Processing Tool Development

Based on our in-depth knowledge of lidar system technology and a strong background in signal and image processing techniques we are able to create tools that exploit advanced lidar features like return signal intensity (e.g. for surface classification), echo pulse shape and multiple return statistics (for object detection, characterization of vegetation, etc.), and fusion of lidar data with imager/thermal scanner data.

Our tools development serves to both increase our own processing productivity and to provide solutions to our customers. We have developed custom tools to detect and remove systematic errors and noise, and to enhance lidar data quality, in some cases even allowing to save flawed data to avoid reflights of large missions.

Tools for Advanced LIDAR Features

Intensity

  • Surface classification
  • Object and feature identification
  • Automatic track alignment
  • Accuracy enhancement by matching techniques with image data

Return statistics

  • Surface classification
  • Vegetation layering and density
  • Surface slope and roughness

Return pulse width

  • Surface slope and roughness
  • Improved surface modelling
  • Surface classification
  • Low-level vegetation detection

Return waveform

  • Surface slope and roughness
  • Accurate vegetation layering and density analysis
  • Vegetation classification
  • High-resolution analysis of vertical structures (e.g. transmission line infrastructure)
  • Improved building detection
  • Improved ground detection in densly vegetated areas

Tools for Filtering and Data Enhancement

Point filtering and classification

  • Development of new approaches for increasing the degree of automation of ground point detection
  • Procedures for automated classification of points into surface type classes
    • open terrain
    • vegetation
    • buildings
    • bridge structures
    • water
    • ...

Data quality enhancement

  • Detection and removal of outliers
  • Reduction of random noise
  • Development of custom noise and error compensation schemes to restore flawed data

Data Fusion

Fusion with other data sources

  • Use of LIDAR intensity data for surface classification
  • Automatic orthorectification of digital airborne and satellite imagery and scanner data using LIDAR DSMs
  • Fusion of 3D data with image data from other sources (video, multispectral scanner, aerial photos, etc.)
  • Thematic data analysis

Application-specific tools

Building and feature extraction

  • Detection of terrain features
    • Breaklines
    • Ditches
    • Land-water boundaries

  • Detection of surface features
    • Buildings
    • Infrastructure
    • Vegetation

  • Feature vectorisation and parametrisation
    • Breakline
    • Building ground plan, height, roof shape
    • Powerline post location, sag
    • Tree height, vegetation density

  • Custom filters for specific objects and features

Visualisation and Output

Visualisation

  • Elevation data as shaded relief images with or without color coding
  • Intensity on color-coded elevation
  • Perspective/oblique views
  • Orthofoto and video image draping (overlay of image and 3D data)
  • Integration of digital landscapes, DSMs and remote sensing image data
  • Conversion and integration of DSMs into architectural visualizations

Output

  • Integration of laser altimetry data and DSMs into GIS data bases
  • Design ouf data output converters
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