Introduction
LiDAR is changing how we model our world in 3D, bringing with it new data transformation challenges and huge data volumes. For a high-level overview of how FME can help you with LiDAR, see our website.Content Overview
- LiDAR Terminology
- Tutorials
- Format Documentation
- Top Questions and Answers
- Additional Resources
- Troubleshooting
- Known Issues
- Support
LiDAR Terminology
LiDAR: stands for “Light Detection and Ranging”. This remote sensing technology can be mounted to aerial vehicles to send laser pulses to the Earth’s surface and once the laser has returned to the sensor it records the data returned. A LiDAR system usually comprises of a laser, a scanner, a GPS receiver, an inertial measurement unit, and an onboard computer.Point Cloud: commonly the product of a LiDAR system, it is a collection of points useful for storing large amounts of data. Each point in the point cloud can hold information, called components, which contains a value that describes the point. Components may include X, Y, and Z coordinates as well as information about the intensity, color, time, and many more not listed here.
Returns: when a laser pulse bounces off an object it is processed to determine what it bounced off of. I.e. bare earth, trees, cars, buildings. These are called returns. Up to five returns can be captured per laser pulse.
Classification: returns can be classified to define the type of object that has reflected the laser pulse. The American Society for Photogrammetry and Remote Sensing has developed a set of standard classifications for LiDAR-derived data.
LAS: a common LiDAR Data Exchange Format that contains LiDAR point records. Is used for the interchange of 3-dimensional point cloud data. It has less volume and is more easily transferred than the ASCII format.
Tutorials
Getting Started Articles
Getting Started with Point Clouds- Viewing and Inspecting Point Clouds
- Reading Point Clouds
- Writing Point Clouds
- Thinning and Combining Point Clouds
- Using the PointCloudFilter
- Removing Noise in Point Clouds
Intermediate Articles
Tutorial: Point Cloud Transformations- Point Cloud to 3D Terrain Model with Buildings
- Creating Point Clouds from 3D Models or Raster Data
- Using the PointCloudFilter
- Creating Boundary and Point Features from a Point Cloud
- Using the PointCloudCoercer to Convert Point Clouds
Transformers to use with Point Clouds
Converting Point Clouds to Surface Models Using the PointCloudLASClassifier
Creating Rasters and DEMs from Point Clouds
Clipping and Tiling Point Cloud Data
LiDAR and Coordinate Systems
Advanced Articles
Before completing the following articles be sure to work through the Getting Started Articles first.Using LiDAR Waveform Attributes in FME
Point Clouds for Profiling and Slicing
Volume Measurements with the VolumeCalculator
Format Documentation
ASPRS LiDAR Data Exchange Format (LAS) Reader/WriterPoint Cloud XYZ Reader/Writer
Point Cloud Data Reader/Writer
Space Delimited XYZ Reader
Cesium 3D Point Cloud Reader/Writer
CARIS Spatial Archive (CSAR) Point Cloud Reader/Writer
Top Questions and Answers
Generate simple trees from Point Cloud (LIDAR)Question regarding thinning out point clouds
Additional Resources
Blogs:
Think like a point cloud: Tips for effective data processingTop 4 LiDAR and Point Cloud Processing Workflows
Presentations:
Wood vs Wings [FME World Tour 2020]Templates:
LAS to PDF 3D (DEM and TIN)Point Cloud XYZ to DEM
PXT Point Cloud Reader
Videos:
How to generate DEMs and HIllshades from LiDAR files [4:36]LiDAR Processing: How to thin, combine, and convert point cloud data [3:08]
Webinars:
5 Ways to Improve Your LiDAR Workflows [40:20]Troubleshooting
Oracle Spatial Point Cloud TroubleshootingKnown Issues
For a list of Known Issues, see the following articles: 2021.x, 2020.x, 2019.x, 2018.x, 2017.x
Support
Can’t find what you are looking for? Search our Community for a related question or post your question in our Forums or contact Support.
Comments
0 comments
Please sign in to leave a comment.