GI_Forum 2022, Volume 10, Issue 2

Challenges related to population ageing and urbanization have become major topics in society over the last two generations. With the emergence of the concept of sustainability, cities are required to develop age‐friendly environments and improve the quality of urban life. This study aims to expand the currently loosely defined concept of the healthy ageing society and the framework provided by the World Health Organization (WHO). Access by elderly people to public transport is crucial for them to develop and maintain their functional abilities in society and in creating sustainable urban development. This research addresses the topic of spatial accessibility for elderly people, helping to quantify and analyse their needs and expectations within a Healthy Ageing context. As policy making is shaped significantly by the use of indicators, the investigation and discussion of indicators are important tools to facilitate policy developments and adjustments.

Keywords: healthy ageing, spatial accessibility, geographic information system (gis), indicator studies, policy development

Land cover changes have been mapped for decades to investigate urban expansion patterns. Under the UN Sustainable Development Goals (SDGs), several indices are employed to interpret urban growth trends quantitatively and comprehensively. However, landowners and the interested public usually have limited insights into these types of information as access to data and software is limited. Static maps and the inability to access special file formats increase the difficulty of viewing and investigating the data. This contribution presents a dedicated, interactive, web-based analysis tool for integrating land cover and land use maps as well as urban expansion indices. The tool’s concept, development and functionality are presented, and its general design is reviewed based on an actual implementation case. The setup allows integrating land use and land cover (LULC) change data alongside SDG indicators. The tool’s design aims to enhance user accessibility to information on urban expansion indices and LULC. We demonstrate that such a tool can be used to help disseminate results and to improve communication with the public in the context of other use cases.

Keywords: Web GIS, land use and land cover change, lulc, urban expansion, sustainable development goals, sdg

Urban planning benefits significantly from improved knowledge concerning spatiotemporal relationships and patterns in cities based on geospatial factors. In this context, the potential of geodata seems inexhaustible. Applications include limited-service offers like carparks, the occupancy of which is controlled by geospatial factors characterized by their spatiotemporal patterns. This paper proposes an enhanced model for identifying geospatial key factors, tying in with an existing geo-analytics model. Our approach combines real-world empirical data for off-street parking with open-source geodata on points of interest. We formulate stabilization measures in different model-enhancement stages to optimize model reliability and fit, based on analyses of statistical characteristics. Additionally, we consider modifying the choice of geospatial factors in order to reduce multicollinearity. Our results show improved reliability of geo-analytics for the identification of urban spatiotemporal relationships.

Keywords: geo-analytics, metric of geospatial impact, urban analysis, smart city planning, smart mobility

Growing interest in Urban Green Spaces (UGSs) has led to the discovery of the wide spectrum of services that they either provide or support. Yet, there is persistent confusion about what types of green spaces exist and how they should be classified. Current Land Use (LU) and Land Cover (LC) maps both at European and national levels are either lacking or misclassify various types of UGS, thus underestimating the actual amount of green space that a city offers its citizens. In this paper, we highlight reasons for green space misclassification and suggest an ontology of UGSs. Our ontology takes into account both the physical appearance of UGSs and their semantics. We characterize the physical appearance using four different LC classes while providing semantics using unique characteristics expressed as rules. The ontology proposed emphasizes in particular frequently disregarded small and heterogeneous UGSs and can be used as a basis for their precise identification and mapping.

Keywords: ontology, urban green spaces, urban atlas, OSM

There is currently no standardized methodology for evaluating the impacts of road infrastructure measures on different road-user groups or the mobility system. In the POSITIM project, we developed a standardized methodology that allows us to evaluate systemic and personal effects of infrastructural interventions. The evaluation criteria were safety, stress, smoothness, acceptance of the intervention, and mobility behaviour.

Keywords: mixed-methods, human sensing, GIS, qualitative interviews, evaluation, planning

Various methods, for example image recognition, speech-to-text algorithms, and natural language processing, can be used to capture location references in linear and non-linear media content. The methods differ in terms of the technologies, procedures or media, such as the audio track or video images. Our investigation, which is based on the metadata of a video, reveals that georeferencing media content is possible, and that, using examples from the ARD Mediathek, the genre and thus the content of a video can influence the results.

Keywords: georeferencing, media content, image, Audio, recognition, data analysis

Gaining insights from trajectory datasets is a challenging task that requires suitable visual data representations. There is a considerable gap between the state-of-the-art cartographic techniques presented in the literature and currently available spatial data science toolboxes. This review paper presents the current state of geospatial visualization tools for trajectory data, focusing on the Python and Jupyter notebooks ecosystem. The shortcomings identified provide pointers for further scientific software development, as well as a reference for data scientists in choosing the best-fitting tool for a specific job.

Keywords: trajectories, movement data analysis, visual analysis, exploratory data analysis