Evaluation of Crosta, SAM (spectral Angle Mapper) and MTMF Methods for Recognizing Sedimentary Alteration Zones Using ASTER Data

Remote sensing technology has become one of the most efficient tools in geological explorations due to exploiting a broad spatial coverage along with a wide range of spectral resolution. Hence, it has been used widely for geological objects, such as identification and extraction of alteration zones during the recent decades. This research aimed to recognize alteration zones using shortwave infrared radiations of ASTER data and methods of spectral analysis including Crosta, spectral angle mapper (SAM) and mixture tuned matched filtering (MTMF) techniques. To implement the research goal, Siah Kooh area in Kerman Province of Iran was defined as a case study. Then, argillic, sericite (phyllic) and propylitic alteration zones were recognized via the proposed approach. To compare the obtained results with ground control samples for error estimation, Kappa index was used. Error evaluating of methods show that combined approach of MTMF with Kappa index of 64.62 and the total accuracy of 97.12 is the most efficient method to recognize and explore the alteration zones. MTMF method as an integrated approach shows the compliance with field samples and can be used as a suitable method to recognize and map the altered sedimentary zones.