This session aims to showcase novel applications of methods from the field of artificial intelligence and machine learning in geodesy.

In recent years, the exponential growth of geodetic data from various observation techniques has created challenges and opportunities. Innovative approaches are required to efficiently handle and harness the vast amount of geodetic data available nowadays for scientific purposes, for example when dealing with “big data” from Global Navigation Satellite System (GNSS) and Interferometric Synthetic Aperture Radar (InSAR). Likewise, numerical weather models and other environmental models important for geodesy come with ever-growing resolutions and dimensions. Strategies and methodologies from the fields of artificial intelligence and machine learning have shown great potential not only in this context but also when applied to more limited data sets to solve complex non-linear problems in geodesy.

We invite contributions related to various aspects of applying methods from artificial intelligence and machine learning (including both shallow and deep learning techniques) to geodetic problems and data sets. We welcome investigations related to (but not limited to): more efficient and automated processing of geodetic data, pattern and anomaly detection in geodetic time series, images or higher-dimensional data sets, improved predictions of geodetic parameters, such as Earth orientation or atmospheric parameters into the future, combination and extraction of information from multiple inhomogeneous data sets (multi-temporal, multi-sensor, multi-modal fusion), feature selection and sensitivity, downscaling geodetic data, and improvements of large-scale simulations. We strongly encourage contributions that address crucial aspects of uncertainty quantification and integration of physical relationships into data-driven frameworks. Moreover, addressing reproducibility, interpretability and explainability of machine learning outcomes is certainly fundamental for ensuring scientific rigorousness of novel AI-based solutions.

By combining the power of artificial intelligence with geodetic science, we aim to open new horizons in our understanding of Earth's dynamic geophysical processes. Join us in this session to explore how the fusion of physics and machine learning promises advantages in generalization, consistency, and extrapolation, ultimately advancing the frontiers of geodesy.

A global Terrestrial Reference Frame (TRF) is fundamental for monitoring the Earth's rotation in space, and to many Earth science applications that need absolute positioning and precise orbit determination of near-Earth satellites. An accurate and stable TRF is especially needed for the quantification of global change phenomena such as sea level rise, current ice melting, tectonic, and seismic deformations. This session generally welcomes contributions on the computation, the evaluation and the use of TRFs.

The computation of TRFs relies on space geodetic observations acquired by ground networks of stations and requires the estimation of a large number of parameters including station positions and Earth Orientation Parameters. Nowadays, measurement biases and imperfect background models are the main factors limiting the accuracy of TRFs. This session therefore welcomes contributions that develop strategies to overcome systematics in space geodetic observing systems such as long-term mean range biases in SLR observations, gravitational deformation of VLBI antennas, GNSS antenna phase patterns, etc.

The second objective of this session is to bring together contributions from individual technique services, space geodetic data analysts, ITRS combination centers and TRF users to discuss the TRF solutions produced by different groups, with a special focus on their comparison, evaluation and updates. The understanding of the discrepancies between the terrestrial scale observed by the different space geodetic techniques, the determination of new local tie vectors at co-location sites, the improvement of geocentre motion determination and the assessment of observed non-linear station motions by comparison with geophysical deformation models are of particular interest.

Papers on the exploitation of past ITRF solutions and the latest 2020 solution updates are of course welcome, as well as presentations regarding any type of development that could improve future TRF solutions. With the development of the GENESIS mission, any contributions on the handling and the impact of co-located instruments of individual techniques onboard satellite missions (space ties) for TRF realization are strongly encouraged. Contributions concerning TRF construction strategies based on combination at the observation level are also welcome.

Fibre optic based techniques allow probing highly precise point and distributed sensing of the full ground motion wave-field including translation, rotation and strain, as well as environmental parameters such as temperature at a scale and to an extent previously unattainable with conventional geophysical sensors. Considerable improvements in optical and atom interferometry enable new concepts for inertial rotation, translational displacement and acceleration sensing. Laser reflectometry on commercial fibre optic cables allows for the first time spatially dense and temporally continuous sensing of the ocean’s floor, successfully detecting a variety of signals including microseism, local and teleseismic earthquakes, volcanic events, ocean dynamics, etc. Significant breakthrough in the use of fibre optic sensing techniques came from the new ability to interrogate telecommunication cables to high temporal and spatial precision across a wide range of environments. Applications based on this new type of data are numerous, including: seismic source and wave-field characterisation with single point observations in harsh environments such as active volcanoes and the seafloor, seismic ambient noise interferometry, earthquake and tsunami early warning, and infrastructure stability monitoring.

We welcome contributions on developments in instrumental and theoretical advances, applications and processing with fibre optic point and/or distributed multi-sensing techniques, light polarization and transmission analyses, using standard telecommunication and/or engineered fibre cables. We seek studies on theoretical, instrumental, observation and advanced processing across all solid earth fields, including seismology, volcanology, glaciology, geodesy, geophysics, natural hazards, oceanography, urban environment, geothermal applications, laboratory studies, large-scale field tests, planetary exploration, gravitational wave detection, fundamental physics. We encourage contributions on data analysis techniques, novel applications, machine learning, data management, instrumental performance and comparison as well as new experimental, field, laboratory, modelling studies in fibre optic sensing studies.

In recent years, we have observed steady progress in signals, services, and satellite deployment of Global Navigation Satellite Systems (GNSS). Consequently, modernizing and developing GNSS constellations have moved us towards an era of multi-constellation and multi-frequency GNSS signal availability. Also, the deployment of LEO constellations brings opportunities for LEO-augmented PNT services and applications, which, however, forces revisiting the existing and developing novel processing algorithms when fusing LEO and GNSS. Meanwhile, the technology development provided high-grade GNSS user receivers to collect high-rate, low-noise, and multipath impact measurements. Also, recent extraordinary progress in low-cost GNSS chipsets, smartphones, and sensor fusion must be acknowledged. Such advancements boost GNSS research and catalyze an expansion of satellite navigation to novel areas of science and industry. On one side, the developments stimulate a broad range of new GNSS applications. On the other side, they result in new challenges in data processing. Hence, algorithmic advancements are needed to address the opportunities and challenges in enhancing high-precision GNSS applications' accuracy, availability, interoperability, and integrity.
This session is a forum to discuss advances in high-precision GNSS algorithms and their applications in geosciences such as geodesy, geodynamics, seismology, tsunamis, ionosphere, troposphere, etc.
We encourage but do not limit submissions related to:
- GNSS processing algorithms,
- Multi-GNSS benefits for Geosciences,
- Multi-constellation GNSS processing and product standards,
- High-rate GNSS,
- Low-cost receiver and smartphone GNSS observations for precise positioning, navigation, and geoscience applications,
- LEO-augmented precise positioning and quality control,
- LEO observations modeling and processing algorithms,
- Precise Point Positioning (PPP, PPP-RTK) and Real Time Kinematic (RTK),
- GNSS and other sensors (accelerometers, INS, etc.) fusion,
- GNSS products for high-precision applications (orbits, clocks, uncalibrated phase delays, inter-system and inter-frequency biases, etc.),
- Troposphere and ionosphere modeling and sounding with GNSS,
- CORS services for Geosciences (GBAS, Network-RTK, etc.),
- Precise Positioning of EOS platforms,
- GNSS for natural hazards prevention,
- Monitoring crustal deformation and the seismic cycle of active faults,
- GNSS and early-warning systems,
- GNSS reflectometry.

Remarkable advances over recent years prove that geodesy today develops under a broad spectrum of interactions, including theory, science, engineering, technology, observations, and practice-oriented services. Geodetic science accumulates significant results in studies towards classical geodetic problems and problems that only emerged or gained new interest, in many cases due to synergistic activities in geodesy and tremendous advances in the instrumentations and computational tools. In-depth studies progressed in parallel with investigations that led to a broadening of the traditional core of geodesy. The scope of the session is conceived with a certain degree of freedom, even though the session intends to provide a forum for all investigations and results of a theoretical and methodological nature.
Within this concept, we seek contributions concerning problems of reference frames, gravity field, geodynamics, and positioning, but also studies surpassing the frontiers of these topics. We invite presentations discussing analytical and numerical methods in solving geodetic problems, advances in mathematical modelling and statistical concepts, or the use of high-performance facilities. Demonstrations of mathematical and physical research directly motivated by geodetic practice and ties to other disciplines are welcome. In parallel to theory-oriented results, examinations of novel data-processing methods in various branches of geodetic science and practice are also acceptable.

We are looking for studies that investigate how tectonic plates move, how this movement is accommodated in deformation zones, and how elastic strain builds up and is released along faults and at plate boundaries. These studies should combine space- or sea-floor geodesy with observations like seismicity, geological slip-rates and rakes or sea-level and gravity changes.

How to best reference relative InSAR rate tiles to a plate? How can we infer the likelihood of future earthquakes from elastic strain buildup? How persistent are fault asperities over multiple earthquake cycles? Are paleoseismic fault slip rates identical to those constrained by geodesy? What portion of plate motion results in earthquakes, and where does the rest go? How do mountains grow? How well can we constrain the stresses that drive the observed deformation? How much do the nearly constant velocities of plates vary during the earthquake cycle, and does this influence the definition of Earth's reference frame?

We seek studies using space and sea floor geodetic data that focus on plate motion, deformation zones, and the earthquake cycle. Key questions include earthquake likelihood, fault slip-rates, uplift rates, non-elastic strain, and sea-level changes.