LINEAR AND CORRELATION-ANALYSIS FOR COMPUTERIZED IDENTIFICATION OF CATEGORIES IN LANDSAT IMAGES

A major source of quantitative data, which contains information that c an be used in the classification of land covers, is the Landsat series of low orbiting spacecrafts, which began in 1972 with Landsat-l. The later versions of this series, starting with Landsat-4 and -5 are equi pped with Thematic Mapper (TM) sensor systems, which generate a vector for different intensity responses, of each pixel, in seven light and infrared spectral bands. With knowledge of different spectral response s of land covers it is possible to identify categories when analysing the vector data formats. This paper introduces a computerized procedur e which is believed to be effective in identification of land covers. The method is particularly applicable to the Thematic Mapper system. I t combines the linear analysis with the correlation procedures in spec ific formats, using a small number of reference identifiable categorie s in order to aggregate and pin-point the pixel contents (with small p robability of error). Fine identification of categories (such as the s eparation of corn or wheat in the vegetation covers) is the subject of further promising applicability using this described computerized tec hnique.