Academic Scope
This sub-session focuses on advanced spatial analysis, geospatial modeling, and the application of artificial intelligence to geospatial data processing. The increasing availability of large and complex spatial datasets has created new opportunities for data-driven decision-making through machine learning, deep learning, and intelligent analytical frameworks.
The sub-session welcomes contributions related to GIS-based spatial analysis, environmental modeling, predictive analytics, Geo-AI applications, and spatial statistics. Research utilizing machine learning, deep learning, and advanced visualization techniques for 2D, 3D, and 4D spatial data is particularly encouraged.
The session promotes interdisciplinary approaches that combine geospatial science, data analytics, and artificial intelligence to improve understanding of environmental processes, resource systems, and spatial dynamics.
Session Metadata
Target audience: Researchers in geodesy, GIS, remote sensing, and Geo-AI Engineers and practitioners in geospatial systems Data scientists and AI specialists Government and policy stakeholders Industry professionals and technology providers Graduate students and early-career researchers
Recommended Contributions
Original research, case studies, applied methodological papers, and evidence-based perspectives aligned with the scope of this sub-session.
Author Guidance
Abstracts should be submitted in English (250–300 words), clearly linked to this sub-session code, and should state objective, methodology, key results, and relevance.
Review Fit
Submissions should demonstrate scientific relevance, originality, methodological quality, clarity, and alignment with the session theme.
Fees & Bank Transfer
Use the details below to transfer your registration fee. After transferring, log in and confirm the payment on your submission page — the secretariat will verify the receipt.
- Bank
- ГОЛОМТ
- Account #
47001 500 8115007020- Holder
- ШУТИС ГУУС
- Currency
- USD
