Mapping biotic and abiotic seafloor habitat characteristics with multi-spectral multi-beam backscatter data

Detailed knowledge of both the sedimentological and ecological characteristics of the seafloor is essential when undertaking bottom-disturbing activities, but can be a challenge to obtain. Through backscatter data at different frequencies, collected with a multi-spectral multi-beam sonar, information on the structure of both the sediment...

Characterizing seabed sediments using multi-spectral backscatter data in the North Sea

Acoustic classification using single-beam and multi-beam echosounders has been widely applied in characterizing seabed sediments. Although previous studies have shown a better discrimination of fine and coarse sediments using multi-spectral echosounder data, analysis regarding comprehensive seabed sediment properties is still needed. In this...

Indications of marine benthos occurrence from multi-spectral multi-beam backscatter data: a case study in the North Sea

To facilitate the conservation of seafloor habitats and planning of offshore activities, there is a growing need for mapping marine benthos in an effective and efficient way. Acoustic data acquired by multi-beam echosounders (MBES) have been extensively used for large-scale and high-resolution seafloor characterization. A deeper understanding of...

Road type classification of MLS point clouds using deep learning

Functional classification of the road is important to the construction of sustainable transport systems and proper design of facilities. Mobile laser scanning (MLS) point clouds provide accurate and dense 3D measurements of road scenes, while their massive data volume and lack of structure also bring difficulties in processing. 3D point cloud...

Airborne Laser Scanning Point Cloud Classification Using the DGCNN Deep Learning Method

Classification of aerial point clouds with high accuracy is significant for many geographical applications, but not trivial as the data are massive and unstructured. In recent years, deep learning for 3D point cloud classification has been actively developed and applied, but notably for indoor scenes. In this study, we implement the point-wise...