Towards an automatic interpretation and knowledge based search of satellite images in databases

  • Authors:
  • M. Cantón;J. A. Torres;F. Guindos;M. Peralta

  • Affiliations:
  • Departamento de Lenguajes y Computación, Universidad de Almería, 04120 Almería, Spain;Departamento de Lenguajes y Computación, Universidad de Almería, 04120 Almería, Spain;Departamento de Lenguajes y Computación, Universidad de Almería, 04120 Almería, Spain;Departamento de Lenguajes y Computación, Universidad de Almería, 04120 Almería, Spain

  • Venue:
  • Systems Analysis Modelling Simulation - Special issue: Intelligent systems, models and databases for environmental research
  • Year:
  • 2003

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Abstract

This paper shows a prototype automatic interpretation system for ocean AVHRR (Advanced Very High Resolution Radiometer) satellite images. It is built on a three-level knowledge model (pixel, regional and domain semantic problem levels) and uses several connectionist computational approaches. First artificial neural net models (to the pixel level) were used for basic preprocessing tasks such as cloud masking. Next, a new connectionist technique using input vectors with nonnumerical regional marine features has also been developed and used in the identification phase. The paper shows some results of oceanic structure identification tasks (wakes, upwellings and eddies) in infrared images of the NW African coast and Canary Islands. These results illustrate a procedure for improving automatic oceanic interpretation of satellite images.