LiDARpunktmoln

LiDARpunktmoln, or LiDAR point cloud, is a data set of numerous 3D points captured by LiDAR systems. Each point records coordinates (X, Y, Z) and may include attributes such as return intensity, color, and a classification tag. The cloud represents surfaces in the scanned environment and supports 3D models, measurements, and analyses. In German-language contexts, the standard term is LiDAR-Punktwolke.

Points are stored unstructured; there is no inherent connectivity between neighboring points. To enable efficient processing, clouds are indexed with spatial data structures (for example octrees or k-d trees) and stored in standardized formats. Common file formats include LAS and its compressed LAZ, PLY, and E57, with coordinates defined in a chosen CRS and units (typically meters).

LiDAR data are acquired by different platforms: airborne LiDAR mounted on aircraft, mobile LiDAR on vehicles, and terrestrial LiDAR on tripods or robots. Sensor configurations, point density, and scanning patterns vary, affecting accuracy and vegetation penetration. Point clouds can be colorized by co-registered imagery or laser intensity measurements, enhancing interpretation.

Processing typically involves filtering noise, classifying points (ground, vegetation, buildings), and normalizing elevations to produce digital terrain models or digital surface models. Further steps include segmentation, feature extraction, temporal analysis, and surface reconstruction. LiDAR point clouds underpin applications in surveying, urban planning, forestry, archaeology, and autonomous navigation.

Challenges include large data volumes, occlusion, datum alignment, and the need for accurate georeferencing. Data integration with imagery and other sensor data remains an active area of research, as do methods for real-time processing in field environments.