EU 2016 - Transforming Rasters & Point Clouds
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This document discusses transforming rasters and point clouds in FME 2016.1. It introduces new capabilities like support for Autodesk ReCap and Cesium point clouds. It also describes tools for integrating third-party software like LAStools and ImageMagick. Examples are provided on using these tools to create digital terrain and surface models from point clouds. Advanced techniques for large-scale viewshed analysis with point clouds handling billions of points are also covered.
EU 2016 - Transforming Rasters & Point Clouds
- 1. Transforming Rasters & Point Clouds
- 2. Agenda • Point Clouds and Rasters in FME • New in FME 2016.1 • Do more with third-party tool integrations • LAStools • ImageMagick • Example point cloud to raster transformation • Advanced transformations for big data problems • Viewshed Analysis with point clouds
- 5. New in FME 2016.1 • Autodesk ReCap • Cesium 3D Point Clouds • Sentinel 1 and 2
- 6. Third-Party Tool Integrations Make even more with LAStools and ImageMagick.
- 7. Custom Transformers LAStools wrappers • LAStools.lasground • LAStools.lasheight • LAStools.lasnoise • LAStools.lasclassify • LAStools.lasgrid • LAStools.laspublish ImageMagick wrappers • SVGReader • AnimatedGIFWriter Article & downloads: fme.ly/3rdparty
- 11. Demo: Creating a Fancy Animated GIF
- 12. Example point cloud to raster transformation Create a Digital Terrain Model (DTM) and Digital Surface Model (DSM) from a point cloud.
- 13. Merge component values from one point cloud to another. Sort a point cloud by the values of components.
- 15. Advanced Transformations Using point cloud power for Viewshed Analysis.
- 16. Viewshed Analysis ● Goal: Identify which land parcels have a view of the water ● Expressing a big data problem as a point cloud made the impossible possible ● Millions of parcels and lines of sight = 17 billion points ○ Point clouds can handle this volume! ● Test if the DEM intersects with the line-of-sight points
- 18. ● FME is extremely efficient when handling point clouds and rasters. ● Many powerful transformers and custom transformers are available. ● Try using point clouds for your big data problems.