Schreck, Tobias

Lade...
Profilbild
E-Mail-Adresse
ORCID
Geburtsdatum
Forschungsvorhaben
Organisationseinheiten
Berufsbeschreibung
Nachname
Schreck
Vorname
Tobias
Name
Weiterer Name

Suchergebnisse Publikationen

Gerade angezeigt 1 - 6 von 6
Vorschaubild nicht verfügbar
Veröffentlichung

Analysis and Comparison of Feature-Based Patterns in Urban Street Networks

2017-08-09, Shao, Lin, Mittelstädt, Sebastian, Goldblatt, Ran, Omer, Itzhak, Bak, Peter, Schreck, Tobias

Analysis of street networks is a challenging task, needed in urban planning applications such as urban design or transportation network analysis. Typically, different network features of interest are used for within- and between comparisons across street networks. We introduce StreetExplorer, a visual-interactive system for analysis and comparison of global and local patterns in urban street networks. The system uses appropriate similarity functions to search for patterns, taking into account topological and geometric features of a street network. We enhance the visual comparison of street network patterns by a suitable color-mapping and boosting scheme to visualize the similarity between street network portions and the distribution of network features. Together with experts from the urban morphology domain, we apply our approach to analyze and compare two urban street networks, identifying patterns of historic development and modern planning approaches, demonstrating the usefulness of StreetExplorer.

Lade...
Vorschaubild
Veröffentlichung

Visual analytics of urban environments using high-resolution geographic data

2010, Bak, Peter, Omer, Itzhak, Schreck, Tobias

High-resolution urban data at house level are essential for understanding the relationship between objects of the urban built environment (e.g. streets, housing types, public resources and open spaces). However, it is rather difficult to analyze such data due to the huge amount of urban objects, their multidimensional character and the complex spatial relation between them. In this paper we propose a methodology for assessing the spatial relation between geo-referenced urban environmental variables, in order to identify typical or significant spatial configurations as well as to characterize their geographical distribution. Configuration in this sense refers to the unique combination of different urban environmental variables. We structure the analytic process by defining spatial configurations, multidimensional clustering of the individual configurations, and identifying emerging patterns of interesting configurations. This process is based on the tight combination of interactive visualization methods with automatic analysis techniques. We demonstrate the usefulness of the proposed methods and methodology in an application example on the relation between street network topology and distribution of land uses in a city.

Lade...
Vorschaubild
Veröffentlichung

A visual analytics approach for assessing pedestrian friendliness of urban environments

2013, Schreck, Tobias, Omer, Itzhak, Bak, Peter, Lerman, Yoav

The availability of efficient transportation facilities is vital to the function and development of modern cities. Promoting walking is crucial for supporting livable communities and cities. Assessing the quality of pedestrian facilities and constructing appropriate pedestrian walking facilities are important tasks in public city planning. Additionally, walking facilities in a community affect commercial activities including private investment decisions such as those of retailers. However, analyzing what we call pedestrian friendliness in an urban environment involves multiple data perspectives, such as street networks, land use, and other multivariate observation measurements, and consequently poses significant challenges. In this study, we investigate the effect of urban environment properties on pedestrian movement in different locations in the metropolitan region of Tel Aviv. The first urban area we investigated was the inner city of the Tel Aviv metropolitan region, one of the central regions in Tel Aviv, a city that serves many non-local residents. For simplicity, we refer to this area as Tel Aviv. We also investigated Bat Yam, a small city, whose residents use many of the services of Tel Aviv. We apply an improved tool for visual analysis of the correlation between multiple independent and one dependent variable in geographical context. We use the tool to investigate the effect of functional and topological properties on the volume of pedestrian movement. The results of our study indicate that these two urban areas differ greatly. The urban area of Tel Aviv has much more correspondence and interdependency among the functional and topological properties of the urban environment that might influence pedestrian movement. We also found that the pedestrian movements as well as the related urban environment properties in this region are distributed geographically in a more equal and organized form.

Lade...
Vorschaubild
Veröffentlichung

Using space–time visual analytic methods for exploring the dynamics of ethnic groups' residential patterns

2010, Omer, Itzhak, Bak, Peter, Schreck, Tobias

In this article, we present a methodological framework, based on georeferenced house-level socio-demographic and infrastructure data, for investigating minority (or ethnic) group residential pattern dynamics in cities. This methodology, which uses visual analytical tools, is meant to help researchers examine how local land-use configurations shape minorities' residential dynamics and, thereby, affect the level of minority–majority segregation. This methodology responds to the need to refer to the relationship between local land-use configurations and the identity of a building's residents, without simultaneously revealing sensitive house-related details. The research was instantiated on the residential patterns exhibited by the Arab community in Jaffa, Israel. The residential data were collected for over 40 years at four different moments, each associated with the population and housing censuses conducted by Israel's Central Bureau of Statistics and the Ministry of the Interior. Using this methodology enabled us to remain on the level of the individual building when identifying the relationships between spatial land-use configurations and rates of change in ethnic composition and the Arab community's residence pattern dynamics at different geographical scales. It likewise allowed us to identify the qualitative changes in the population's residential preferences during the pattern's development.

Vorschaubild nicht verfügbar
Veröffentlichung

A framework for using self-organising maps to analyse spatio-temporal patterns, exemplified by analysis of mobile phone usage

2010-09, Andrienko, Gennady, Andrienko, Natalia, Bak, Peter, Bremm, Sebastian, Keim, Daniel A., von Landesberger, Tatiana, Pölitz, Christian, Schreck, Tobias

We suggest a visual analytics framework for the exploration and analysis of spatially and temporally referenced values of numeric attributes. The framework supports two complementary perspectives on spatio-temporal data: as a temporal sequence of spatial distributions of attribute values (called spatial situations) and as a set of spatially referenced time series of attribute values representing local temporal variations. To handle a large amount of data, we use the self-organising map (SOM) method, which groups objects and arranges them according to similarity of relevant data features. We apply the SOM approach to spatial situations and to local temporal variations and obtain two types of SOM outcomes, called space-in-time SOM and time-in-space SOM, respectively. The examination and interpretation of both types of SOM outcomes are supported by appropriate visualisation and interaction techniques. This article describes the use of the framework by an example scenario of data analysis. We also discuss how the framework can be extended from supporting explorative analysis to building predictive models of the spatio-temporal variation of attribute values. We apply our approach to phone call data showing its usefulness in real-world analytic scenarios.

Lade...
Vorschaubild
Veröffentlichung

Space-in-Time and Time-in-Space Self-Organizing Maps for Exploring Spatiotemporal Patterns

2010, Andrienko, Gennady L., Andrienko, Natalia, Bremm, S., Schreck, Tobias, Landesberger, Tatiana von, Bak, Peter, Keim, Daniel A.

Spatiotemporal data pose serious challenges to analysts in geographic and other domains. Owing to the complexity of the geospatial and temporal components, this kind of data cannot be analyzed by fully automatic methods but require the involvement of the human analyst's expertise. For a comprehensive analysis, the data need to be considered from two complementary perspectives: (1) as spatial distributions (situations) changing over time and (2) as profiles of local temporal variation distributed over space. In order to support the visual analysis of spatiotemporal data, we suggest a framework based on the “Self-Organizing Map” (SOM) method combined with a set of interactive visual tools supporting both analytic perspectives. SOM can be considered as a combination of clustering and dimensionality reduction. In the first perspective, SOM is applied to the spatial situations at different time moments or intervals. In the other perspective, SOM is applied to the local temporal evolution profiles. The integrated visual analytics environment includes interactive coordinated displays enabling various transformations of spatiotemporal data and post-processing of SOM results. The SOM matrix display offers an overview of the groupings of data objects and their two-dimensional arrangement by similarity. This view is linked to a cartographic map display, a time series graph, and a periodic pattern view. The linkage of these views supports the analysis of SOM results in both the spatial and temporal contexts. The variable SOM grid coloring serves as an instrument for linking the SOM with the corresponding items in the other displays. The framework has been validated on a large dataset with real city traffic data, where expected spatiotemporal patterns have been successfully uncovered. We also describe the use of the framework for discovery of previously unknown patterns in 41-years time series of 7 crime rate attributes in the states of the USA.