Common Terms in 3D Mapping and Surveying

An introduction to key concepts used in LiDAR and photogrammetry workflows

This post gives a brief overview of some key terms commonly used in 3D mapping and spatial data work. More detailed definitions and technical explanations will follow in future posts.

In the surveying, heritage, environmental, and property sectors, 3D spatial data is increasingly used for planning, documentation, analysis, and interpretation. Techniques such as terrestrial LiDAR scanning and photogrammetry techniques allow for accurate digital records of real-world structures, sites, and landscapes. However, the terminology can often be unclear to those not working directly in the field.

The terms below reflect the core methods used at Wren 3D and are also widely recognised across the broader industry.

A LiDAR survey produced this point cloud of Treborth Botanic Gardens Chinese Garden

Laser Scanning or LiDAR (Light Detection and Ranging)

Laser scanning, or LiDAR (Light Detection and Ranging), is a method used to record accurate 3D measurements by firing pulses of laser light at surfaces and recording the time it takes for them to return. The result is a highly detailed 3D dataset known as a point cloud.

At Wren 3D, we use tripod-mounted terrestrial LiDAR to scan buildings, historic sites, woodland structures, and terrain. It’s a reliable and precise way to record the shape and condition of physical spaces, down to millimetre accuracy.

Photogrammetry

Photogrammetry is the process of creating 3D models from photographs. By taking a series of overlapping images from different angles, software can reconstruct the shape and layout of a site or object.

It’s a good option for areas that are hard to scan or where photographic texture is a priority. We often use photogrammetry alongside LiDAR, depending on the needs of the project.

Point Cloud

A point cloud is a collection of millions of individual 3D points that represent the shape and surface of a real-world object or environment. It is the raw output from both laser scanning and photogrammetry.

Point clouds are highly accurate and are commonly used for measurement, spatial analysis, and as a starting point for creating floor plans or 3D models. While detailed, they can be difficult to interpret on their own and often need to be processed or converted into more visual formats such as mesh models or drawings.

Mesh Model

A mesh is a 3D surface created by joining up the points in a point cloud. It turns the scan data into a continuous shape using small connected triangles or polygons.

Mesh models are useful when you need a simplified version of the scan for visualisation, 3D printing, or digital reconstruction. They’re easier to work with than point clouds in many situations, but don’t always keep the same level of raw measurement accuracy.

Textured Mesh

A textured mesh is a mesh model with high-resolution photos added to the surface. This gives it a more realistic appearance, combining the shape from the scan with actual textures from the site.

We use textured meshes for things like public interpretation, 3D viewers, or virtual documentation. They’re especially useful when the visual detail is just as important as the shape itself.

BIM (Building Information Modelling)

BIM is a digital model of a building or structure that includes both its shape and useful data like materials, layouts, or service information.

Although we don’t create BIM models ourselves, the data we provide — such as point clouds and 3D models — can be used by architects or engineers as the starting point for a BIM workflow.

Georeferencing

Georeferencing is the process of assigning real-world spatial coordinates to a dataset so that it accurately aligns with geographic reference systems such as Ordnance Survey grid references or national coordinate frameworks. This ensures that scanned data fits correctly within mapping environments, planning documents, or GIS platforms.

It is an essential step when working with large or multi-phase sites, combining LiDAR and photogrammetry outputs, or aligning surveys with existing spatial data. Without proper georeferencing, measurements may be locally accurate but cannot be reliably compared, analysed, or integrated with other geospatial datasets over time