Feature Extraction

Over the past decade new automated data acquisition technologies have emerged.

Under the classification of “imaging sensors”, such technologies include digital aerial photography, high-resolution satellite imaging systems, space-borne and airborne interferometric synthetic aperture radar (InSAR) and airborne laser scanning (LiDAR).

Moreover, such new technologies have not been restricted to aerial and space platforms, as we are seeing broader application of terrestrial imaging and laser scanning within mainstream surveying, mapping and GIS.

These data acquisition systems produce a wealth of primary data that require extensive processing in order to generate information products.

Feature Extraction Intensive Seminar - view presentations here

Automation of the data-to-information generation process gives productivity gains, which are necessary to handle the ever-increasing volume of spatial data

The program has three themes

  1. Support for the application of new data acquisition systems for feature extraction in spatial information. This includes metric sensor modelling, calibration, sensor orientation and geopositioning and development of the necessary mathematical models and computational processes needed to generate the data products from which cartographic features are extracted.
  2. Automated feature extraction from fused data obtained with multisensor systems, the focus being upon imaging and ranging data from digital aerial and satellite imagery, multi- and hyperspectral imagers, LiDAR and space- and airborne InSAR.
  3. Developing feature extraction algorithms, tools and processes for accurate and reliable feature database building in end-user specified application domains in the areas of defence mapping, utility asset management, urban planning and modelling, natural resource management and GIS in general.