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Urban flooding, as one of the most serious natural disasters, has caused considerable personal injury and property damage throughout the world. To better cope with the problem of waterlogging, the experts have developed many waterlogging models that can accurately simulate the process of pipe network drainage and water accumulation. The study of urban waterlogging involves many data types. These data come from the departments of hydrology, meteorology, planning, surveying, and mapping, etc. The incoordination of space–time scale and format standard has brought huge obstacles to the study of urban waterlogging. This is not conducive to interpretation, transmission, and visualization in today’s network environment. In this paper, the entities and attributes related to waterlogging are defined. Based on the five modules of urban drainage network, sub basin, dynamic water body, time series, and meteorological data, the corresponding UML (Unified Modeling Language) model is designed and constructed. On this basis, the urban waterlogging application domain extension model city waterlogging application domain extension (CTWLADE) is established. According to the characteristics of different types of data, two different methods based on FME object and citygml4j are proposed to realize the corresponding data integration, and KML (Keyhole Markup Language) /glTF data organization form and the corresponding sharing method are proposed to solve the problem that the CTWLADE model data cannot be visualized directly on the web and cannot interact in three-dimensional format. To evaluate the CTWLADE, a prototype system was implemented, which can convert waterlogging-related multi-source data in extensible markup language (XML) files conform. The current CTWLADE can map the data required and provided by the hydraulic software tool storm water management model (SWMM) and is ready to be integrated into a Web 3D Service to provide the data for 3D dynamic visualization in interactive scenes.

This paper describes a new tool for eye-tracking data and their analysis with the use of interactive 3D models. This tool helps to analyse interactive 3D models easier than by time-consuming, frame-by-frame investigation of captured screen recordings with superimposed scanpaths. The main function of this tool, called 3DgazeR, is to calculate 3D coordinates (X, Y, Z coordinates of the 3D scene) for individual points of view. These 3D coordinates can be calculated from the values of the position and orientation of a virtual camera and the 2D coordinates of the gaze upon the screen. The functionality of 3DgazeR is introduced in a case study example using Digital Elevation Models as stimuli. The purpose of the case study was to verify the functionality of the tool and discover the most suitable visualization methods for geographic 3D models. Five selected methods are presented in the results section of the paper. Most of the output was created in a Geographic Information System. 3DgazeR works with generic CSV files, SMI eye-tracker, and the low-cost EyeTribe tracker connected with open source application OGAMA. It can compute 3D coordinates from raw data and fixations.

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.

This paper presents the results of an empirical economic data-based survey of the costs and revenues of geographical data and Web services across public administration in Czechia. The survey was composed of questionnaires and interviews. The data was collected from the 19 biggest public producers of geographical information and 25 organizations that use geographical information. The results focus on the economic consequences of data opening, splitting finances within public administration bodies, the prioritization of activities related to geographical information, licensing issues and life cycle planning etc. We also consider user opinions on the restrictions on the (re)use of geographical information of public administration, including open data.

Population distribution modelling can benefit many different domains, for example, transportation, urban planning, ecology or emergency management. Information about the location and number of people in an affected area is crucial for decision-makers during emergencies and crises. Mobile phone data represents relatively reliable and time accurate information on real-time population distribution, movement and behaviour. In this study, we evaluate the spatio-temporal distribution of population derived from phone data of the selected pilot area (City of Brno, Czech Republic). Analysis is based on the dataset describing the estimated human presence (EHP) with two values – visitors and transiting persons. The temporal change of data is first analysed and further processed using two methodological approaches. First, the dasymetric method is used where the building geometry and technical attributes served as a target layer. Second, the results of building level analysis are transformed into a regular grid zone of both visitors and the general EHP. Resulting spatio-temporal patterns are compared to the census data. Results demonstrate how the proposed building level dasymetric approach can improve the spatial granularity of EHP. Potential use of proposed methodology within selected emergency situations is further discussed.

Three-dimensional geovisualizations are currently pushed both by technological development and by the demands of experts in various applied areas. In the presented empirical study, we compared the features of real 3D (stereoscopic) versus pseudo 3D (monoscopic) geovisualizations in static and interactive digital elevation models. We tested 39 high-school students in their ability to identify the correct terrain profile from digital elevation models. Students’ performance was recorded and further analysed with respect to their spatial abilities, which were measured by a psychological mental rotation test and think aloud protocol. The results of the study indicated that the influence of the type of 3D visualization (monoscopic/stereoscopic) on the performance of the users is not clear, the level of navigational interactivity has significant influence on the usability of a particular 3D visualization, and finally no influences of the spatial abilities on the performance of the user within the 3D environment were identified.

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.

Efforts related to minimizing the environmental burden caused by agricultural activities and increasing economic efficiency are key contemporary drivers in the precision agriculture domain. Controlled Traffic Farming (CTF) techniques are being applied against soil compaction creation, using the on-line optimization of trajectory planning for soil-sensitive field operations. The research presented in this paper aims at a proof-of-concept solution with respect to optimizing farm machinery trajectories in order to minimize the environmental burden and increase economic efficiency. As such, it further advances existing CTF solutions by including (1) efficient plot divisions in 3D, (2) the optimization of entry and exit points of both plot and plot segments, (3) the employment of more machines in parallel and (4) obstacles in a farm machinery trajectory. The developed algorithm is expressed in terms of unified modeling language (UML) activity diagrams as well as pseudo-code. Results were visualized in 2D and 3D to demonstrate terrain impact. Verifications were conducted at a fully operational commercial farm (Rostěnice, the Czech Republic) against second-by-second sensor measurements of real farm machinery trajectories.

Detailed measurements of yield values are becoming a common practice in precision agriculture. Field harvesters generate point Big Data as they provide yield measurements together with dozens of complex attributes in a frequency of up to one second. Such a flood of data brings uncertainties caused by several factors: accuracy of the positioning system used, trajectory overlaps, raising the cutting bar due to obstacles or unevenness, and so on. This paper deals with 2D and 3D cartographic visualizations of terrain, measured yield, and its uncertainties. Four graphic variables were identified as credible for visualizations of uncertainties in point Big Data. Data from two plots at a fully operational farm were used for this purpose. ISO 19157 was examined for its applicability and a proof-of-concept for selected uncertainty expression was defined. Special attention was paid to spatial pattern interpretations.

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.

Yield is one of the primary concerns for any farmer since it is a key to economic prosperity. Yield productivity zones—that is to say, areas with the same yield level within fields over the long-term—are a form of derived (predicted) data from periodic remote sensing, in this study according to the Enhanced Vegetation Index (EVI). The delineation of yield productivity zones can (a) increase economic prosperity and (b) reduce the environmental burden by employing site-specific crop management practices which implement advanced geospatial technologies that respect soil heterogeneity. This paper presents yield productivity zone identification and computing based on Sentinel-2A/B and Landsat 8 multispectral satellite data and also quantifies the success rate of yield prediction in comparison to the measured yield data. Yield data on spring barley, winter wheat, corn, and oilseed rape were measured with a spatial resolution of up to several meters directly by a CASE IH harvester in the field. The yield data were available from three plots in three years on the Rostěnice Farm in the Czech Republic, with an overall acreage of 176 hectares. The presented yield productivity zones concept was found to be credible for the prediction of yield, including its geospatial variations.

Yield mapping is a subject of research in (precision) agriculture and one of the primary concerns for farmers as it forms the basis of their income and has implications for subsidies and taxes. The presented approach involves deployment of field harvesters equipped with sensors that provide more detailed and spatially localized values than merely a sum of yields for the whole plot. The measurements from such sensors need to be filtered and subject to further processing, including interpolation, to facilitate follow-up interpretation. This paper aims to identify the relative differences between interpolations from (1) (field) measured data, (2) measured data that were globally filtered, and (3) measured data that were globally and locally filtered. All the measured data were obtained at a fully operational farm and are considered to represent a natural experiment. The revealed spatial patterns and recommendations regarding global and local filtering methods are presented at the end of the paper. Time investments into filtering techniques are also taken into account.

Big data have also become a big challenge for cartographers, as the majority of big data may be localized. The use of visual analytics tools, as well as comprising interactive maps, stimulates inter-disciplinary actors to explore new ideas and decision-making methods. This paper deals with the evaluation of three map-based visual analytics tools by means of the eye-tracking method. The conceptual part of the paper begins with an analysis of the state-of-the-art and ends with the design of proof-of-concept experiments. The verification part consists of the design, composition, and realization of the conducted eye-tracking experiment, in which three map-based visual analytics tools were tested in terms of user-friendliness. A set of recommendations on GUI (graphical user interface) design and interactive functionality for map makers is formulated on the basis of the discovered errors and shortcomings in the assessed stimuli. The results of the verification were used as inputs for improving the three tested map-based visual analytics tools and might serve as a best practice for map-based visual analytics tools in general, as well as for improving the policy making cycle as elaborated by the European project PoliVisu (Policy Development based on Advanced Geospatial Data Analytics and Visualization).

Human performance and navigation activity in virtual environments can be measured and assessed with the aim to draw specific conclusions about human cognition. This paper presents an original virtual geographic environment (VGE) designed and used for this purpose. The presented research is rooted in an interdisciplinary approach combining knowledge and principles from the fields of psychology, cartography, and information technologies. The VGE was embedded with user logging functionality to provide a basis from which conclusions about human cognitive processes in a VGE could be drawn. The scope of this solution is introduced, described, and discussed under a behavioral measurement framework. An exploratory research design was adopted to demonstrate the environment’s utility in proof-of-concept user testing. Twenty participants were observed in interactive, semi-interactive and non-interactive tasks, their performance and individual differences were analyzed. The behavioral measurements were supplemented by Object-Spatial Imagery and a Verbal Questionnaire to determine the participants’ cognitive styles. In this sample, significant differences in exploration strategies between men and women were detected. Differences between experienced and non-experienced users were also found in their ability to identify spatial relations in virtual scenes. Finally, areas for future research areas and development were pinpointed.

Immersive virtual reality (iVR) devices are rapidly becoming an important part of our lives and forming a new way for people to interact with computers and each other. The impact and consequences of this innovative technology have not yet been satisfactory explored. This empirical study investigated the cognitive and social aspects of collaboration in a shared, immersive virtual reality. A unique application for implementing a collaborative immersive virtual environment (CIVE) was developed by our interdisciplinary team as a software solution for educational purposes, with two scenarios for learning about hypsography, i.e., explanations of contour line principles. Both scenarios allow switching between a usual 2D contour map and a 3D model of the corresponding terrain to increase the intelligibility and clarity of the educational content. Gamification principles were also applied to both scenarios to augment user engagement during the completion of tasks. A qualitative research approach was adopted to obtain a deep insight into the lived experience of users in a CIVE. It was thus possible to form a deep understanding of very new subject matter. Twelve pairs of participants were observed during their CIVE experience and then interviewed either in a semistructured interview or a focus group. Data from these three research techniques were analyzed using interpretative phenomenological analysis, which is research method for studying individual experience. Four superordinate themes—with detailed descriptions of experiences shared by numerous participants—emerged as results from the analysis; we called these (1) Appreciation for having a collaborator, (2) The Surprising “Fun with Maps”, (3) Communication as a challenge, and (4) Cognition in two realities. The findings of the study indicate the importance of the social dimension during education in a virtual environment and the effectiveness of dynamic and interactive 3D visualization.

Interactive 3D visualizations of geospatial data are currently available and popular through various applications such as Google EarthTM and others. Several studies have focused on user performance with 3D maps, but static 3D maps were mostly used as stimuli. The main objective of this paper was to identify differences between interactive and static 3D maps. We also explored the role of different tasks and inter-individual differences of map users. In the experimental study, we analyzed effectiveness, efficiency, and subjective preferences, when working with static and interactive 3D maps. The study included 76 participants and used a within-subjects design. Experimental testing was performed using our own testing tool 3DmoveR 2.0, which was based on a user logging method and open web technologies. We demonstrated statistically significant differences between interactive and static 3D maps in effectiveness, efficiency, and subjective preferences. Interactivity influenced the results mainly in ‘spatial understanding’ and ‘combined’ tasks. From the identified differences, we concluded that the results of the user studies with static 3D maps as stimuli could not be transferred to interactive 3D visualizations or virtual reality.

Intensive farming on land represents an increased burden on the environment due to, among other reasons, the usage of agrochemicals. Precision farming can reduce the environmental burden by employing site specific crop management practices which implement advanced geospatial technologies for respecting soil heterogeneity. The objectives of this paper are to present the frontier approaches of geospatial (Big) data processing based on satellite and sensor data which both aim at the prevention and mitigation phases of disaster risk reduction in agriculture. Three techniques are presented in order to demonstrate the possibilities of geospatial (Big) data collection in agriculture: (1) farm machinery telemetry for providing data about machinery operations on fields through the developed MapLogAgri application; (2) agrometeorological observation in the form of a wireless sensor network together with the SensLog solution for storing, analysing, and publishing sensor data; and (3) remote sensing for monitoring field spatial variability and crop status by means of freely-available high resolution satellite imagery. The benefits of re-using the techniques in disaster risk reduction processes are discussed. The conducted tests demonstrated the transferability of agricultural techniques to crisis/emergency management domains.