Friday, April 6, 2012

Point Classification

Baker's latest article for LiDAR News was published last week.  The article, Mobile LiDAR Point Classification, discusses the advantages to classifying features of similar type into groups. The grouping of features into classes provides the ability to isolate, remove or exploit smaller sets of information.  Due to the extensive detail and volume of data provided by Mobile LiDAR, point classification is incredibly useful for downstream applications.

The image above, presented in the article, shows classified features in an urban environment.  Street signs, vegetation, buildings, roads and other information are isolated into user defined classes.
Extents of tree canopies, outlines of building footprints, curbing and overhead wires are clearly depicted in the image above.  Ground points have been removed for clarity.
An elevation of a parking garage with DTM surface shows the undulating terrain.
If you have a recommendation for a future article, please leave a comment. 


Thank you to William for helping with content and images for this and past articles.  And, as always, thanks to Aaron for continued support, proofing and guidance.

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What is Mobile LiDAR?

Mobile LiDAR (Light Detection and Ranging) systems are comprised of vehicle-mounted lasers, cameras and GPS/INS navigation systems to capture highly-detailed and accurate three-dimensional (3D) topographic information for surveying and engineering applications. Michael Baker International became an early adopter of Mobile LiDAR technology by acquiring our first system in 2009, with further expansions in 2014 and 2015 that increased our fleet to four (4) Optech Lynx SG1 Mobile LiDAR systems. Over that period our systems have completed more than 300 projects throughout 29 different U.S. States (and multiple countries), and encompassing hundreds of thousands of miles. Our project portfolio includes applications in roadway design, 3D modeling, railroad corridors, signaled intersections, utility infrastructure, asset management, pavement condition assessment and airport infrastructure.