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Cartography and Geovisual Analytics
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Cartography and Geovisual Analytics

A special issue of ISPRS International Journal of Geo-Information (ISSN 2220-9964).

Deadline for manuscript submissions: 31 July 2026 | Viewed by 27304

Editors

Dr. Andriani Skopeliti

E-Mail Website
Guest Editor
School of Rural, Surveying and Geoinformatics Engineering, National Technical University of Athens, 15780 Zographos, Greece
Interests: cartography; web mapping; geovisualization; volunteered geographic information; ethics in cartography; cartographic generalization; citizen science
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Ioannis Giannopoulos

E-Mail Website
Guest Editor
Department of Geodesy and Geoinformation, Technische Universitat Wien, Vienna, Austria
Interests: GIScience; GeoAI; human-computer interaction; eye tracking; location-based services; mobility; augmented reality
Special Issues, Collections and Topics in MDPI journals
Dr. Vassilios Krassanakis

E-Mail Website
Guest Editor
Department of Surveying and Geoinformatics Engineering, School of Engineering, University of West Attica, 12243 Egaleo, Greece
Interests: cartography; eye tracking; geovisualization; GIS; visual perception
Special Issues, Collections and Topics in MDPI journals
Dr. Guillaume Touya

E-Mail Website
Guest Editor
ENSG-IGN, Université Gustave Eiffel, IGN, 77455 Marne-la-Vallee, France
Interests: map generalisation; multi-scale visualisation; spatial cognition, AI; data matching; road network; OpenStreetMap; crowdsourced data quality; crowdsourced data evolution

Special Issue Information

Dear Colleagues,

In the past few years, cartography and visual analytics have supported the challenge of understanding and communicating spatial phenomena in the era of big data. Since spatial information has become increasingly vital to policymaking, governance, disaster management, urban planning, and environmental monitoring, effective and novel methods and tools for cartography and visual analytics have become essential.

Cartography is the mother science that states the theory and practice of spatial data representation. Visual analytics builds on cartography by combining interactive visuals, data analysis, and focus on users' needs. By combining analytical reasoning, cognitive science, and multiple data visualizations, we can explore and understand large and varied geospatial datasets. This teamwork between cartography and visual analytics enhances our ability to handle uncertainty, identify trends, and make informed decisions.

This Special Issue aims at collecting new theoretical foundations and design principles, novel tools and technologies, and cases of successful applications of cartography and visual analytics. We welcome submissions that cover, but are not limited to, the following topics:

  • Cognitive aspects of map-based visual analytics;
  • Ethics and bias in cartographic visualizations;
  • Evaluation methods for geovisual analytic tools;
  • Interactive and dynamic map interfaces;
  • Visual analytics for spatial-temporal data;
  • Machine learning and AI in visual cartography;
  • Immersive technologies (AR/VR) in geovisualization;
  • Web-based visual analytic platforms for spatial data;
  • Big geospatial data and scalable visualization techniques;
  • Visual analytics in urban planning and smart cities;
  • Public health and epidemiological mapping;
  • Geovisual analytics for disaster management;
  • User-centered approaches in geovisualization;
  • Uncertainty visualization in geospatial analysis;
  • Collaborative and participatory mapping analytics;
  • Multiscale and multiresolution cartographic visualization;
  • Eye tracking and visual analytics.

Dr. Andriani Skopeliti
Prof. Dr. Ioannis Giannopoulos
Dr. Vassilios Krassanakis
Dr. Guillaume Touya
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. ISPRS International Journal of Geo-Information is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • cartography
  • visual analytics
  • interactive geographic visualization
  • analytical reasoning
  • visual interfaces
  • user centered design
  • AR/VR
  • AI
  • eye tracking

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Published Papers (15 papers)

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Research

41 pages, 8165 KB  
Article
Evaluating Geovisualizations Based on Open Data: An Integrative Framework for Engagement, Openness, and Accessibility
by Andrea Miletić and Ana Kuveždić Divjak
ISPRS Int. J. Geo-Inf. 2026, 15(6), 259; https://doi.org/10.3390/ijgi15060259 - 10 Jun 2026
Viewed by 404
Abstract
Geovisualizations based on open data are increasingly used as public-facing interfaces for communicating geospatial information, yet their evaluation often remains limited to isolated design, usability, or technical aspects. This study addresses that gap by developing and applying an integrative evaluation framework that combines [...] Read more.
Geovisualizations based on open data are increasingly used as public-facing interfaces for communicating geospatial information, yet their evaluation often remains limited to isolated design, usability, or technical aspects. This study addresses that gap by developing and applying an integrative evaluation framework that combines four analytical dimensions: cartographic representation, interaction and engagement affordances, openness, and accessibility, while treating contextual characteristics as conditioning factors. The framework is operationalized through a mixed-methods content analysis of 26 publicly available geovisualizations based on open data. The results show that most cases are produced by public-sector actors, focus on environmental and transport themes, and rely on conventional cartographic techniques combined with medium levels of interactivity that support structured exploration rather than deeper analytical reasoning. Although many geovisualizations cite data sources and provide some form of data access, licensing remains inconsistent, particularly for the visualization artefacts themselves, limiting reuse potential. Accessibility is implemented even less consistently across geovisualizations, with recurring shortcomings in color contrast, keyboard navigation, screen-reader compatibility, and multilingual support. Overall, the findings suggest that the broader societal potential of geovisualizations based on open data may not be determined by individual features, but by balanced cross-dimensional configurations. Strengthening the integration of openness and accessibility alongside interaction and design may enhance the potential of geovisualizations to support reuse, inclusiveness, and public engagement. Full article
(This article belongs to the Special Issue Cartography and Geovisual Analytics)
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29 pages, 9601 KB  
Article
A User-Based Study on the Graphic Parameters of Pictorial Symbols for Tourist Maps
by Eirini Nektaria Konstantinou, Andriani Skopeliti and Byron Nakos
ISPRS Int. J. Geo-Inf. 2026, 15(6), 250; https://doi.org/10.3390/ijgi15060250 - 3 Jun 2026
Viewed by 307
Abstract
Modern web and tourist maps use pictorial symbols to help users quickly and easily identify Points of Interest (POIs). Pictorial symbols are sometimes misinterpreted due to poor design choices. As a result, it is important to evaluate pictorial symbols with map users. This [...] Read more.
Modern web and tourist maps use pictorial symbols to help users quickly and easily identify Points of Interest (POIs). Pictorial symbols are sometimes misinterpreted due to poor design choices. As a result, it is important to evaluate pictorial symbols with map users. This paper uses an online questionnaire to examine how different graphic parameters—such as frame outline, frame background, frame shape, color hue, and pictogram category (semantic, visual, or arbitrary)—are perceived by map users. The evaluation of pictograms includes three aspects: understanding, to capture the map reader’s opinion; preference, to investigate the map maker’s choice; and appropriateness, to document the evaluation of an existing map. Seven popular Points of Interest (POIs) were selected for the evaluation of pictorial symbols: Hotel, Restaurant, Parking, Museum, Airport, Hospital, and Church. Based on the questionnaire results and the statistical analysis of 520 responses, several conclusions were drawn. Users prefer symbols with a frame outline and a frame background. They also prefer symbols with a white background, which increases contrast and improves legibility. In contrast, users do not have a strong preference for a specific frame shape. In general, users can recognize symbol groups based on frame shape, but the effect is stronger when the color hue appears in the frame background or outline. The statistical analysis demonstrates that perceived appropriateness constitutes an objective measure related to comprehension. Furthermore, appropriateness is independent of the pictogram classification as semantic, visual, or arbitrary. Instead, it is determined by the graphic ability of the pictogram to represent a specific POI. This conclusion reaffirms the importance of designing successful semantic and visual pictograms or adopting those already familiar to map users, as familiarity has also been identified as an important factor by this research. Overall, this paper, based on user evaluations, provides practical insights to improve pictorial symbols on a tourist map. Full article
(This article belongs to the Special Issue Cartography and Geovisual Analytics)
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19 pages, 6663 KB  
Article
Using a Visual Positioning System for a Geolocated Visualization of an Archaeological Site in Augmented Reality
by František Mužík and Lukáš Běloch
ISPRS Int. J. Geo-Inf. 2026, 15(5), 219; https://doi.org/10.3390/ijgi15050219 - 20 May 2026
Viewed by 619
Abstract
In recent years, augmented reality has become a popular method of spatial data visualization, both via the most popular and basic plane-based method and more advanced automatic positioning of visualizations based on predefined real-world locations. The aim of this study is to provide [...] Read more.
In recent years, augmented reality has become a popular method of spatial data visualization, both via the most popular and basic plane-based method and more advanced automatic positioning of visualizations based on predefined real-world locations. The aim of this study is to provide new insights into geolocated 3D visualizations in AR using a visual positioning system (VPS). VPS technology enables the creation of visualizations that can be displayed with high accuracy directly on a specific area of interest. This approach is especially well-suited to cultural heritage preservation, as it can be used to visualize destroyed buildings or archaeological sites. The result of the study is a mobile application created using the Unity game engine, which allows users to access AR visualizations as well as additional context in the form of pop-up texts or photographs. Thanks to the display of AR visualization directly at the chosen location, the user can better understand the context of the whole scene. This is because it is a more immersive experience than simply viewing a 3D model on a computer or mobile phone screen. Full article
(This article belongs to the Special Issue Cartography and Geovisual Analytics)
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25 pages, 17422 KB  
Article
Demystifying Geographic “Laws” for Soil Mapping via Interactive Geovisualization
by Guiming Zhang
ISPRS Int. J. Geo-Inf. 2026, 15(5), 212; https://doi.org/10.3390/ijgi15050212 - 12 May 2026
Viewed by 540
Abstract
“Laws” of geography such as Tobler’s First Law (spatial autocorrelation) and Zhu’s Third Law (environmental similarity) offer fundamental principles for spatial prediction and mapping, yet their implications for digital soil mapping (DSM) are often opaque because the underlying principles and mechanisms of DSM [...] Read more.
“Laws” of geography such as Tobler’s First Law (spatial autocorrelation) and Zhu’s Third Law (environmental similarity) offer fundamental principles for spatial prediction and mapping, yet their implications for digital soil mapping (DSM) are often opaque because the underlying principles and mechanisms of DSM models are rarely inspectable in typical DSM workflows. This study presents an interactive geovisualization portal that demystifies Tobler’s Law, Zhu’s Law, and a combined formulation in spatial prediction processes, using soil organic matter (SOM) concentration prediction in Xuancheng, China, as a case study. The portal integrates multiple DSM frameworks that operationalize two geographic laws—inverse distance weighting (IDW), individual predictive soil mapping (iPSM), an iPSM-IDW hybrid, ordinary kriging (OK), and regression kriging (RK)—and couples them with user-configurable parameters such as neighborhood size, distance-decay factor, and variogram model. The portal provides coordinated, interactive views that link SOM predictions to dynamic map and diagnostic statistical charts for explaining location-level predictions, visualizing the manifestation of geographic laws in constructing local predictions, examining weight allocation patterns, and assessing overall prediction accuracy. Additionally, a built-in sensitivity analysis enables users to investigate and understand the effects of varying the geographic law, modeling framework, and modeling parameters on prediction results. This geovisualization portal advances interpretable DSM by rendering its underlying geographic principles, model mechanics, and parameter influences visually inspectable. Full article
(This article belongs to the Special Issue Cartography and Geovisual Analytics)
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26 pages, 5044 KB  
Article
Making Participation Tangible: A Methodological Reflection on the Potentials and Limitations of Immersive Virtual Reality, Electrodermal Activity Measurement, and Qualitative Inquiry in the Analysis of Urban Fear Spaces
by Katrin Reichert, Anna-Lena Heppenheimer, Julian Keil, Frank Dickmann and Dennis Edler
ISPRS Int. J. Geo-Inf. 2026, 15(5), 191; https://doi.org/10.3390/ijgi15050191 - 1 May 2026
Cited by 1 | Viewed by 770
Abstract
The subjective perception of safety in public space is a crucial indicator of urban participation, shaping how people experience and navigate their surroundings. Urban fear spaces highlight how physical, social, and emotional factors unequally structure access to and use of public environments, linking [...] Read more.
The subjective perception of safety in public space is a crucial indicator of urban participation, shaping how people experience and navigate their surroundings. Urban fear spaces highlight how physical, social, and emotional factors unequally structure access to and use of public environments, linking spatial perception to social justice. This paper addresses the question: What opportunities and limitations does a mixed-methods approach—combining immersive Virtual Reality (VR), electrodermal activity (EDA) measurement, and semi-structured interviews—offer for examining subjective perceptions of urban fear? It offers a methodological reflection on an exploratory study of potential fear spaces on the campus of Ruhr University Bochum, hypothesizing that mixed-methods integration reveals non-conscious arousal patterns inaccessible via verbal data alone. We discuss methodological potentials and limitations in integrating physiological data within qualitative frameworks. The study design comprised VR simulation, physiological signal acquisition, and qualitative interpretation and triangulation. Findings show that combining immersive VR with EDA detects non-conscious physiological arousal patterns that would remain inaccessible through verbal data alone, while simultaneously revealing substantial interpretative challenges that necessitate qualitative contextualization. Integrating interviews proved vital for linking physiological patterns to subjective meaning. The reflection concludes with implications for applying such multimodal approaches in participatory urban planning and spatial research. Full article
(This article belongs to the Special Issue Cartography and Geovisual Analytics)
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25 pages, 3994 KB  
Article
From SYNOP to Station Model Symbols on Web Maps: Leveraging Web Technologies to Implement Standardized WMO Symbology for Synoptic Surface Weather Charts
by Dániel Balla and Mátyás Gede
ISPRS Int. J. Geo-Inf. 2026, 15(4), 150; https://doi.org/10.3390/ijgi15040150 - 1 Apr 2026
Viewed by 1331
Abstract
Modern web mapping technologies implement web standards that make the visualization of geoscience data on the web possible using various methods, offering a high degree of customizability for creating web maps. In meteorology, synoptic surface weather charts serve as crucial products to communicate [...] Read more.
Modern web mapping technologies implement web standards that make the visualization of geoscience data on the web possible using various methods, offering a high degree of customizability for creating web maps. In meteorology, synoptic surface weather charts serve as crucial products to communicate observed surface weather at a point in time. To convey such information, these maps implement complex symbology, such as a multi-element surface station model symbol to indicate station data, isobars, and special line symbology to visualize weather fronts. Synoptic messages (SYNOP standard numerical code by WMO) are periodic meteorological reports of weather observations, exchanged by national meteorological services around the globe. This study focuses on visualizing surface weather data decoded from SYNOP reports. The paper introduces an open-source JavaScript module, which handles data decoding and dynamic symbol generation, using a WMO-compliant method for creating station model vector symbols for observational GeoJSON data on the client-side, in an interactive web mapping environment. Its output is compatible with popular, open-source web mapping libraries. It runs Python in the browser with Pyodide and makes use of the Web Workers API for parallelization, speeding up the decoding and visualization process without blocking the user interface thread. The developed module intends to help with easy representation of surface weather observations on web maps used in meteorology, which can also be implemented in a dynamically updated server–client architecture. The code is presented with a ready-to-use wrapper for Leaflet. Full article
(This article belongs to the Special Issue Cartography and Geovisual Analytics)
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15 pages, 2232 KB  
Article
Search Efficiency and Visual Appeal of Pictorial-Based and Typography-Based Map
by Dorotea Kovačević and Klementina Možina
ISPRS Int. J. Geo-Inf. 2026, 15(3), 119; https://doi.org/10.3390/ijgi15030119 - 12 Mar 2026
Cited by 1 | Viewed by 856
Abstract
Visual information should be presented clearly and effectively so that it is quickly and easily understood. The same principle applies to different types of maps and plans. This study explores the relationship between a map’s design and how users interact with it when [...] Read more.
Visual information should be presented clearly and effectively so that it is quickly and easily understood. The same principle applies to different types of maps and plans. This study explores the relationship between a map’s design and how users interact with it when searching for specific targets. Focusing on a digital tourist city map, we employed an eye-tracking technology to investigate how different cartographic designs (pictorial-based versus typography-based) influence visual search. As the need for visually appealing designs becomes an important part of the user experience, we further explored the observers’ perceptions of the maps’ visual appeal. The results show that the typography-based maps enabled a more effective visual search than the pictorial, as measured by search time, fixation count, and the number of fixations before locating the target. A greater amount of visual attention was directed towards the typography-based maps, as measured by completion time and several eye-tracking metrics during the observers’ evaluation of the maps’ visual appeal. Based on the results, this study highlights the practical implications of effective map design in enhancing users’ navigation and their visual engagement with cartographic data. Full article
(This article belongs to the Special Issue Cartography and Geovisual Analytics)
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27 pages, 1125 KB  
Article
Spatial Autocorrelation Latent in Geographic Theory: A Call to Action
by Daniel A. Griffith
ISPRS Int. J. Geo-Inf. 2026, 15(2), 73; https://doi.org/10.3390/ijgi15020073 - 10 Feb 2026
Viewed by 1312
Abstract
This paper exposes the latent but potent role of seemingly hidden spatial autocorrelation (SA) in all geographic theories, highlighting that it is everywhere, matters, and is a fundamental property of geotagged phenomena. This narrative examines and extends the literature about the inescapable nature [...] Read more.
This paper exposes the latent but potent role of seemingly hidden spatial autocorrelation (SA) in all geographic theories, highlighting that it is everywhere, matters, and is a fundamental property of geotagged phenomena. This narrative examines and extends the literature about the inescapable nature of the SA paradigm and the near-universal mixing of positive and negative SA. This study summary transcends the widespread but often implicit treatment of SA within geographic theories that their assumptions help achieve when they embed spatial processes, shape geospatial expectations, and define independent areal units so that these theory-delineating constraints largely absorb SA, reducing residual spatial dependence/correlation and improving conjectural validity, masking its presence for decades if not centuries. This paper explores selected prominent human geography theories (spatial optimization, agricultural location, gravity-model-based spatial interaction, central place systems), cultural and humanistic geography, geohumanities abstractions, physical geography theories (plate tectonics, climatology, uniformitarianism, soil formation), cartographic theories (geometric projections, semiotic/communication, cognitive/perceptual, geographic information systems anchored spatial analysis), and basic geospatial data gathering methodologies (qualitative and quantitative spatial sampling). It demonstrates that across the discipline of geography, exposing masquerading SA deepens theoretical coherence and strengthens methodological integrity, encouraging integrated spatial reasoning that bridges interpretive and analytical traditions. This article concludes by providing exemplifications of bringing scholastically unrealized SA in geographic theories out of obscurity, together with certain salient benefits from doing so, affirming the magnitude of fulfilling its major objective: SA is poised for discovery in all geospatial theories, from those for human and humanistic geography, through physical geography, to those for cartography as well as methodologies concerning all georeferenced data collection missions. Full article
(This article belongs to the Special Issue Cartography and Geovisual Analytics)
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23 pages, 5575 KB  
Article
Spatial and Temporal Analysis of Climatic Zones in Kazakhstan Using Google Earth Engine
by Kalamkas Yessimkhanova and Mátyás Gede
ISPRS Int. J. Geo-Inf. 2026, 15(2), 57; https://doi.org/10.3390/ijgi15020057 - 26 Jan 2026
Viewed by 1381
Abstract
Kazakhstan, located in Central Asia, is experiencing faster warming than the global trend, making it an important region regarding the study of how climate change is affecting climatic zones. This research aims to identify projected shifts in Köppen–Geiger climate zones under high-emission Shared [...] Read more.
Kazakhstan, located in Central Asia, is experiencing faster warming than the global trend, making it an important region regarding the study of how climate change is affecting climatic zones. This research aims to identify projected shifts in Köppen–Geiger climate zones under high-emission Shared Socioeconomic Pathway (SSP) 5-8.5 climate scenarios. The Köppen–Geiger climate classification system is a practical tool that effectively captures climate types based on just two variables: temperature and precipitation. Monthly temperature and precipitation data from Climatic Research Unit (CRU,) ERA5-Land, and Coupled Model Intercomparison Project Phase 6 (CMIP6) ensembles from 1951 to 2100 were used to generate climatic zone maps. CMIP6 models were evaluated against meteorological station data and ERA5-Land, with bias metrics used to identify the best-performing models for temperature and precipitation in Kazakhstan. Based on these results, two inter-model datasets were developed and used to generate Köppen–Geiger climate maps for high-emission scenarios for the 2061–2100 time period. This research resulted in two key outcomes. First, to facilitate this analysis, a Google Earth Engine (GEE) application was developed as an open accessible tool for dynamic visualization of Köppen–Geiger climate maps. Second, projected maps based on CMIP6 SSP5-8.5 scenario projections indicate that southern Kazakhstan may shift to BSh (Hot Semi-Arid) and Csa (Mediterranean) climates, and the southwest region of the country is projected to shift to a BWh (Hot Desert) climate. These projected Köppen–Geiger climate maps contributed to climate adaptation efforts by identifying regions at risk of desertification and aridification. This study provides a comprehensive analysis of climate zone transformations in Kazakhstan and offers a practical scalable geovisualization tool for monitoring climate change impacts. This allows users easy access to climate-related information and insights into data processing procedures. Full article
(This article belongs to the Special Issue Cartography and Geovisual Analytics)
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25 pages, 8743 KB  
Article
Irregular Area Cartograms for Local-Level Presentation of Selected SDGs Indicators Based on Earth Observation Data
by Anna Markowska and Dariusz Dukaczewski
ISPRS Int. J. Geo-Inf. 2025, 14(12), 500; https://doi.org/10.3390/ijgi14120500 - 18 Dec 2025
Viewed by 1045
Abstract
The objective of this study is to explore the applicability of irregular area cartograms for the visualization of sustainable development indicator components, utilizing earth observation (EO) data. The analysis focuses on selected Sustainable Development Goals (SDG 11 ‘Make cities and human settlements inclusive, [...] Read more.
The objective of this study is to explore the applicability of irregular area cartograms for the visualization of sustainable development indicator components, utilizing earth observation (EO) data. The analysis focuses on selected Sustainable Development Goals (SDG 11 ‘Make cities and human settlements inclusive, safe, resilient and sustainable’ and SDG 13 ‘Take urgent action to combat climate change and its impacts’) and specific targets and indicators related to green urban areas and air quality (targets: 13.2, 11.6, and 11.7; indicators: 11.6.2., 11.7.1., 13.2.2.). A comprehensive review of the relevant literature indicates that irregular area cartograms are employed only sporadically in the context of SDG monitoring, particularly at lower levels of territorial division (i.e., communes and counties). To address this gap, a series of thematic maps, including choropleth maps and irregular area cartograms, was developed. These visualizations are based on EO-derived datasets and supplemented with statistical information obtained from the Local Data Bank of the Statistics Poland. The analysis demonstrates that irregular area cartograms provide an effective means of visualizing spatial disparities in variables such as urban green space availability and air pollution at the commune and county levels. These visualizations enhance the interpretability of complex indicator structures and support more nuanced assessments of progress toward selected Sustainable Development Goals, especially in spatially detailed analytical frameworks. Preliminary usability testing among potential users revealed that irregular area cartograms are perceived as an interesting visualization technique that enhances data interpretation. Full article
(This article belongs to the Special Issue Cartography and Geovisual Analytics)
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30 pages, 8433 KB  
Article
Creating Choropleth Maps by Artificial Intelligence—Case Study on ChatGPT-4
by Parinda Pannoon and Rostislav Netek
ISPRS Int. J. Geo-Inf. 2025, 14(12), 486; https://doi.org/10.3390/ijgi14120486 - 9 Dec 2025
Viewed by 2145
Abstract
This study explores the potential of ChatGPT-4, an AI-powered large language model, to generate thematic maps and compare its outputs to the traditional method in which maps are produced manually by humans using GIS software. Prompt engineering is a crucial methodology of large [...] Read more.
This study explores the potential of ChatGPT-4, an AI-powered large language model, to generate thematic maps and compare its outputs to the traditional method in which maps are produced manually by humans using GIS software. Prompt engineering is a crucial methodology of large language models that can enhance output quality. The main objective of this study is to assess the capability of AI-generated maps and to compare the quality with a traditional method. The study evaluates two prompt patterns: basic (zero-shot prompts) and advanced (Cognitive Verifier and Question Refinement). The performance of AI-generated maps is assessed based on attempts, errors, incorrect results, and map completeness. The final stage involved evaluating AI-generated maps against cartographic rules to assess their suitability. ChatGPT-4 performs well in generating suitable choropleth maps but faced challenges in understanding the prompts and potential errors in the generated code. Advanced prompts reduced errors and improved the quality of outputs, particularly for complex map elements. This paper enhances the understanding of AI’s role in cartography and further research in automated cartography. The study assesses cartographic aspects, offering insights into the strengths and limitations of AI in cartography, illustrating how large language models can process geospatial data and adhere to cartographic principles. The study also paves the way for future innovations in automated geovisualization. Full article
(This article belongs to the Special Issue Cartography and Geovisual Analytics)
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28 pages, 4616 KB  
Article
Analysis of Semi-Global Factors Influencing the Prediction of Crash Severity
by Johannes Frank, Cédric Roussel and Klaus Böhm
ISPRS Int. J. Geo-Inf. 2025, 14(11), 454; https://doi.org/10.3390/ijgi14110454 - 19 Nov 2025
Viewed by 1066
Abstract
As road users and means of transport in Germany become more diverse, we must better understand the causes and influencing factors of serious crashes. The aim of this work is to develop an AI-supported analysis approach that identifies and clearly visualizes the causes [...] Read more.
As road users and means of transport in Germany become more diverse, we must better understand the causes and influencing factors of serious crashes. The aim of this work is to develop an AI-supported analysis approach that identifies and clearly visualizes the causes of crashes and their impact on crash severity in the urban area of the city of Mainz. The machine learning models predict crash severity and use Shapley values as explainability methods to make the underlying patterns understandable for urban planners, safety personnel, and other stakeholders. A particular challenge lies in presenting these complex relationships in a user-friendly way through visualizations and interactive maps. Full article
(This article belongs to the Special Issue Cartography and Geovisual Analytics)
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22 pages, 3516 KB  
Article
Hurricane Precipitation Intensity as a Function of Geometric Shape: The Evolution of Dvorak Geometries
by Ivan Gonzalez Garcia, Alfonso Gutierrez-Lopez, Ana Marcela Herrera Navarro and Hugo Jimenez-Hernandez
ISPRS Int. J. Geo-Inf. 2025, 14(11), 443; https://doi.org/10.3390/ijgi14110443 - 8 Nov 2025
Viewed by 1356
Abstract
The Dvorak technique has represented a fundamental tool for understanding the power of tropical cyclones based on their shape and geometric evolution. However, it should be noted that the Dvorak technique is purely morphological in nature and was developed for wind, not precipitation. [...] Read more.
The Dvorak technique has represented a fundamental tool for understanding the power of tropical cyclones based on their shape and geometric evolution. However, it should be noted that the Dvorak technique is purely morphological in nature and was developed for wind, not precipitation. The role of shape methods in precipitation prediction remains uncertain, particularly in the context of modern multi-sensor capabilities. This uncertainty forms the motivation for the present study. In an attempt to enrich Dvorak’s technique, this study proposes a novel hypothesis. This study tests the hypothesis that higher precipitation intensity is associated with more organized cloud-system morphology, as captured by simple geometric descriptors and indicative of dynamically coherent convection. A total of 3419 cloud-system objects (after size filter) were utilized to establish geometric relationships in each of them. For the case study of Hurricane Patricia over the Mexican coast in 2015, 3858 geometric shapes were processed. The cloud-system morphology was derived from geostationary imagery (GOES-13) and collocated with satellite precipitation estimates in order to isolate intense-rainfall objects (>50 mm/h). For each object, simple geometric descriptors were computed, and shape variability was summarised via Principal Component Analysis (PCA). The present study sought to evaluate the associations with rain-rate metrics (mean, mode, maximum) using rank correlations and k-means clustering. Furthermore, sensitivity analyses were conducted on the rain threshold and minimum object size. A Shape Descriptor: ratio between perimeter and diameter was identified as a promising tool to enhance early prediction models of extreme rainfall, contributing to enhanced meteorological risk management. The study indicates that cloud shape can serve as a valuable indicator in the classification and forecasting of intense cloud systems. Full article
(This article belongs to the Special Issue Cartography and Geovisual Analytics)
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12 pages, 3911 KB  
Article
Study Area Map Generator: A Web-Based Shiny Application for Generating Country-Level Study Area Maps for Scientific Publications
by Cesar Ivan Alvarez, Juan Gabriel Mollocana-Lara, Izar Sinde-González and Ana Claudia Teodoro
ISPRS Int. J. Geo-Inf. 2025, 14(10), 387; https://doi.org/10.3390/ijgi14100387 - 3 Oct 2025
Cited by 1 | Viewed by 4788
Abstract
The increasing demand for high-quality geospatial visualizations in scientific publications has highlighted the need for accessible and standardized tools that support reproducible research. Researchers from various disciplines—often without expertise in Geographic Information Systems (GIS)—frequently require a map figure to locate their study area. [...] Read more.
The increasing demand for high-quality geospatial visualizations in scientific publications has highlighted the need for accessible and standardized tools that support reproducible research. Researchers from various disciplines—often without expertise in Geographic Information Systems (GIS)—frequently require a map figure to locate their study area. This paper presents the Study Area Map Generator, a web-based application developed using Shiny for Python, designed to automate the creation of country- and city-level study area maps. The tool integrates geospatial data processing, cartographic rendering, and user-friendly customization features within a browser-based interface. It enables users—regardless of GIS proficiency—to generate publication-ready maps with customizable titles, basemaps, and inset views. A usability survey involving 92 participants from diverse professional and geographic-based backgrounds revealed high levels of satisfaction, ease of use, and perceived usefulness, with no significant differences across GIS experience levels. The application has already been adopted in academic and policy contexts, particularly in low-resource settings, demonstrating its potential to democratize access to cartographic tools. By aligning with open science principles and supporting reproducible workflows, the Study Area Map Generator contributes to more equitable and efficient scientific communication. The application is freely available online. Future developments include support for subnational units, thematic overlays, multilingual interfaces, and enhanced export options. Full article
(This article belongs to the Special Issue Cartography and Geovisual Analytics)
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Article
Vector Data Rendering Performance Analysis of Open-Source Web Mapping Libraries
by Dániel Balla and Mátyás Gede
ISPRS Int. J. Geo-Inf. 2025, 14(9), 336; https://doi.org/10.3390/ijgi14090336 - 30 Aug 2025
Cited by 6 | Viewed by 7130
Abstract
Nowadays, various technologies exist with differing rendering performance for interactive web maps. These maps are consumed on devices with varying capabilities; therefore, choosing the best-performing library for a dataset is emphasized. Unlike existing research, this study presents a comparative analysis on libraries’ native [...] Read more.
Nowadays, various technologies exist with differing rendering performance for interactive web maps. These maps are consumed on devices with varying capabilities; therefore, choosing the best-performing library for a dataset is emphasized. Unlike existing research, this study presents a comparative analysis on libraries’ native performance for rendering large amounts of GeoJSON vector data, partially extracted from OpenStreetMap (OSM). Four libraries were analyzed. Results showed that regardless of feature types, Leaflet and OpenLayers excelled for features up to 10,000. Up to 5000 points, these two were the fastest, above which the libraries’ performance converged. For 50,000 or more, Mapbox GL JS rendered them the quickest, followed by OpenLayers, MapLibre GL JS and Leaflet. For up to 50,000 lines and 10,000 polygons, Leaflet and OpenLayers were the fastest in all scenarios. For 100,000 lines, OpenLayers was almost twice as fast as the others, while Mapbox rendered 50,000 polygons the quickest. The performance of Leaflet and OpenLayers scales with the increasing feature quantities, yet for Mapbox and MapLibre, any performance impact is offset to 1000 features and beyond. Slow initalization of map elements makes Mapbox and MapLibre less suitable for rapid rendering of small feature quantities. Other behavioural differences affecting user experience are also explored. Full article
(This article belongs to the Special Issue Cartography and Geovisual Analytics)
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