Over the past decade, geodetic and remote sensing techniques have experienced significant growth, driven by the expansion of GNSS-based networks and the launch of satellite missions such as Sentinel-1, ALOS-2, TerraSAR-X, LuTan-1, SAOCOM-1, NISAR, and various commercial satellites. This rapidly increasing volume of data enables the acquisition of continuous and spatially extensive datasets over large regions of Earth, offering unprecedented opportunities to improve our understanding of natural and human-induced geohazards across a wide range of temporal and spatial scales, including earthquakes, volcanic eruptions, landslides, glacier dynamics, underground fluid changes, sea-level rise, land (coastal) subsidence, and tsunamis.
This session invites contributions across various disciplines and techniques to quantify, monitor and model the above-mentioned natural and human-induced processes, with particular emphasis on coastal vertical land motion and subsidence-related hazards. Interdisciplinary studies bridging tectonics, geodesy, volcanology, engineering geology, remote sensing, hydrology, ocean sciences, geomorphology and AI for enhanced risk assessment are strongly encouraged. We welcome contributions on a wide range of topics, including but not limited to: 1) Novel algorithms for mitigating SAR/InSAR errors, including deep learning approaches; 2) Advanced strategies for processing and analyzing SAR big data; 3) Integration of AI and machine learning with GNSS and InSAR observations to improve time series interpretation, identify deformation patterns, and disentangle driving processes, 4) multi-sensor and in-situ monitoring using geomorphologic, geodetic, field-based, and modeling approaches; 5) hazard assessments and disaster risk reduction, focusing on vulnerability, capacity, and resilience.
Mahdi Motagh