Imaging the Earth’s surface and reconstructing its topography to study the landscape and (sub-) surface processes have strongly evolved during the past two decades, sometimes separately in different scientific disciplines of geosciences. New generations of satellites, Uncrewed Aerial Vehicles (UAVs), LiDAR systems, Structure-from-Motion (SfM) methods and deep learning approaches have made 2D, 3D and 4D (time series) data acquisitions 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 details. Coupled with the development of optimized workflows to digitize and process analogue data, such as historical aerial photographs, geoscientists now have various sets of tools to better understand our rapidly changing environments and distinguish the anthropogenic and natural causes of these changes.
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 deal with complex camera distortions? How to process unknown, damaged and/or poorly overlapping digitized analogue photographs? How to properly assess the precision of these measurements and take these estimates into account in our results and interpretation? How to deal with heterogeneous time series? These questions exemplify situations commonly faced by geoscientists.
In the present session, we would like to gather contributions from a broad range of geoscience disciplines (geomorphology, glaciology, volcanology, hydrology, bio-geosciences, geology, soil sciences, etc.) to share our views and experience about the opportunities, limitations and challenges that modern 2D/3D/4D surface imaging offers, no matter the physical process or environment studied. Contributions can cover any aspects of surface imaging, from new methods, tools and processing workflows to precision assessments, time series constructions and specific applications in geosciences. We would like to especially emphasize 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.
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 deal with complex camera distortions? How to process unknown, damaged and/or poorly overlapping digitized analogue photographs? How to properly assess the precision of these measurements and take these estimates into account in our results and interpretation? How to deal with heterogeneous time series? These questions exemplify situations commonly faced by geoscientists.
In the present session, we would like to gather contributions from a broad range of geoscience disciplines (geomorphology, glaciology, volcanology, hydrology, bio-geosciences, geology, soil sciences, etc.) to share our views and experience about the opportunities, limitations and challenges that modern 2D/3D/4D surface imaging offers, no matter the physical process or environment studied. Contributions can cover any aspects of surface imaging, from new methods, tools and processing workflows to precision assessments, time series constructions and specific applications in geosciences. We would like to especially emphasize 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.