ABSTRACT. Cartographic knowledge is fundamental to the design of effective maps. Yet even the most skilled cartographer may fail to produce a legible and accurate map without engaging with domain experts and, crucially, with prospective users. This consideration is particularly important in the context of inclusive cartography, where maps must accommodate users with diverse perceptual and cognitive abilities.

Historically, map design was largely practice-led, prioritizing the accurate and aesthetically pleasing visual representation of spatial data. Decisions concerning symbolization and layout were typically made by mapmakers or specialized professionals according to the intended function of the map. While legibility was considered in a general sense, systematic attention to users’ perceptual and cognitive processes remained limited. It was not until the second half of the twentieth century that cartography began to draw explicitly on psychological theory and empirical research. This shift—often described as the “cognitive turn” in cartography—introduced a more user-centred approach to map design.

Within this framework, map design is understood as a complex and context-dependent process shaped by multiple interrelated factors. In visually oriented cartography, five such factors are commonly identified: the nature of the geographic phenomena, the intended recipient, technical constraints, map scale, and the purpose of the map. However, these factors do not carry equal weight in all mapping contexts. In tactile cartography and other forms of inclusive mapping, the recipient becomes a primary design driver, requiring greater attention to users’ perceptual and cognitive capabilities.

Building on the cognitive turn in cartography, this presentation examines the map design process through the lens of users’ perceptual and cognitive capabilities, drawing on principles from tactile mapping. It asks whether design principles rooted in visually dominant cartographic traditions can adequately support non-visual modes of perception, and what design decisions enable users with varying cognitive profiles to construct meaningful cognitive maps.

ABSTRACT. This contribution is focused on the design and experimental evaluation of immersive cartographic visualizations and interaction paradigms in iVR environments. While the earlier work primarily addressed technological and methodological foundations—such as alternative user perspectives, natural interaction, and logging of user behaviour—this contribution extends the research towards the visualization and interpretation of spatio-temporal social data and their application in decision-making, crisis management and planning contexts. The main objective is to investigate how different visualization strategies (e.g. “on-the-table” versus “on-the-ground” perspectives), levels of abstraction, and interaction techniques influence users’ understanding of dynamic social processes in space and time. The study integrates open urban and institutional datasets, time series, and 3D spatial models into a collaborative immersive virtual environment that supports both individual and multi-user exploration. Methodologically, the research is based on user studies involving both domain experts and members of the general public, complemented by qualitative feedback and analysis of recorded user interactions. The results indicate that carefully designed immersive cartographic visualizations can significantly enhance the comprehension of complex spatio-temporal phenomena, support participatory discussion, and increase transparency in planning and decision-making processes. At the same time, the paper identifies current limitations and open challenges related to the use of immersive virtual reality in cartography and geovisualization, and outlines directions for future research focusing on scalability, and usability.

ABSTRACT. Spatial models and modeling are relevant platform for presenting and interpretation of the reality. Srebarna wetland system is one of the most famous nature objects, protected by national and international law (NATURA 2000, UNESCO etc.). The first part of the research is related with functions and opportunities of the spatial models and modeling for the presenting of the different condition in the nature and social system. The other aspect is interpretation of the status and processes. The third level is investigation of the transformations and making the prognosis and projections. The object of the research is Srebarna wetland system. It is observed as integrated nature system between River Danube, lake Srebarna, underground waters and catchment area of the rivers with irregular regime in south part of the lake – Srebarska, Babushka and Kulnezha. Present research is focused on the parameters and transformations of the Srebarna wetland system during the last year. The key modeling elements are water body and hydrophite formation. The important part of the research is investigation and analysis of the factors and reasons for changes in water level and expansion of the hydrophite formation – natural and anthropogenic. The research gives some recommendations for optimization the management of wetland system and reduction of anthropogenic impact.

ABSTRACT. Mobile devices pose significant accessibility challenges compared to desktop environments, including small screens, dense interfaces, complex gestures and hidden navigation structures. These challenges are particularly pronounced in mobile map applications, which involve a high density of content, visual information and operating options. Elderly users are known to have age-related sensory, motor and cognitive limitations, such as a narrower field of view—often leading to overlooked user interface elements at the screen edges—and decreasing abilities in recognising relations and abstracting information. They often face multiple limitations at once, making mobile map use especially demanding.

While existing research addresses accessibility issues of elderly people in mobile applications and navigation apps, the contents, visualisation and operation of mobile maps for elderly users remain underexplored. With our ongoing research, we aim to gain a deeper understanding of how elderly people use mobile map applications and which challenges they encounter.

Adopting an exploratory qualitative approach, we conducted an initial focus group with seven participants aged between their late 50s and early 80s. Building on these insights, the topic was integrated into a master‘s-level course on Mobile Cartography. Students were asked to guide their parents or grandparents through a questionnaire and to document their own observations of how their parents or grandparents use mobile map applications. Based on the identified issues, students developed preliminary design ideas and guidelines to adapt mobile map applications to the needs of elderly users.

These early findings contribute to the development of accessibility-oriented design principles for mobile maps and highlight their potential to support elderly people in daily activities, health maintenance and social participation.

ABSTRACT. This paper presents a comprehensive and unified methodology for developing educational 3D relief maps and models. It employs an interdisciplinary approach, utilizing contemporary photogrammetric and cartographic methods to enhance teaching in geography and earth sciences. The proposed workflow begins with an analytical phase that examines existing educational relief representations, digital resources, and curriculum requirements to align scientific advancements with pedagogical needs. High-quality spatial data, including photogrammetric imagery, digital terrain models, and orthophotography data, are collected to ensure geometric accuracy and reliability. The data are processed using specialized photogrammetric software to generate digital terrain models and three-dimensional surfaces. Next, cartographic interpretation is applied by integrating essential map elements such as contour lines, hydrography, settlements, and labels, bridging traditional cartographic principles with modern 3D visualization techniques. The resulting models will be produced as physical relief maps and scale models using additive manufacturing and CNC (Computer Numerical Control) technologies, alongside interactive digital versions. During the workflow implementation, physical models will be integrated with digital technologies, including photogrammetry, 3D reconstruction, GIS analysis, and 3D printing, to create accurate, scalable, and interactive educational tools. The elaborated educational products will be tested in real user environments, with their effectiveness evaluated through structured feedback and analysis. The results are expected to contribute to improving spatial understanding and tactile perception, which have proven didactic value, and to support the sustainable integration of 3D relief models into educational practice.

ABSTRACT. Agricultural Geographical Indications (AGIs) represent a spatially embedded institutional arrangement linking localized natural endowments with agri-food production systems, yet their fine-scale spatiotemporal patterns and multi-level driving mechanisms remain insufficiently understood. Using data on 3,510 AGIs in China from 2008 to 2022, this study constructs a high-resolution spatiotemporal database covering 43,655 townships and applies the Theil index and optimal Geodetector within a multi-scale spatial framework. This framework spans national, regional, and provincial levels, enabling a systematic examination of AGI dynamics, spatial inequality, and scale-dependent driving mechanisms. The results show that: (1) AGIs exhibit a crop-dominated structure, with fruits and vegetables accounting for the largest share. New registrations follow a phased trajectory characterized by fluctuating growth, peaking in 2020 and subsequently declining. Spatially, AGIs display a pattern of widespread distribution combined with clustering in specific ecological zones, with differentiated terroir–market coupling across product categories. (2) Pronounced spatial inequality exists in AGI distribution, and its sources are scale dependent. In the Eastern and Western regions, overall disparity is mainly driven by inter-regional structural differences, whereas in the Central region it primarily arises from intra-regional differentiation among counties. (3) Driving mechanisms exhibit pronounced spatial stratified heterogeneity and scale effects. As the spatial stratification becomes more detailed across regional divisions, the explanatory power (q-value) of core factors increases markedly. Dominant drivers vary across regions: the East is primarily influenced by hydro-thermal conditions and agricultural inputs; the Central region is dominated by population, transportation, and economic factors; and the West is constrained by a combination of natural endowments (soil and topography) and development levels. These findings highlight the scale dependence and regional heterogeneity of AGI distribution mechanisms, underscoring the value of multi-scale geospatial analysis and the necessity of zone-specific governance strategies.

ABSTRACT. According to an Interpol and UN Environment Programme estimate, environmental crime is considered the fourth-largest criminal activity in the world. Environmental crime poses an increasing threat to ecosystem stability, biodiversity conservation, and sustainable land management. This study presents a methodological framework for detecting and mapping potential illegal environmental activities in Slovakia using Earth observation data. The focus is placed on two key landscape transformations: the destruction or ploughing of protected grasslands and the removal of non-forest woody vegetation, both of which play a crucial role in climate resilience and ecological connectivity. The approach integrates multi-temporal Sentinel-2 and PlanetScope satellite imagery with vegetation indices, particularly the Normalised Difference Vegetation Index and the Bare Soil Index. Areas at risk were first delineated using high-resolution masks of protected grasslands and woody vegetation. Spectral and temporal anomalies were then analysed to identify disturbances inconsistent with natural vegetation dynamics. The primary outcome of this research is a national-scale map depicting the frequency and spatial distribution of detected illegal activities between 2018 and 2021. This map reveals clear regional patterns, highlighting hotspots concentrated in agriculturally heterogeneous basins and socio-economically vulnerable regions. Another significant hotspots are prominent around the capital city and along the valleys between regional centres, where urban sprawl and agricultural or industrial expansion often pressure surrounding natural areas. Validation against inspectorate-reported cases demonstrates high detection precision, confirming the effectiveness of remote sensing for identifying suspicious land use/cover changes. By transforming these findings into cartographic products, the research delivers a practical tool for authorities and policymakers, enabling targeted interventions and more efficient protection of vulnerable ecosystems.

This work was supported by the Slovak Scientific Grant Agency VEGA under Grant 2/0043/23 “Detection of landscape diversity and its changes in Slovakia based on remote sensing data in the context of the European Green Deal”.

ABSTRACT. Forest transition and its drivers are among the primary concerns of land use policy in European countries. This paper investigates the spatial-temporal changes in forest cover in Poland caused by the location of motorway in a rural-forest region. The analysis was conducted in two stages. The first involved a macro-analysis of land cover data for the entire country from 1990 to 2018, provided by the European Environment Agency in the form of Corine Land Cover. The study, carried out using GIS methods, highlights the main changes in forest and infrastructure areas, with a historical overview of forest changes in Poland since 1945. The second stage focused on the A4 motorway in the Małopolska region. The detailed research of forest cover changes in several buffer zones from motorway axis was conducted over a ten-year period from 2014 to 2024, based on the Database of Topographic Objects. The results indicate that the most significant differences in the spatial distribution and extent of forest cover change around the motorway are found in the initial buffer zones. The particular arrangement of agricultural parcels in southern Poland, coupled with the agricultural policies in place, is conducive to a swift increase in forest cover. Furthermore, the findings suggest that ongoing changes in forest cover act as a catalyst for subsequent transformation.

ABSTRACT. The study addresses the problem of the readability of large-scale maps used in crisis situations, in which the user must quickly locate and identify operationally relevant information, interpret spatial relationships, and make decisions under stress and severe time constraints. The aim of the research is to comprehensively assess the impact of factors such as graphic variables, visualization techniques, contrast, and visual clutter on map perception. The study also examines the efficiency of visual scanning of map content by the human eye as well as decision-making time. Eye-tracking methods were employed in the experiment. The research material consisted of large-scale maps in two different scales, on which the location of a crisis event (fire) was marked. For each scale, a series of maps was examined, with successive modifications introduced step by step. This approach enabled the isolation of the effect of a single variable on users’ visual behavior and allowed comparison of the same cartographic solutions across different scales. During the experiment, participants performed tasks involving the identification of a specific object of operational significance for the ongoing response action, indicated using a mouse cursor. A range of metrics was analyzed, including time to first fixation and fixation duration, attention dwell time within predefined areas of interest, the number of fixations and revisits to areas containing key cartographic content prior to decision-making, as well as response time and accuracy. The results will be presented, among others, in the form of heat maps, fixation maps, and charts illustrating differences in metrics across specified areas of interest.

ABSTRACT. This study develops a spatial prediction model for the invasive brown macroalgae Rugulopteryx okamurae along the Algerian Mediterranean coast using environmental variables and machine learning algorithms. We integrated five key predictors: bathymetry, sea surface temperature (SST), salinity, turbidity, and chlorophyll-a concentration to model habitat suitability for this invasive species.

Field data comprising 187 georeferenced presence/absence points were collected during 2022-2023 surveys. Environmental variables were extracted from satellite data (Sentinel-2 and Sentinel-3) and marine databases. Three machine learning algorithms—Random Forest, Maximum Entropy (MaxEnt), and Support Vector Machines—were trained and compared for predictive performance.

The Random Forest model demonstrated superior predictive accuracy with an Area Under Curve (AUC) of 0.91 and True Skill Statistic (TSS) of 0.83. Variable importance analysis identified sea surface temperature (18-24°C range) and bathymetry (10-30m depth) as the most influential predictors, contributing 34% and 29% to model predictions respectively. Turbidity and chlorophyll-a concentration showed moderate influence, while salinity had the lowest predictive power.

Spatial predictions revealed three distinct suitability zones: (1) High-risk areas concentrated in semi-enclosed bays comprising approximately 85 km², (2) Moderate-risk zones along exposed coastlines covering 210 km², and (3) Low-risk areas in river mouths and deep waters. The model identified specific coastal sectors near Oran, Algiers, and Bejaia as primary invasion hotspots with suitability probabilities exceeding 0.8.

This research provides the first comprehensive habitat suitability map for R. okamurae along the Algerian coast, offering valuable tools for coastal managers to prioritize monitoring efforts and implement targeted control measures. The methodology demonstrates the effectiveness of integrating environmental variables with machine learning for predicting invasive species distributions in marine environments.

ABSTRACT. This paper examines the potential of cartography and Geographic Information Systems (GIS) for the documentation and analysis of small water sources, with a particular focus on public fountains as both natural and cultural resources. In the Bulgarian context, these features have a deeply rooted social, historical and symbolic significance that goes beyond their purely utilitarian function as water supply points. They are an integral part of local identity, closely associated with donation practices, collective memory, and everyday social interactions and in mountainous and semi-mountainous areas they also play a key role in providing access to drinking water. The study focuses on the territory of the Municipality of Satovcha, Bulgaria, an area characterized by an exceptionally high concentration of spring-fed public fountains and internationally recognized for holding a Guinness World Record for the highest number of such fountains per capita. This makes the municipality a representative example of sustainable interaction between natural water resources and traditional social practices. The main objective is to create a web thematic map that presents the spatial distribution of the fountains and enables analysis of their accessibility, technical condition, and relationship to the road network and the natural environment. The methodology includes preliminary research, collection and structuring of spatial and tabular data, their integration into a GIS environment, the development of an attribute structure, and the design of an appropriate symbol system and cartographic layout. The result is a practically oriented web-based cartographic product that can support municipal authorities, experts, and the general public in visiting the area, planning fountain maintenance, and ensuring the sustainable management of small water resources.

ABSTRACT. Fluvial flooding arises when the volume of water in a river surpasses the capacity of its channel, leading to inundation of surrounding floodplains. This study focused on fast prediction of fluvial flood extent and flow depths using machine learning (ML), in particular, the Random Forest (RF) model. The studied domain was represented by an 8.79 km section of the Kysuca River, northern Slovakia. The RF models were trained on hydraulically derived flood maps for five scenarios (Q10, Q20, Q50, Q100, and Q1000) using the MIKE+ model. The innovative training procedure of RF models included a river segmentation to ten segments, of which 5 variants of segment splits were used for training and testing within each flood scenario. Moreover, we used seven predictors with 1 m resolution to train the ML models. Multicollinearity among predictors was assessed using the Pearson correlation and Variance Inflation Factor. Several metrics were used to evaluate the RF classification and regression models. The results confirmed that RF model is capable of delivering computationally efficient and accurate flood extent and flow depth maps across all data splits and flood scenarios. The F1-score for classification of flood extent ranged from 0.86 to 0.97 across the studied flood scenarios and segment splits. The flow depth performance metrics resulted in the following values for the studied flood scenarios and variants of splits: root mean square error (5-8%), mean absolute error (3-5%), and coefficient of determination (81-94%). In all of the segment splits, except one, RF model slightly overestimated (<4%) the hydraulically modeled flow depths. The maximum training time was 1.88 and 1.46 minutes for classification and regression, respectively, which enables potential deployment of RF models for real-time flood mapping applications. Acknowledgment: Funded by the EU NextGenerationEU through the Recovery and Resilience Plan for Slovakia under the project No. 09I03-03-V03-00085.

ABSTRACT. Natural disasters, as devastating events with significant impact on the environment and society, are one of the challenges that humanity has consistently faced and remain a current topic for scientific research. Special focus in modern research is placed on spatio-temporal analysis in GIS environment, an essential tool for comprehensive assessments of natural hazards. Every year, a large number of natural disasters are recorded in Serbia, and their study increasingly includes comprehensive spatial analysis using GIS. One of the most endangered regions is Šumadija, located in central Serbia. Therefore, this study aims to present the GIS that was created for spatial analysis of natural disasters in Šumadija, as well as for assessing the different levels of vulnerability of this territory to specific types of natural disasters. In the first phase, thematic and topographic maps were digitized, settlements were defined and connected to MS EXCEL and MS ACCESS databases. The created GIS database contains the locations of measuring stations with relevant datasets, and information on registered natural disasters, including descriptions, demographic data (victims and injured), and economic losses. This GIS database enabled access to geospatial data by type of natural disaster and by municipalities in Šumadija. In the next phase, shapefiles of seismic hazard were entered, and flood zones and landslide stability zones were defined, which enabled additional vulnerability analyses and the creation of appropriate thematic maps. Through geospatial analysis of the collected data, areas with different degrees of natural hazard in Šumadija were identified. The integration of physical-geographical and demographic-economic parameters showed that the greatest risk of natural disasters is in the eastern and southeastern parts of Šumadija. By identifying municipalities with high natural hazard risk, this study provides a valuable basis for decision-makers in improving the planning of preventive measures and establishing a sustainable natural disasters management system, with the aim of mitigating their consequences.

ABSTRACT. The emergencies at nuclear power plants pose a high risk to public order, life, health, and safety if radiation is released into surrounding communities and areas. Owing to this, every measure taken to make responses to this kind of emergency more effective is of great importance. Because of that fact, the proposed article deals with the usage of spatial data of various kinds to make the management of emergencies at nuclear power plants more effective. In its first part, the article deals with the collection and evaluation of measurements of the rate of ionizing radiation equivalent dose, which the Fire Rescue Service of the Czech Republic daily carries out. These measurements further strengthen the existing radiation monitoring network on the area of the Czech Republic in the consequence with endangerment of the nuclear power plants by the conflict on Ukraine. Next, the article provides an overview of the use of spatial data for emergency management support during a simulated accident at Nuclear Powerplant Dukovany, within the framework of the exercise Zóna 2025. Finally, the article attempts to formulate, based on the previously mentioned cases, guidelines for spatial data support for emergency management at nuclear power plants and for emergency management generally.

ABSTRACT. The averaged shear-wave velocity in the upper 30 m of the subsurface (Vs30) is widely used as a standardized proxy for near-surface stiffness and is fundamental for estimating ground-motion amplification in seismic hazard assessment, informing building code provisions, and ensuring consistent seismic site classification. Although Bulgaria does not yet have an official national Vs30 map, ongoing local mapping efforts provide an initial framework that can be further enhanced with greater methodological rigor and transparency to better support seismic hazard analyses. This study presents the first attempt to develop a proxy Vs30 map for the southeastern part of the Sofia Basin. The mapping integrates topographic-slope metrics derived from the TanDEM-X 1.0 arcsecond (~30 m) DEM, surficial geological information, empirical data from soil and engineering datasets, and in situ microtremor measurements obtained using the HVSR approach near 70 borehole locations. The resulting Vs30 model is generated through a hybrid, hierarchical approach that combines available data to achieve accuracy and robustness across different relief terrains in the studied area. The compiled Vs30 map is a gridded dataset with a spatial resolution of 100 × 100 m. Comparative evaluation against previously published Vs30 maps for the Sofia Basin indicates that the new model exhibits superior graphical fidelity and improved spatial precision. Furthermore, the map was independently validated at a construction site in central Sofia, where dynamic field testing of soil layers was performed using direct microseismic logging. Ongoing work includes incorporating additional microtremor measurements from the western Sofia Basin, which will support future refinements of the model and facilitate more reliable assessments of site amplification during earthquakes.

ABSTRACT. In 2025, significant shifts and advances were observed in the role of cartography and geoinformatics within early warning (EW), disaster risk management (DRM), and disaster risk reduction (DRR). These developments were reflected at major international events, including the RIMMA Conference in Bern, Switzerland (January 28–30) (Kremers, 2025), with participation from members of the ICA Commission on Cartography for Early Warning and Crisis Management; the International Cartographic Conference (ICC) in Vancouver, Canada (August 17); and the UNESCO World Natural Heritage and Sustainable Development Cooperation Conference in Jiuzhaigou, China (October 13). Scholarly interest in this field has remained strong, with continued engagement from the International Journal of Digital Earth and increasing attention from other journals, such as the International Journal of Cartography. At the same time, notable progress has occurred in the broader domain of informatization (Annoni, 2024), including the formulation of a new Digital Earth (DE) concept. This concept, titled Digital Earth Strategic Architecture: A Framework and Meta-Framework for Planetary Intelligence and Sustainability Governance, was introduced by newly elected ISDE President Richard Simpson on April 21, 2025, in Chongqing, China. Responding to planetary-scale risks and systemic change, the framework emphasizes shared understanding, ethical coordination, and inclusive foresight through adaptive, ethically grounded, and semantically interoperable systems. The new DE concept is structured into three tiers: Foundational Systems, Enabling Infrastructures, and Human-Centric Applications. Among its twelve conceptual frameworks are Digital Earth as a Dynamic Complex Adaptive System, a Cyber-Physical Continuum, a Supersense and Perception system, and a Meta-Design Space for Planetary Futures. The authors view this framework as an opportunity to integrate previously fragmented efforts and to demonstrate its potential for EW, DRM, and DRR. It enables a clearer link between progressive cartography and the broader objectives of Digital Earth, with particular emphasis on user-centered visualization, uncertainty communication, data ecosystems, and mobile-first delivery. The authors also anticipate constructive feedback and proposals from participants to support further qualitative progress in emergency management.