A new signature extension method for use with LANDSAT data has been developed. The MASC (Multiplicative and Additive Signature Correction) algorithm uses an unsupervised clustering routine to gain relative information from two data sets. This information is then used to map the signatures derived from one data set onto the other data set. The MASC algorithm can be totally automated, thus making it suitable for use in large area crop inventories.
This signature extension method has been tested an agricultural LANDSAT data. The results of field center pixel classification using MASC-extended signatures have been compared with classification results using untransformed signatures. In all three data set pairs the MASC algorithm yielded very goad results.
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