Fly-throught presentation of Helsinki University of Technology

This fly-through presentation displays the area of Helsinki University of Technology. The mission of the survey area (around 3 square kilometres) contains 15 million airborne laser points and around 3000 raw digital images. For further information about the survey, please look Quality of Laser Scanning, Helsinki University and Building Vectorization from Presentations -page in TerraScan.

• The pixel size of the true-ortho images on the ground 5 cm.
• Average Xy- accuracy of true-ortho images 7 cm.
• Average Z- accuracy of laser points 7 cm.
• Xyz-accuracy of building roof edge vectors 10 - 20 cm.

• Reading-in laser points: co-ordinate transformations (TerraScan)
• Checking and fixing systematic orientation errors of airborne data (TerraScan & TerraMatch)
• Removing extra laser data points on areas where multiple flight lines overlap (TerraScan)
• Adjusting the height of points according to geoid surface (TerraScan)
• Classifying laser points into different points classes such as ground, low vegetation, high vegetation (TerraScan)
• Processing raw images: solving camera parameters (TerraPhoto)
• Detecting building roof vector edges by using raw digital images and laser points, extracting roof colour from images, applying roof vectors to create the building model (TerraScan & TerraPhoto)
• Outputting selected ground points into TerraModeler for terrain modelling (TerraScan & TerraModeler)
• Producing true-ortho mosaic images to a model of ground and vector roofs (TerraModeler)
• Draping high resolution (1 pixel = 5 cm on the ground) along the TIN (TerraModeler)
• Detecting trees from high vegetation points and displaying them as RPC-cells^[1]

• One square kilometre within one week / one professional user

1:

New under MicroStation V8!
With TerraModeler and TerraPhoto (or TerraPhoto Viewer) you can now render high-resolution ortho images draped along a TIN and a large number of RPC-cells (www.archvision.com). Please query the cells from Terrasolid too.