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Abstract Empirical data on human evacuation behavior are invaluable for adjusting and training computational algorithms that simulate evacuation processes, including agent-based modeling. We provide a dataset on human decision-making during evacuations from virtual buildings, captured using experimental methods that controlled specific building layout parameters. An online experiment assigned participants a random subset of tasks featuring T-intersections. Data from 208 respondents, aged 17 to 71, were analyzed, considering education levels and excluding those with significant technical issues. Quantitative data on user interaction and evacuation route choices included decision time, mouse rotation, and the selected corridor, recorded through mouse clicks on invisible areas of interest. Respondents also self-reported their choice confidence on a Likert scale. Additionally, responses to final retrospective evaluation questionnaires were recorded. This dataset offers diverse research opportunities, particularly in emergency evacuation planning, where understanding evacuation choices in simulations can inform real-world strategies. It supports the development of models to predict human behavior in emergencies using machine learning and predictive modeling and is accessible for both academic and commercial use.

This study investigates the utilization of YouTube as a data source in crisis management, focusing on human behavior during a tornado event in the Southern Moravia Region, Czech Republic, in 2021. Utilizing YouTube's Data API, we harvested video metadata and content to explore spatio-temporal patterns in disaster impact and recovery. Our analysis reveals how YouTube content reflects the immediate and long-term responses to the disaster, offering insights into community reactions, damage extent, and recovery processes. By integrating automated and manual content analysis, we uniquely demonstrate YouTube's potential in enhancing spatial analyses and visualizations for disaster management. This research underscores the value of social media data in providing multiple perspectives on human behavior during and after disaster, contributing to a nuanced understanding of disaster impact and community resilience.

Abstract The building design is a crucial factor that can be actively adjusted and optimized to prevent human and property threats in emergency scenarios. Previous research suggests that specific building layouts may significantly influence human behaviour during evacuation. However, detailed empirical data about human behaviour in various types of buildings with different layouts are still missing and only marginal recommendations from this field are reflected in actual construction practice. In this study, desktop VR technologies were employed to study human decision-making in problematic T-intersections in the context of an emergency evacuation. More specifically, we studied fundamental attributes of buildings such as the width and length of the corridors and the presence of stairs to explore how they influence the choice of the evacuation route. The space-syntax isovist method was used to describe spatial parameters of corridors, which makes the results applicable to all buildings. Behavioural data from 208 respondents were analysed using multilevel regression models. Our results support previous claims concerning the importance of specific spatial layouts of evacuation corridors because respondents systematically chose wider and shorter corridors with visible staircases as the preferred evacuation route. The present findings further promote the ongoing discussion on the design of marked evacuation routes and building design that takes human factors into consideration.

Agent-based evacuation modeling represents an effective tool for making predictions about evacuation aspects of buildings such as evacuation times, congestions, and maximum safe building capacity. Collection of real behavioral data for calibrating agent-based evacuation models is time-consuming, costly, and completely impossible in the case of buildings in the design phase, where predictions about evacuation behavior are especially needed. In recent years evacuation experiments conducted in virtual reality (VR) have been frequently proposed in the literature as an effective tool for collecting data about human behavior. However, empirical studies which would assess validity of VR-based data for such purposes are still rare and considerably lacking in the agent-based evacuation modeling domain. This study explores opportunities that the VR behavioral data may bring for refining outputs of agent evacuation models. To this end, this study employed multiple input settings of agent-based evacuation models (ABEMs), including those based on the data gathered from the VR evacuation experiment that mapped out evacuation behaviors of individuals within the building. Calibration and evaluation of models was based on empirical data gathered from an original evacuation exercise conducted in a real building (N = 35) and its virtual twin (N = 38). This study found that the resulting predictions of single agent models using data collected in the VR environment after proposed corrections have the potential to better predict real-world evacuation behavior while offering desirable variance in the data outputs necessary for practical applications.

The use of 3D visualization technologies has increased rapidly in many applied fields, including geovisualization, and has been researched from many different perspectives. However, the findings for the benefits of 3D visualization, especially in stereoscopic 3D forms, remain inconclusive and disputed. Stereoscopic "real" 3D visualization was proposed as encouraging the visual perception of shapes and volume of displayed content yet criticised as problematic and limited in a number of ways, particularly in visual discomfort and increased response time in tasks. In order to assess the potential of real 3D visualization for geo-applications, 91 participants were engaged in this study to work with digital terrain models in different 3D settings. The researchers examined the effectivity of stereoscopic real 3D visualization compared to monoscopic 3D (or pseudo 3D) visualization under static and interactive conditions and applied three tasks with experimental stimuli representing different geo-related phenomena, i.e. objects in the terrain, flat areas marked in the terrain and terrain elevation profiles. The authors explored the significant effects of real 3D visualization and interactivity factors in terms of response time and correctness. Researchers observed that the option to interact (t = -10.849, p < 0.001) with a virtual terrain and its depiction with real 3D visualization (t = 4.64, p < 0.001) extended the participants' response times. Counterintuitively, the data demonstrated that the static condition increased response correctness (z = 5.38, p < 0.001). Regarding detailed analysis of data, an interactivity factor was proposed as a potential substitute for real 3D visualization in 3D geographical tasks.

From the user perspective, 3D geospatial data visualizations are one of the bridges between the physical and the digital world. As such, the potential of 3D geospatial data visualizations is frequently discussed within and beyond the digital twins. The effects on human cognitive processes in complex spatial tasks is rather poorly known. No uniform standards exist for the 3D technologies used in these tasks. Although stereoscopic geovisualizations presented using 3D technologies enhance depth perception, it has been suggested that the visual discomfort experienced when using 3D technology outweighs its benefits and results in lower efficiency and errors. In the present study, sixty participants using 3D technologies were tested in terms of their ability to make informed decisions in selecting the correct position of a virtual transmitter in a digital twin and a digital terrain model, respectively. Participants (n = 60) were randomly assigned into two groups, one using 3D technology engaging stereoscopic shutter glasses and the second working with standard computer screen-based visualizations. The results indicated that the participants who used shutter glasses performed significantly worse in terms of response time (W = 175.0; p < 0.001, r = −0.524). This finding verifies previous conclusions concerning the unsuitability of stereoscopic visualization technology for complex decision-making in geospatial tasks.

This manuscript identifies and documents unsolved problems and research challenges in the extended reality (XR) domain (i.e., virtual (VR), augmented (AR), and mixed reality (MR)). The manuscript is structured to include technology, design, and human factor perspectives. The text is visualization/display-focused, that is, other modalities such as audio, haptic, smell, and touch, while important for XR, are beyond the scope of this paper. We further narrow our focus to mainly geospatial research, with necessary deviations to other domains where these technologies are widely researched. The main objective of the study is to provide an overview of broader research challenges and directions in XR, especially in spatial sciences. Aside from the research challenges identified based on a comprehensive literature review, we provide case studies with original results from our own studies in each section as examples to demonstrate the relevance of the challenges in the current research. We believe that this paper will be of relevance to anyone who has scientific interest in extended reality, and/or uses these systems in their research.

This work addresses the impact of a geovisualization’s level of realism on a user’s experience in indoor navigation. The key part of the work is a user study in which participants navigated along a designated evacuation route previously learnt in a virtual tour or traditional 2D floor plan. The efficiency and effectiveness of completing the task was measured by the number of incorrect turns during navigation and completion time. The complexity of mental spatial representations that participants developed before and after navigating the route was also evaluated. The data was obtained using several qualitative and quantitative research methods (mobile eye tracking, structured interviews, sketching of cognitive maps, creation of navigation instructions, and additional questions to evaluate spatial orientation abilities). A total of 36 subjects (17 in the “floor plan” group and 19 in the “virtual tour” group) participated in the study. The results showed that the participants from both groups were able to finish the designated navigation route, but more detailed mental spatial representations were developed by the “virtual tour” group than the “floor plan” group. The participants in the virtual tour group created richer navigation instructions both before and after evacuation, mentioned more landmarks and could recall their characteristics. Visual landmark characteristics available in the virtual tour also seemed to support the correct decision-making.