From laser returns to a terrain model
An airborne system combines laser range, position and orientation to create a point cloud. Software classifies returns as ground, vegetation, buildings or other classes. A digital terrain model interpolates classified ground points; it does not literally remove a forest or expose buried objects.
Point cloud
Coordinates, return information, classification and acquisition metadata.
Terrain model
Grid resolution, interpolation and ground-class choices affect visible form.
Interpretation
Shape, context and comparison suggest a feature; field evidence tests it.
Visualization changes what stands out
Hillshade depends on illumination angle and can hide features aligned with the light. Slope, local relief and sky-view-factor products emphasize different geometry. A responsible interpretation checks several renderings and the underlying elevation values.
Minimum metadata
- Acquisition date, sensor, flight parameters and coordinate reference system.
- Point density, vertical accuracy, classification version and withheld/noise flags.
- Terrain grid resolution, interpolation and visualization settings.
- Feature coordinates, dimensions, confidence and validation status.
Evidence exercise
A 20 cm-high linear bank appears in one hillshade but disappears when illumination rotates 90 degrees. Before naming it, inspect elevation profiles, alternative visualizations, adjacent drainage and modern maps; then mark it as a candidate pending field verification.
Sources
Sources accessed 10 October 2026. This page provides no unpublished site coordinates or excavation conclusion.
Reading Archaeological LiDAR
LiDAR measures ranges to surfaces. Archaeological features emerge only after classification, terrain modelling and comparison with other evidence.
| Observe | Describe material, form, marks, wear or spatial relation without assigning identity or purpose. Begin with “From laser returns to a terrain model.” |
|---|---|
| Context | Locate the record in excavation, collection, restoration and display history. Check the chain against USGS LiDAR Base Specification and Historic England: Using Airborne Lidar in Archaeological Survey. |
| Infer | Elevation returns reveal surface form after classification choices; they do not by themselves identify a feature, its date or its function. Tie every attribution to the feature that supports it and retain competing readings. |
| Withhold | Do not extend “Point cloud” beyond the date, sample, comparison or provenance actually documented. |
Provenance checkpoint
List each custody or documentation gap separately; an unknown interval is evidence about the record, not permission to invent continuity.
Catalogue note
An airborne system combines laser range, position and orientation to create a point cloud. Software classifies returns as ground, vegetation, buildings or other classes. Mark later repairs, labels and digital reconstructions as later interventions rather than original features.
Research-room promptWhat single comparison object, technical test or archive entry would most change the interpretation of Reading Archaeological LiDAR?