Over recent decades, 3D point clouds have been a popular data source applied in automatic
change detection in a wide variety of applications. Compared with 2D images, using 3D …

Blue carbon ecosystems (mangroves, seagrasses and saltmarshes) are highly productive
coastal habitats, and are considered some of the most carbon-dense ecosystems on the …

This study is concerned with urban change detection and categorization in point clouds. In
such situations, objects are mainly characterized by their vertical axis, and the use of native …

Building change detection in high-resolution satellite images plays a special role in urban
management and development. Recently, methods for building change detection have been …

Rockfall is a common hazard along US Interstate Highway 70 in Glenwood Canyon,
Colorado. While natural rock slopes source a substantial number of rockfalls, there remains …

Change detection has been increasingly studied in remote and close-range sensing in the
last decades, driven by its importance in environment monitoring and database updating …

Advances in remote sensing image processing techniques have further increased the
demand for annotated datasets. However, preparing annotated multi-temporal 2D/3D …

Neural radiance fields (NeRFs) combining machine learning with differentiable rendering
have arisen as one of the most promising approaches for novel view synthesis and depth …

Automatic point cloud classification (PCC) is a challenging task in large-scale urban point
clouds due to the heterogeneous density of points, the high number of points and the …

Automatic comparison of time-variant BIM models facilitates value-added applications
during the building life cycle. This paper addresses a solution capable of exploring changes …