Imaging the Earth’s surface and reconstructing its topography to study the landscape and (sub-)surface processes has advanced rapidly over the past two decades, sometimes separately within different geoscience disciplines. New generations of satellites, Uncrewed Aerial Vehicles (UAVs), LiDAR systems, Structure-from-Motion (SfM) methods, ground-based systems, and deep learning approaches have made 2D, 3D, and 4D (time series) data acquisition easier, cheaper, and more precise. The spatial, temporal, and spectral resolutions of the measurements cover wide ranges of scales, offering the opportunity to study the evolution of the ground surface from local to regional scale with unprecedented detail. Equipped with optimized workflows ranging from digitizing analogue data – such as historical aerial photographs – to processing near-continuous records of topographic change, geoscientists now have a variety of tools to better understand our rapidly changing environments and disentangle anthropogenic from natural drivers.
However, challenges still exist at both methodological and application levels. How to properly acquire images and 3D data in harsh, remote or non-ideal environments? How to process unknown, damaged and/or poorly overlapping digitized analogue photographs? How to assess measurement precision and incorporate this uncertainty in the results and interpretation? How to model complex camera distortions and/or the resulting systematic error? How to deal with large, heterogeneous time series and multi-modal data sets? These questions exemplify situations commonly faced by geoscientists.
In the present session, we invite contributions from a broad range of geoscience disciplines (geomorphology, glaciology, volcanology, hydrology, soil sciences, etc.) to share perspectives about the opportunities, limitations, and challenges that modern 2-4D surface imaging offers across diverse processes and environments. Contributions can cover any aspect of surface imaging and mapping, from new methods, tools, and processing workflows to precision assessments, time series constructions, and specific applications in geosciences. We especially welcome contributions that cover 1) novel data acquisition and processing approaches (including image matching, camera distortion correction, complex signal/image and point cloud processing, and time series construction), 2) data acquisition in complex and fast-changing environments, and 3) innovative applications in geosciences.