The paper describes the results of investigation into urban fires in the city of Vilnius, Lithuania in the three-year period of 2010-2012. Cartographic and geospatial analysis of fires is needed due to dynamism of this phenomenon, risks for inhabitants, importance to city's socio-economic development and lack of geographic approach to research of urban fires in Lithuania. The registered fires were mapped and grouped by their type (abandoned building fires, open space fires, fires in tower blocks of flats, garbage can fires, vehicle fires and arsons), cause, location type (open space and premises) and by fatality rate. Spatial distribution of fires at different scales was analysed using cartographic method and spatial analysis with GIS. Some unexpected patterns have been revealed, analysed and compared with building materials that dominate in different areas of the city. It was found out that relative frequency of fires depends on complex parameters of socio-demographic environment whereas constructional materials have little or no impact. We expected to observe a relationship between criminal activities and fires due to similar influencing socio-demographic factors. Positive correlation, though insignificant, supported this hypothesis. The study showed that fire distribution patterns may be very specific for an individual city and difficult to explain by general assumptions. Different methods of spatial, statistical and cartographic analysis must be combined in order to make reliable generalisations.
In Europe, especially in Eastern Europe, geographic research in criminology deals mainly with data analysis and accompanying cartographic communication through the visualisation of crime maps is less developed. Therefore, there is still a dearth of crime maps that could potentially not only show the facts, but also portray the criminal landscape of the city and tell the reader a story in a way that stimulates thinking, and motivates deeper analysis and spatial reasoning. This set of maps, which were designed by the authors, represent specific characteristics, density and temporal distribution of crimes in the city of Vilnius in 2014. It also shows changes in the crime rate from 2012 to 2014. The maps represent generalised data that was derived from detailed tabular data on reported criminal activities in 2012, 2013, and 2014. The primary map reveals some primary factors that allow understanding of spatio-temporal patterns of crimes in modern Vilnius: prevalent crime types with specific territorial and temporal distribution (crimes of violence, property crimes, and distribution/ possession of drugs); changes in distribution over the examined period of 3 recent years; overall crime rate and detailed structure of 9 types of crimes, the rate of burglaries and seasonality of violent crimes for all the 21 administrative districts of the city. Original cartographic signs have been designed for the depiction of 11 characteristics. The maps are supplemented by 3D visualisations and a chart that shows changes in the overall crime rate and juvenile crime numbers in the decade from 2004 to 2014. The reference scale is 1:100,000 for the Main map and 1:300,000 for complementary maps.
Policies of urban development are developed and come into force in form of laws, planning documents and other legal acts in many European countries. The Declarations of the Rights of the European Human right stresses up the safety and declares the necessity to foster a city, which as far as possible prevents crime, offenses and aggression. Both planners and citizens understand the impact of organization of urban environment to life quality, including safety. The problem is that the relationship between the environment and society is very complex. It is not sufficiently investigated how urban environment changes people who reside and socially interact in that territory and how it affects criminality. Public safety is one of the factors that strongly influence the quality of life. Reduction of crime rate can only be achieved if diverse factors, including characteristics of urban environment, are taken into account. The authors of the paper analysed possible impact of different urban parameters to the distribution and dynamics of crimes in open spaces. A theoretical framework of factors that can influence crimes in public spaces was developed on the basis of the classical 'crime triangle', linking likely offenders, suitable targets and guardians for the targets in time and space. The main initial hypothesis was that functionally homogeneous zones (i.e., 'purely' residential, commercial, or industrial) tend to have significantly higher crime rate than mixed use (polyfunctional) zones. The hypothesis was tested on a densely populated part of Vilnius city-12 districts with similar morphometric characteristics (density, height and fragmentation) of the built-up areas across the residential zone. The authors have been looking for the relationships between homoand heterogeneity of the land use and varying territorial crime patterns based on more than 10,000 registered criminal incidents of 2012. The investigation showed that territories with monofunctional commercial use are exposed to the highest risk of all types of crimes in the open space: murders and assaults, robberies and thefts and minor offenses. On the contrary, in the residential zones, less percentage of mixed use means lower crime rate.
The article presents the preliminary results of spatio-temporal analysis of the events registered by Lithuanian police in 2015–2019. Such analyses contribute to understanding of crime as a socially and spatially bound phenomenon. Distribution of crime is complex, inhomogeneous and depends on various characteristics of locations. Of all 3.48 million of events registered in the five-year period, five groups were selected for analysis: crime of violence, thefts, destruction of or damage to property, drug-related crime and public nuisance, presuming that these five groups best represent the crime situation in the country. The total amount of analysed records was 1.69 million. Point events have been aggregated into hexagonal cells 25 square kilometer each, covering the entire territory of the country. The crime rate was calculated based on the population data for each cell. Appropriate methods for the temporal and probability density analysis of crime were selected and applied to the cells, yielding relative crime probability density maps for all events and, separately, for open space events. The density information was complemented by the cells with a stable significant growth of the crime rate for five years. Thus the most problematic areas are clearly seen and can be further analysed in detail. The multi-scale lattice maps for each of the five groups of crime have been designed and made publicly available at the Lithuanian spatial information portal geoportal.lt where they can be laid over various available geospatial data and used for spatial insights.
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