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Video: What is a Point Cloud and How Does it Relate to Photogrammetry?

Maybe it’s time to ask that pointed question: What is a point cloud?

The first thing to know is that point clouds are born of data – lots and lots of data, better known as a dataset. 

Each point in a dataset represents a set of X, Y and Z geometric coordinates and an intensity value, which records the strength of the return signal based on surface reflectivity. When combined, these points form a point cloud, a collection of data points in space that represent a 3D shape or object. Point clouds also can be colorized automatically for more realistic visualization.

Purposes for point clouds

So, what does one do with a point cloud? 

So much. Point clouds are used for many purposes, including visualization, animation, rendering, and CAD models. In geospatial workflows, point clouds are used for deliverables including topographic and bathymetric maps, digital elevation models, digital terrain models, 3D CAD and Building Information Models (BIM), point cloud, and imagery viewers, and animation and virtual reality.

Accurate geospatial data is invaluable for:

  • monitoring and validating new construction,
  • reconstruction or renovation of buildings, plants, and civil infrastructure,
  • forensics investigations of crime scenes so they are undisturbed and evidence is permissible in court,
  • accident recreation that is safe and fast to reduce road closures,
  • preserving and restoring cultural heritage sites for generations to come, and,
  • countless more.

So, in the most basic sense, point clouds are digital representations of the real world, and the data is truly incomparable. 

point cloud 2

Capturing data points

The data that form point clouds are collected in a number of ways, including cameras in total stations, terrestrial and airborne laser scanners, unmanned aerial systems (UAS), mobile mapping systems, snapshot images, and videos from hand-held controllers, and smartphones and computer-aided design (CAD) programs that generate surface and structural models.

Analyzing point cloud data

Point clouds can be large and may exceed hundreds of gigabytes in size. This is where powerful software solutions are necessary for efficient point cloud processing, analysis, and data export. 

Secure storage and data sharing are also essential for successful project collaboration. This is where cloud-based solutions make a difference, providing easy access to visualize and interact with the point cloud in a productive way.

Product examples:

To learn more about point clouds, watch our video above, part of our Geospatial 101 video series.