GM2.4 | Integrating 3D Data in Geomorphology, Landscape Evolution, and Sediment Transport
EDI
Integrating 3D Data in Geomorphology, Landscape Evolution, and Sediment Transport
Convener: Mathilde LetardECSECS | Co-conveners: Ron Nativ, David Mair, Fiona Clubb

3D data are becoming ubiquitous throughout geomorphology, with the rapid expansion in the availability of high-resolution topographic data, such as from terrestrial or airborne LiDAR, advances in the availability of CT scanning for sedimentological analysis, and the collection of combined topographic and bathymetric data from rivers and coasts. These data take the form of high-density 3D point clouds or image stacks, which might be used to model a landscape, a sediment core, or a riverbed, for example. Using 3D data to extract meaningful geomorphic information involves challenges in data acquisition, storage, analysis, and computational processing, which requires the innovation of new techniques or algorithms to efficiently process and analyse large volumes of data.

This session welcomes studies taking advantage of 3D data to advance our understanding of geomorphology, landscape evolution, or sediment transport. Abstract submissions may address any type of 3D data, including but not limited to topo-bathymetric data, CT scanning, terrestrial and airborne LiDAR, and UAV data. Topics may involve data acquisition; methods for processing and/or segmenting 3D data; extracting features such as landforms, sediment grain sizes, orientations, and shapes; or topographic change detection and landscape evolution. Submissions from early career scientists and from those in underrepresented groups within the geosciences are particularly encouraged.

3D data are becoming ubiquitous throughout geomorphology, with the rapid expansion in the availability of high-resolution topographic data, such as from terrestrial or airborne LiDAR, advances in the availability of CT scanning for sedimentological analysis, and the collection of combined topographic and bathymetric data from rivers and coasts. These data take the form of high-density 3D point clouds or image stacks, which might be used to model a landscape, a sediment core, or a riverbed, for example. Using 3D data to extract meaningful geomorphic information involves challenges in data acquisition, storage, analysis, and computational processing, which requires the innovation of new techniques or algorithms to efficiently process and analyse large volumes of data.

This session welcomes studies taking advantage of 3D data to advance our understanding of geomorphology, landscape evolution, or sediment transport. Abstract submissions may address any type of 3D data, including but not limited to topo-bathymetric data, CT scanning, terrestrial and airborne LiDAR, and UAV data. Topics may involve data acquisition; methods for processing and/or segmenting 3D data; extracting features such as landforms, sediment grain sizes, orientations, and shapes; or topographic change detection and landscape evolution. Submissions from early career scientists and from those in underrepresented groups within the geosciences are particularly encouraged.