Additionally, change analysis and photogrammetry techniques allow one to establish slide movement patterns and to quantify the magnitude of movements. Terrain models can be made in areas difficult to access using air and satellite imagery.  Such models are the critical basis for computations of slide volume, velocity, run-out distance, and, eventually, total risk. 

High and very high resolution optical satellite photos have many different applications, including change detection and visual analysis. Different surface cover types can be distinguished using texture, while spectral information from other bands (infrared, thermal) can be used to delineate areas of interest further. Geometric patterns can also be used to automatically extract landscape elements. Finally, these images are helpful for obtaining a general overview of natural disaster areas, including forest fires, floods, and damage resulting from hurricanes, tornados, and similar climatic hazards. 

NGI's work with optical remote sensing in the last few years has been primarily related to snow avalanche research, through initiatives such as aval-RS, ASAM, AAF and SeFaS.

Through the aval-RS and ASAM projects, NGI has made use of very high resolution satellite imagery to automatically detect avalanche movements. These areas are often difficult to physically access, and pose a great risk in Norway, the Alps, and most other mountain ranges in the world. Finding avalanches in this way allows one to build a database with relevant statistics regarding frequency of their occurrence, which together with meteorological information, can be used to evaluate advanced warning systems.

NGI Optical remote sensing

Left panel: avalanche areas mapped with the help of an automated algorithm. Right panel: avalanche areas as captured by the WorldView-1 satellite. (Satellite image: Copyright © DigitalGlobe/WorldView-1)

NGI has also surveyed landslide zones in Pakistan with the help of optical satellite images from ASTER and change detection techniques. In this case, slide zones were detected by calculating various vegetation-, snow-, and water-indices from the different bands in the image data and by filtering out urban areas based on slope angle of the terrain model. The survey was conducted for Pakistani authorities, and was based on analysis of satellite imagery from ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer).

Current R&D at NGI

  • Automatic pattern recognition of snow avalanche deposits
  • Mapping and quantification of shoreline regression using satellite imagery, terrain models, and sea-level modelling in Vietnam
  • SENSUM - Use of satellite data for landslide/avalanche risk and vulnerability studies in data-poor areas
  • Tsunami modelling using satellite imagery, terrain modelling, and sea-level modelling
  • Orthophoto analysis in Flåmsdalen to detect slope movements


TerraNor (eCognition, PCI Geomatica)
Geodata (ArcGIS-software)

Tjenester innen metoden

Overview mapping
Identification of hazard "hot-spots"
Cost-effective planning of onsite investigations
Pattern recognition
Change analysis