Recent advances in image collection, e.g. using uncrewed aerial vehicles (UAVs), and topographic measurements, e.g. using terrestrial or airborne LiDAR, are providing an unprecedented insight into landscape and process characterization in geosciences. In parallel, historical data including terrestrial, aerial, and satellite photos as well as historical digital elevation models (DEMs), can extend high-resolution time series and offer exciting potential to distinguish anthropogenic from natural causes of environmental change and to reconstruct the long-term evolution of the surface from local to landscape scale.
For both historic and contemporary scenarios, the rise of techniques with ‘structure from motion’ (SfM) processing has democratized data access and offers a new measurement paradigm to geoscientists. Photogrammetric and remote sensing data are now available on spatial scales from millimetres to kilometres and over durations of single events to lasting time series (e.g. from sub-second to decadal-duration time-lapse), allowing the evaluation of event magnitude and frequency interrelationships.
The session welcomes contributions from a broad range of geoscience disciplines such as geomorphology, cryosphere, volcanology, hydrology, bio-geosciences, and geology, addressing methodological and applied studies. Our goal is to create a diversified and interdisciplinary session to explore the potential, limitations, and challenges of topographic datasets for the reconstruction and interpretation of past and present 2D and 3D changes in different environments and processes. We further encourage contributions describing workflows that optimize data acquisition and processing to guarantee acceptable accuracies and to automate data application (e.g. geomorphic feature detection and tracking), and field-based experimental studies using novel multi-instrument and multi-scale methodologies. This session invites contributions on the state of the art and the latest developments in i) modern photogrammetric and topographic measurements, ii) remote sensing techniques as well as applications, iii) modelling technologies, and iv) data processing tools, for instance, using machine learning approaches.
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