Hyperspectral images are widely employed for geological mapping because of their high spectral resolution. In this article, we develop the mixture-tuned matched filtering (MTMF) method, which can provide highly accurate mapping using the minimum ground-based data. This method is applied
in the Malayer region of western Iran, which is composed of various lithological units. MTMF and minimum noise fraction (MNF) methods were applied to a Thematic Mapper 5 (TM5) image, and minimum number of training data based on field observation were used to produce a suitable false-colour
image in which locations of lithological units were given. Finally, classification of six desired lithological units was done by the maximum likelihood classification (MLC) method. Results of lithological mapping show that although minimum ground-based data were used, the accuracy of classification
is 82.3%. In addition, evaluation of the above-mentioned false-colour image reveals that the algorithm presented enhances the separability of units in the image by 7.3%, which can partially compensate for the low spectral resolution of the image used.
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Document Type: Research Article
Affiliations:1: Faculty of Cartography, University of Tehran, Tehran, Iran 2: Geology Department, Payam-e-Noor University, Tehran, 19395-4697, Iran 3: Surveying Engineering Department, College of Engineering, University of Tehran, Tehran, Iran 4: Department of Surveying and Geomatics Engineering, College of Engineering, University of Tehran, Tehran, Iran