It is estimated that over 80% of the world’s oceans are unexplored and unmapped limiting our understanding of ocean systems. Due to data collection rates of modern survey technologies such as swa…
Real-time semantic segmentation of point clouds has increasing importance in applications related to 3D city modelling and mapping, automated inventory of forests, autonomous driving and mobile rob…
This paper introduces methods for monitoring rock slope movements in Alpine environments based on terrestrial images. The first method is a photogrammtric point cloud-based deformation analysis, re…
In the view of climate change, understanding and managing effects on coastal areas and adjacent cities is essential. Permanent Laser Scanning (PLS) is a successful technique to not only observe not…
The ATLAS sensor onboard the ICESat-2 satellite is a photon-counting lidar (PCL) with a primary mission to map Earth's ice sheets. A secondary goal of the mission is to provide vegetation and terra…
Tree species characterise biodiversity, health, economic potential, and resilience of an ecosystem, for example. Tree species classification based on remote sensing data, however, is known to be a …
Three-dimensional (3D) point cloud registration is a fundamental step for many 3D modeling and mapping applications. Existing approaches are highly disparate in the data source, scene complexity, a…
Three-dimensional (3D) point cloud registration is a fundamental step for many 3D modeling and mapping applications. Existing approaches are highly disparate in the data source, scene complexity, a…
Emerging mobile LiDAR mapping systems exhibit great potential as an alternative for mapping urban environments. Such systems can acquire high-quality, dense point clouds that capture detailed infor…
Deep learning methods based on convolutional neural networks have shown to give excellent results in semantic segmentation of images, but the inherent irregularity of point cloud data complicates t…