LiDAR mapping

A classified point cloud contains millions of three-dimensional LiDAR observations organised into practical groups such as ground, vegetation, buildings and other visible surfaces. The classification makes the dataset easier to filter, inspect and reuse for different technical tasks. LAS or compressed LAZ files can be opened in standard point-cloud, GIS and engineering software for terrain analysis, asset review and detailed measurement.

A bare-earth terrain model represents the ground surface after suitable vegetation and above-ground objects have been separated from the LiDAR observations. It is particularly useful where trees or dense cover make normal aerial imagery difficult to interpret. The resulting DTM supports terrain understanding, drainage and watershed review, slope analysis, route planning and the preparation of contours or engineering sections within the surveyed conditions.

The LiDAR surface model records the uppermost measured surfaces across the site, including tree canopies, structures and exposed ground. It provides a continuous height reference for understanding what occupies the landscape, not only the terrain beneath it. Teams can use the DSM for canopy assessment, visibility studies, clearance review, surface comparison and as a supporting raster layer in GIS or specialist analysis software.

Elevation mapping converts the LiDAR terrain into contours and other level information that can be read in CAD and GIS systems. It provides a practical view of relief, slope changes, valleys, ridges and local height differences across the survey area. The supplied interval and format are selected for the intended use so project teams can integrate the mapping into planning, environmental review or engineering development.

Engineering sections extract the LiDAR surface along selected lines to show how elevation changes through a corridor, riverbed, embankment or other area of interest. Longitudinal profiles explain change along a route, while cross-sections show its shape from side to side. These focused outputs help teams review gradients, clearances, terrain constraints and design context without navigating the complete larger three-dimensional dataset.

The classification record documents how the LiDAR dataset was processed and organised. It identifies the supplied classes, coordinate reference, coverage, point-cloud format, quality review and any limits that users should understand. This supporting information helps technical teams interpret the data consistently, select the right classes for their work and maintain a traceable basis when the terrain products are reused later.