Classification of Hyperspectral Imagery from the Air by the Spectral Angle Mapping and Correlation Coefficient Method

Klasifikacija snimaka ima višestruku primjenu u području daljinskog istraživanja. Hiperspektralne snimke omogućuju najpreciznije spektralne karakteristike područja istraživanja. Izvršena je klasifikacija hiperspektralnih snimaka prirodnih minerala alunita, kaolinita i kalcedona u programu TNTmips. Definirane su spektralne vrijednosti pojedinih minerala te prikazana područja podudaranja uzoraka minerala sa okolnim područjima. Uporabom metoda mapiranja spektralnog kuta i koeficijenta korelacije pokazani su približno jednaki rezultati pokrivenosti minerala na područjima interesa. Preklapanjem rezultata pojedinih metoda, klasificirana područja su određena boljom preciznošću u usporedbi sa pojedinom metodom.Image classification has multiple applications within the field of remote sensing. Hyperspectral images enable the most precise spectral characteristics inside the field of research. The hyperspectral image classification of natural minerals alunite, kaolinite and chalcedony was performed with the program TNTmips. Spectral values of individual minerals were defined and the fields of matching mineral samples with the adjecent areas were displayed. By using the spectral angle mapping and the correlation coefficient methods, the mineral coverage inside the areas of interest displayed similar results. By overlapping the results of each method, the classified fields are defined with better precision in comparison to each method individually