Comparaison de differentes methodes de traitement par analyses en composantes principales des donnees Thematic Mapper de LANDSAT-5 appliquees al'inventaire forets mediterranneennes du sud de la France

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Abstract
The existence of remotely sensed data with high spatial resolution, like the ones produced by the Thematic Mapper of LANDSAT, set the problem of the reduction of the number of spectral dimensions to be analysed. The work presented hereby is in this context and aims to compare the performances of the supervized classification applied to the perception of forested and sub-forested mediterranean ecosystems processed with: original TM data selected only under spectral consideration; components factors provided by a classical Principal Component Analysis (PCA); components factors provided by a selective Principal Component Analysis (PCA). The analysis of the results shows that the classification done using the three axes extracted by a classical Principal Component Analysis of the six Thematic Mapper bands gives better results than all the other combinations (original data or data provided by selective PCA). On the other hand, and for all the classifications processed, it appears that the performances are excellent (near 90 per cent) for units representing stable systems, climatic or definitely degraded. At the opposite end, performances are quite good (near 60 per cent) for the evolutive systems (in regression or progression).

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