Hyperspectral mapping of Iranian east ophiolite m,langes using neutral network classification method

Mapping in the areas, which are near the collision zone, needs extensive and exact studies and tools because of the variety of rocks and complex structures. Hyperspectral sensor is one of the most advanced tools that can do imaging in hundreds of delicate and continuous bands in visible and infrared spectrums. Therefore, it can identify many lithologies despite spectral similarities and complications. In the present study, as one of the first hyperspectral data survey for separating ophiolite melange units in Iran, we applied the spectral-based method of neutral network classification method on hyperion images of Tabas in southeast of Iran. Based on various laboratory-field studies, the lithology of the study area can be separated into five general groups: ophiolite series, metamorphic units, Oligocene-Miocene to Quaternary volcanic units, and lime and flysch units. In order to perform an accuracy assessment of the image processing results, some locations and points were sampled. These samples were analyzed under the microscope and by electron microprobe system. Based on field-laboratory works, the accuracy of the resulting image was validated. Consequently, the neutral network method as advanced hyperspectral image processing method produced an average user accuracy coefficient of 62 % in some parts of colored m,langes. Therefore, the method based on neutral network theory for spectral classification has acceptable ability to discriminate various lithologies in the complex geological scenarios.