Improving global digital elevation models using space-borne GEDI and ICESat-2 LiDAR altimetry data

Open source Global Digital Elevation Models (GDEMs) serve as an important base for studies in geosciences. However, these models contain vertical errors due to various reasons. In this study, data from two Satellite LiDAR altimetry systems, GEDI and ICESat-2, were used to improve the vertical accuracy of GDEMs. Three different machine learning...

Automatically extracting surfaces of reinforced concrete bridges from terrestrial laser scanning point clouds

Three-dimensional (3D) geometric bridge models play an important role in bridge inspection, assessment, and management. Laser scanning nowadays offers a cost-efficient method to capture dense, accurate 3D topographic data of surfaces of the bridge. However, given the typical complexity of bridges, current workflows using commercial software...

Investigation of pointnet for semantic segmentation of large-scale outdoor point clouds

Semantic segmentation of point clouds is indispensable for 3D scene understanding. Point clouds have credibility for capturing geometry of objects including shape, size, and orientation. Deep learning (DL) has been recognized as the most successful approach for image semantic segmentation. Applied to point clouds, performance of the many DL...

LiDAR-guided dense matching for detecting changes and updating of buildings in Airborne LiDAR data

Change detection is essential to keep 3D city models up-to-date. LiDAR data with high accuracy are used to create 3D city models. However, updating LiDAR data at state or nation level often takes around a decade. Very high resolution (VHR) stereo images, with often yearly updating rate and dense 3D information, provide an option for...

Building segmentation from airborne vhr images using mask r-cnn

Up-to-date 3D building models are important for many applications. Airborne very high resolution (VHR) images often acquired annually give an opportunity to create an up-to-date 3D model. Building segmentation is often the first and utmost step. Convolutional neural networks (CNNs) draw lots of attention in interpreting VHR images as they can...

Automatic shadow detection in urban very-high-resolution images using existing 3D models for free training

Up-to-date 3D city models are needed for many applications. Very-high-resolution (VHR) images with rich geometric and spectral information and a high update rate are increasingly applied for the purpose of updating 3D models. Shadow detection is the primary step for image interpretation, as shadow causes radiometric distortions. In addition,...

AdTree: Accurate, Detailed, and Automatic Modelling of Laser-Scanned Trees

Laser scanning is an effective tool for acquiring geometric attributes of trees and vegetation, which lays a solid foundation for 3-dimensional tree modelling. Existing studies on tree modelling from laser scanning data are vast. However, some works cannot guarantee sufficient modelling accuracy, while some other works are mainly rule-based and...

Robust cylinder fitting in three-dimensional point cloud data

This paper investigates the problems of cylinder fitting in laser scanning three-dimensional Point Cloud Data (PCD). Most existing methods require full cylinder data, do not study the presence of outliers, and are not statistically robust. But especially mobile laser scanning often has incomplete data, as street poles for example are only...

Quality assessment and comparison of smartphone, airborne and leica c10 laser scanner based point clouds

3D urban models are valuable for urban map generation, environment monitoring, safety planning and educational purposes. For 3D measurement of urban structures, generally airborne laser scanning sensors or multi-view satellite images are used as a data source. However, close-range sensors (such as terrestrial laser scanners) and low cost cameras...

Morphological changes along a dike landside slope sampled by 4D high resolution terrestrial laser scanning

Emergence of light detection and ranging (LiDAR) technology provides new tools for geomorphologic studies improving spatial and temporal resolution of data sampling hydrogeological instability phenomena. Specifically, terrestrial laser scanning (TLS) collects high resolution 3D point clouds allowing more accurate monitoring of erosion rates...

Active Shapes for Automatic 3D Modeling of Buildings

Recent technological developments help us to acquire high quality 3D measurements of our urban environment. However, these measurements, which come as point clouds or Digital Surface Models (DSM), do not directly give 3D geometrical models of buildings. In addition to that, they are not suitable for fast 3D rendering. Therefore, detection and 3D...

Terrestrial laser scanning for geometry extraction and change monitoring of rubble mound breakwaters

Rubble mound breakwaters are coastal defense structures that protect harbors and beaches from the impacts of both littoral drift and storm waves. They occasionally break, leading to catastrophic damage to surrounding human populations and resulting in huge economic and environmental losses. Ensuring their stability is considered to be of...

Accuracy assessment of building point clouds automatically generated from iphone images

Low-cost sensor generated 3D models can be useful for quick 3D urban model updating, yet the quality of the models is questionable. In this article, we evaluate the reliability of an automatic point cloud generation method using multi-view iPhone images or an iPhone video file as an input. We register such automatically generated point cloud...

ICESat Full-Waveform Altimetry Compared to Airborne Laser Scanning Altimetry Over The Netherlands

Since 2003, the full-waveform laser altimetry system onboard NASA's Ice, Cloud and land Elevation Satellite (ICESat) has acquired a worldwide elevation database. ICESat data are widely applied for change detection of ice sheet mass balance, forest structure estimation, and digital terrain model generation of remote areas. ICESat's measurements...