Compared to central and eastern european countries)

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Celem niniejszego artykulu jest analiza rozmieszczenia przestepstw stwierdzonych przez policje w 2015 r w zakonczonych postepowaniach przygotowawczych w miastach na prawach powiatu w Polsce Oprocz analizy rozmieszczenia poszczegolnych rodzajow przestepstw poszukiwano takze zalezności pomiedzy rozmiarami i koncentracją przestepstw w miastach a ich wielkością i znaczeniem w sieci osadniczej kraju Dane o liczbie popelnionych przestepstw zgromadzono i analizowano wedlug nastepujących sześciu kategorii: przestepstwa ogolem, przestepstwa kryminalne, przestepstwa gospodarcze, przestepstwa drogowe, przestepstwa przeciwko zyciu i zdrowiu, przestepstwa przeciwko mieniu Analizie poddano 49 jednostek przestrzennych stanowiących trzon ukladu osadniczego Polski Jako miare koncentracji przestepstw w miastach i grupach miast wykorzystano wskaźnik lokalizacji wzgledem liczby ludności Rozmieszczenie podstawowych kategorii przestepstw w miastach na prawach powiatu jest silnie zroznicowane Obie metropolie zagrozone są glownie przestepczością gospodarczą Aspirujące metropolie, szybko i burzliwie rozwijające sie wielkie miasta, są zagrozone zwlaszcza przestepstwami kryminalnymi i przeciwko mieniu Duze ośrodki regionalne zagrozone są przede wszystkim przestepstwami przeciwko zyciu i zdrowiu, natomiast w najmniejszym stopniu przestepstwami gospodarczymi Średnie ośrodki regionalne reprezentują przecietny poziom koncentracji, liczba przestepstw wszystkich kategorii odpowiada liczbie ludności Najmniej zagrozone przestepczością są male ośrodki regionalne

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Rozmieszczenie przestępstw w miastach na prawach powiatu w Polsce

Based on data from eight Polish cities, we tested if closed-circuit television (CCTV) monitoring systems are effective in crime reduction and if the CCTV monitoring effects are durable. In a quasi-...

Natalia Sypion-Dutkowska

Papers

Land Use Influencing the Spatial Distribution of Urban Crime: A Case Study of Szczecin, Poland

Walking Access to Public Transportation Stops for City Residents. A Comparison of Methods

Changes in the health situation of the population of Poland following the accession to the European Union (Compared to central and eastern european countries)

Rozmieszczenie przestępstw w miastach na prawach powiatu w Polsce

Effectiveness of CCTV systems as a crime preventive tool: evidence from eight Polish cities