R Ahmadi Rohany; M.H Karimpour; B Rahimi; A Malakzadeh Shafaroudi
Abstract
The studied area is located in east of BajestanTownship, KhorasanRazaviProvince and this region is a part of the Lut Block. Granite is the most important rock in this area with covering approximately 70km2. Processing of satellite data in this area was done by using of SPOT, ASTER and Landsat ETM+ data. ...
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The studied area is located in east of BajestanTownship, KhorasanRazaviProvince and this region is a part of the Lut Block. Granite is the most important rock in this area with covering approximately 70km2. Processing of satellite data in this area was done by using of SPOT, ASTER and Landsat ETM+ data. SPOT images processing and using PCA methods (standard and selective) on the ETM+ data show this intrusive body doesn't have an equal chemical composition. The central part of the intrusive body has distinctive from margin and it seems that the central part have more mafic mineral. For enhancing linear structure, high pass, directional, threshold and sobel filters were applied separately and compositional on the SPOT data. By using these filters linear structures became completely obvious and were vectorized digitally. The most of them show northwestern-southeastern trend. ASTER data processing by spectral angle mapper (SAM), band ratio and band composition methods enhanced epidote, sericite, hematite, argilic and silicified alterations. Processing and Interpretation of airborne geophysical data (potassium, thorium, uranium and total magnetic intensity), which collected by airplane show the amounts of these triple elements (K,U,Th) are high and in vice versa Total Magnetic Intensity data (TMI) is low in this granite. Separating geological boundaries and enhancing major faults are other results from processing of geophysics data. Merging all of the data consist of: satellite and geophysics data processing and field research indicate alteration zones have relation to linear structures in this area. This research specifies the most probability of mineralization presence in this area so that Fe and Cu mineralization conform to epidotic-chloritic and argilic alterations. Introducing favorable area can help us to concentrate exploration activities and next researches in this area and prevent wasting money and time.
F. Masoumi; H. Ranjbar
Abstract
The study area covers the northern half of the Baft 1/100000 geological map in Dehaj-Sarduiyeh volcanic-sedimentary and ophiolitic belts. The aim of this research was application of multispectral ASTER and ETM+ data for determining the altered areas by using different image processing techniques. In ...
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The study area covers the northern half of the Baft 1/100000 geological map in Dehaj-Sarduiyeh volcanic-sedimentary and ophiolitic belts. The aim of this research was application of multispectral ASTER and ETM+ data for determining the altered areas by using different image processing techniques. In order to separate altered zones, false color composite of the ratios was applied on ASTER data that separated propylitic and phyllic/argillic altered zones. Separation of carbonate areas from the altered areas was achieved by making false color composite ratios. Another method for separation of carbonate areas from the altered zone was by applying principal component analysis (PCA) on short wave bands of ASTER data. A color composite of PC2, PC3, -PC4 in red, green and blue respectively was useful for separating carbonate from altered areas. Spectral Angle mapper method was also used for recognizing and mapping the minerals such as muscovite, chlorite, kaolinite, calcite and epidote in altered zones. Sampling from the altered areas and their analysis showed that this method could be used for recognizing the minerals in the altered areas, if they have enough spatial extent.
S. M. Masoudi; F. Fereidoni; & A. A. Matkan
Abstract
In this study, for the first time, Pumices around Damavand Mountain is studied by IRS-1C, Aster and ETM+ images. For this purpose at first, all images are preprocessed. It means geometric corrections and registering images together and with topography maps (1:25000) are done. Then atmospheric corrections, ...
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In this study, for the first time, Pumices around Damavand Mountain is studied by IRS-1C, Aster and ETM+ images. For this purpose at first, all images are preprocessed. It means geometric corrections and registering images together and with topography maps (1:25000) are done. Then atmospheric corrections, calibration of radiance and reflectance and topographic correction with Minneart method are done too. Preprocessing, some techniques like PCA, IHS, OIF, FCC and SAM have been done. Pan image of IRS-1C satellite for data fusion in visible and near infrared of Aster at visual interpretation and recognizing of roads and mines is better than ETM images. After data preprocessing, some techniques like PCA, IHS, OIF, FCC and SAM have been done. Pan image of IRS-1C satellite for data fusion in visible and near infrared of Aster at visual interpretation and recognizing of roads and mines is better than ETM images. IHS and PCA methods equally have separated clearly Pumice mines and trachyandesites without vegetations and soils covers. With respect to VNIR of Aster has more intensity than other spectral areas. Also because of high topographic changes and pampas vegetation, visible bands and Very Near Infrared (VNIR) of Aster aren't too useful. These spectral areas are caused mixing classes together, especially limestones and pumice. Totally for most of stones and different ores, spectral area of Short Wave Infrared (SWIR) of Aster has the best ability. For categorizing and extracting pumices potential layers from images, sampling is done on pixel or pixels that contain pumice mines. Because of less expansion of mines, samples are picked up on just one pixel or in maximum case ten pixels. According to that limitation, Spectral Angle Method (SAM) technique has more ability than the other methods. Use of DEM for separation flat or low dip lands whereas are placed for Pumices in northern, eastern and some southern parts of studied area is effective, but any worthwhile tracks of pumice weren’t found in south-west of mountain. Finally mining hopeful areas in cast of mining potential map is prepared. By calculating the overlay of effective geology structure layer with pumice mines areas layer, which is extracted from PAN image, the amount of overlay is calculated ninety three percent.
