Knowledge-Guided Map Representation and Understanding
A special issue of ISPRS International Journal of Geo-Information (ISSN 2220-9964).
Deadline for manuscript submissions: 30 June 2026 | Viewed by 157
Special Issue Editors
Interests: cartography; schematic map representation; information visualization
Interests: spatial knowledge services; geographic information systems; spatial-temporal knowledge visualization and service
Interests: spatio-temporal data mining; map generalization; large language model
Interests: intelligent cartography; geography complexity analysis
Special Issue Information
Dear Colleagues,
Maps serve as crucial tools for revealing socio-economic and natural phenomena, as well as uncovering cognitive patterns in spatio-temporal distributions. Generating effective map representations based on spatio-temporal and semantic knowledge and enabling automated map understanding are key to enhancing user‑centric map usability. Recent advances in AI, particularly deep learning and large language models (LLMs), have significantly propelled progress toward these goals.
This Special Issue delves into the mutual construction of knowledge and map representation. One direction examines how spatio-temporal data, semantic structures, cognitive models, and cartographic design knowledge can be transformed into task-oriented map representations. The other investigates the automatic extraction of structured knowledge from these maps to support map design and visualization, spatial reasoning, semantic QA services, and intelligent decision‑making. We welcome interdisciplinary submissions that combine theory, methodology, modeling, and applications across cognitive cartography, representation design, computer vision, knowledge graphs, and multimodal foundation models, aiming to advance the symbiotic evolution of map representation and knowledge service under the influence of intelligent technologies.
Topics of Interest (include but are not limited to):
- Knowledge-driven cartography representation;
- Hybrid-intelligent map design, generation, service, and applications;
- Cognitive and perceptual foundations of spatial visualization;
- Automatic extraction of spatial-temporal and cartography knowledge from maps;
- Automatic map interpretation and understanding;
- Spatial question answering and reasoning using cartographic sources;
- Map-based training data for large language or vision-language models;
- Human–map interaction and visual reasoning;
- Integration of spatial knowledge and cartographic representations in digital twins.
Prof. Dr. Peng Ti
Prof. Dr. Wanzeng Liu
Prof. Dr. Wenhao Yu
Dr. Tian Lan
Dr. Wende Li
Guest Editors
Manuscript Submission Information
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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
- map representation
- map understanding
- cartography
- Artificial Intelligence (AI)
- spatio-temporal knowledge
- semantic knowledge
- knowledge extraction
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