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The paper investigates if and where registered crime and the fear of crime intersect in the four locations. This information is important to reduce crime and increase the sense of security of the population. In the past, research was applied to small parts of a city or a whole city, but not in as much detail as this paper. Our research is detailed, and at the same time is applied to four entire locations - three Czech cities (Ostrava, Olomouc, and Kolín) and one Prague district (Prague 12). We placed registered crime and fear of crime on one map to show locations where people feel afraid, where crime happens, and where both events occur together. We drew these phenomena using Moran's I in a bivariate map. The outputs will be applied by Municipal governments and police departments. [ABSTRACT FROM AUTHOR]

One of the ways of improving the attractiveness of public transport is to bring it closer to its potential users. A long walking distance from a stop is often one of the critical factors limiting its more frequent and extensive use. Studies dealing with the accessibility of transport networks usually work only with the closest stop. This article analyses the actual walking distance from the place of residence to the preferred stop. The survey used a questionnaire method and was conducted in two cities in the Czech Republic—Ostrava and Olomouc. Based on the results of the study, the average walking distance was assessed and the impact of demographic characteristics (gender, age, education, number of members in the household, economic activity, the presence of a child in the household, and car ownership), transport behavior (preferred mode of transportation, car convenience and opinions on public transport), and urban characteristics (prevailing housing type) on the walking distance were analyzed. The main findings prove a significant impact on walking distance by a number of these factors, but the preferred use of a car for commuting or unemployment does not significantly affect walking distance. [ABSTRACT FROM AUTHOR]

The principal objective of this paper is to evaluate the spatial patterns of creative industries in a micro-geographic perspective. As the creative industries represent a highly heterogeneous complex, only selected creative industries were studied (culture, marketing and advertising, printing, publishing, architecture). The polycentric industrial city of Ostrava was chosen as the surveyed area. Various spatial statistical methods (e.g. nearest neighbour analysis, kernel density estimation) were applied for the needs of assessment. The results show that spatial patterns of creative industries at intra-urban level do not vary significantly from their counterparts in Western Europe. Despite the fact that Ostrava is highly industrialized polycentric city with relatively weak position of the city centre, creative industries are highly concentrated into the historical city centre and the inner city. [ABSTRACT FROM AUTHOR]

This paper is focused on mapping and monitoring of unemployment hot spots using registers of local authorities in the Ostrava City (Czech Republic) to identify socially excluded localities at the micro-scale. The register of unemployed persons and the population register provide data for quantification of specific indicators of a local labour situation. A share of the registered unemployed in reference to residents in productive age can substitute the rate of unemployment due to the high correlation of both indicators. The mapping of unemployment hot spots has been based on data from 2007, 2009, 2010 and 2011 using kernel density estimation. Various settings of bandwidths have been tested to identify socially excluded localities in the city in hopes of identifying the most accurate way to visualise the pattern. These localities have been identified in two expert studies and the most significant sign is considered to be increased unemployment. Appropriate settings of kernel density estimations of the unemployment indicator enable to identify the majority of experts' localised spots. The hot spots have been delimited by an isoline with a suitable boundary value obtained from an optimisation technique based on a coefficient of areal correspondence and an indicator of spatial extension. This method of isolines is recommended for mapping and monitoring of the development of localities in time. [ABSTRACT FROM AUTHOR]

The fear of crime is an established research topic, not only in sociology, environmental psychology and criminology, but also in GIScience. Using spatial analysis to analyse patterns, explore hotspots and determine the significance of respective surveys is one reason for the increase in popularity of such research topics for geographers, cartographers and spatial data scientists. This paper presents the results of an intensive online map-based questionnaire with 1551 respondents from the city of Ostrava, Czech Republic. The respondents marked 3792 points associated with the fear of crime over a ten week period. The perception data were compared with recorded crime data acquired from police department records for the years 2015–2018. This paper explores the spatial autocorrelation from perceived hotspots and from recorded crime hotspots. Our findings fit into the literature confirming results about the locations that most frequently attract fear, but there is still room for more investigations regarding the links between recorded crime and the fear of crime. [ABSTRACT FROM AUTHOR]