Abstract Over the past four years, CNES has been engaged in a major programme focusing on the development of SPOT Operational Application Projects. With a total of sixty projects now complete, we can draw a number of meaningful conclusions and identify a number of objectives to be satisfied by advanced remote sensing methodology. One of the main conclusions points to the importance of human vision in studies on natural complex space imagery. This being so, visual recognition must be one of the main phases of the “Pilot Project for the Application of Remote Sensing to Agricultural Statistics”: only human experts have the ability to make a meaningful analysis of Spot TM imagery. Non-expert operators will not be able to manage the subsequent rational production phase alone. The first part of this paper describes an approach to the formalization and modelling of expert know-how based on the use of artificial intelligence. The second part puts forward a cooperative operator/computer system based on a cognitive structure. Our proposal comprises 1) a specific knowledge base, 2) an ergonomic interface associated with functional software that is based on automatic image enhancement coupled with perception support functions.


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    Titel :

    Artificial intelligence approach for spot application project system design


    Beteiligte:
    Lefevre, M.J. (Autor:in) / Fisse, G. (Autor:in) / Martin, E. (Autor:in) / de Boissezon, H. (Autor:in) / Galaup, M. (Autor:in)

    Erschienen in:

    Advances in Space Research ; 13 , 11 ; 95-102


    Erscheinungsdatum :

    1993-01-01


    Format / Umfang :

    8 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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