AI-Driven Digital Twins for Smart Cities and Spatial Governance
A special issue of Geomatics (ISSN 2673-7418).
Deadline for manuscript submissions: 30 May 2027 | Viewed by 95
Editors
Interests: urban informatics, urban digital twins; LLM apps; agentic AI; generative AI; visual analytics
Special Issues, Collections and Topics in MDPI journals
2. GATE Institute, Sofia University “St. Kliment Ohridski”, 1113 Sofia, Bulgaria
Interests: urban digital twins; data interoperability and semantic enrichment; data-intensive systems; generative AI for urban planning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Artificial intelligence is rapidly becoming an essential component of digital twins for smart cities and spatial governance. However, the reliability and trustworthiness of AI-driven digital twins fundamentally depend on the quality, consistency, interoperability, and uncertainty of the underlying geospatial data. While significant progress has been made in AI algorithms, comparatively less attention has been devoted to understanding how spatial data quality influences model performance, robustness, reproducibility, and decision-making.
This Special Issue aims to provide a geomatics-oriented perspective on AI-driven digital twins by focusing on the interaction between geographical data and AI systems. We welcome original research that investigates how data quality, spatial resolution, positional accuracy, semantic consistency, data fusion, interoperability, and uncertainty propagation affect AI-enabled digital twins and spatial intelligence. Contributions covering methodological developments, benchmarking frameworks, sensitivity analysis, quality assessment, and real-world case studies are particularly encouraged.
Topics of interest include, but are not limited to:
- Sensitivity of AI models to geospatial data quality and uncertainty
- Benchmarking AI-driven digital twins using heterogeneous spatial datasets
- Effects of spatial resolution, scale, and positional accuracy on AI performance
- Data interoperability, semantic harmonization, and standardization for digital twins
- Multi-source geospatial data fusion for AI-enabled urban systems
- Data quality assessment and validation for GeoAI applications
- Explainable, trustworthy, and reproducible AI for geomatics
- Geospatial foundation models and AI methods robust to imperfect spatial data
- AI-enabled digital twins for urban planning, infrastructure monitoring, environmental management, and disaster resilience
By emphasizing the relationship between geomatics data quality and AI performance, this Special Issue seeks to advance the methodological foundations of trustworthy, interoperable, and scalable digital twins for next-generation spatial governance.
Dr. Haowen Xu
Prof. Dr. Dessislava Petrova-Antonova
Guest Editors
Dr. Christina Mikrenska
Guest Editor Assistant
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. Geomatics is an international peer-reviewed open access semimonthly 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 1200 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
- AI-driven digital twins
- smart cities
- spatial governance
- 3D/4D geospatial modeling
- geomatics
- urban informatics
- spatial data infrastructures
- geospatial artificial intelligence (GeoAI)
- spatial standards
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