What is a Point Cloud?
A point cloud is a large set of 3D points, each with an x, y and z coordinate and often extra attributes like intensity, colour and a classification (ground, building, vegetation) — a direct sample of the surfaces a sensor saw. Point clouds are everywhere in modern survey, and this guide explains the LAS and LAZ formats, and how a cloud becomes a surface you can actually compute with.
A cloud of measured points
A point cloud is a large set of 3D points, each with an x, y and z coordinate, and often extra attributes like intensity, colour and a classification (ground, building, vegetation). It is a direct sample of the surfaces a sensor saw.
Clouds come from LiDAR, which measures points with laser pulses, or from photogrammetry, which reconstructs points from overlapping images.
LAS and LAZ
LAS is the standard file format for point clouds. LAZ is its losslessly compressed form — the same data, much smaller on disk. You can convert freely between them, and good software reads both directly.
From cloud to surface
Point clouds are rich but heavy, and most engineering results need a surface, not raw points. Classifying ground points and gridding them produces a bare-earth DTM; using all points produces a DSM; and the imagery can produce an orthophoto.
Once you have that surface, the familiar work follows: volumes, cross-sections, contours and analysis.
Frequently asked questions
What is a point cloud?
A point cloud is a large set of 3D points, each with an x, y and z coordinate, and often extra attributes like intensity, colour, and a classification (ground, building, vegetation). It is a direct sample of the surfaces a sensor saw.
Where do point clouds come from?
Point clouds come from LiDAR, which measures points using laser pulses, or from photogrammetry, which reconstructs points from overlapping images.
What is the difference between LAS and LAZ files?
LAS is the standard file format for point clouds. LAZ is its losslessly compressed variant — the same data, much smaller on disk. You can convert freely between the two, and good software reads both directly.
How does a point cloud become a usable surface?
Ground points are classified and gridded to produce a bare-earth DTM, all points can be used to produce a DSM, and imagery can be used to produce an orthophoto.
Open LAS/LAZ and build surfaces in STREAM
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