LIDARdata

LiDAR data is the digital output produced by Light Detection and Ranging sensors. It consists of a dense collection of 3D points that encode the geometry of surfaces and objects in the scanned environment, typically with attributes such as return number, laser pulse energy (intensity), and classification labels.

Data are acquired from various platforms, including airborne, terrestrial, and mobile LiDAR. Time-of-flight or phase-based sensors measure the distance to illuminated targets. A single flight or scan yields large point clouds that are georeferenced using GPS and inertial navigation data and organized by scanning pattern or flight line.

Common file formats include LAS and its compressed version LAZ, as well as E57 and PLY. LAS supports standardized fields for coordinates, intensity, and classification, while LAZ reduces storage size. Point clouds carry metadata such as coordinate reference system, sampling density, and sensor parameters.

Processing typically involves alignment (georeferencing), noise removal, and classification to separate ground, vegetation, buildings, and other features. Generated raster products include digital elevation models (DEMs), digital surface models (DSMs), and canopy height models (CHMs). Quality control and attribute editing are common steps, using specialized software.

LiDAR data support a wide range of applications, including topographic mapping, flood risk assessment, forest inventory, urban planning, archaeology, and autonomous navigation. When combined with other data types, such as imagery or multispectral data, LiDAR enhances analyses by providing precise 3D structure and vertical accuracy.

Challenges include large data volumes, processing requirements, and variability in data quality. Standards and sharing practices emphasize metadata, reproducibility, and licensing, with open data portals and guidelines from agencies and research consortia.