Artificial Intelligence Potential to Solve Multiple Complex Geodetic Problems

Dear Colleagues,

Artificial intelligence (AI) has emerged as a powerful tool for addressing complex challenges in geodesy, the science of measuring and understanding the Earth’s size, shape, gravitational field, changes over time, and other geophysical phenomena. By leveraging a diversity of AI methods and algorithms (ANNs, CNNs, SVM, RF, DT, KNN, ARIMA, GANs, XGBoost, cluster algorithms, ML, DL, and others), geodetic problems can be solved more efficiently and with greater precision. AI methods are becoming increasingly important for solving complex problems related to increasing volumes of multi-sensor data from satellite, ground, and airborne measurements and observations to estimate various geodetic parameters. AI's potential to analyze large datasets, particularly useful in automating real-time data analysis, enabling better prediction and modeling, which is essential for various applications such as forecasting, anomaly detection, and pattern recognition. Using AI in geodesy offers opportunities to test new methodologies and techniques that complement and extend existing methods and approaches. The scalability of AI to analyze large datasets, automate processes, and identify patterns that traditional methods may overlook complements and enhances existing surveying research, driving both progress and new insights.

The Special Issue is to present the latest advances in using artificial intelligence methods to solve complex geodetic problems, which include, but are not limited to, the following:

• AI for integrating multiple geodetic data sources;
• Geodetic data processing and analysis using AI;
• Geospatial data interpretation, modeling, and prediction;
• AI for error detection and calibration;
• AI and GNSS observation analyses;
• AI methods and algorithms for time series analysis;
• AI for geoid modeling;
• AI applications for real-time monitoring;
• AI for geohazard assessment and prediction;
• AI for climate change monitoring;
• AI supporting interdisciplinary research.

Dr. Lyubka Pashova
Prof. Dr. Shuanggen Jin
Prof. Dr. Desislava Ivanova
Guest Editors

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