R Khavari
Abstract
Stream gradients of rivers bedrock in the Khuzestan province were calculated, using GIS and 50-m digital elevation models to discuss the distribution of knick zones. Gradients were classified into local and regional types based on the measurement lengths of stream gradients for 474 rivers having at least ...
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Stream gradients of rivers bedrock in the Khuzestan province were calculated, using GIS and 50-m digital elevation models to discuss the distribution of knick zones. Gradients were classified into local and regional types based on the measurement lengths of stream gradients for 474 rivers having at least 10-km long in the study area. The transition rate from the local to regional gradients, i.e. the decreasing rate of gradient with increasing measurement length, is then obtained as the indicator of relative steepness of a river segment, which permits the objective identification of fluvial knick zones. Knick zones occur widely in the study area. The knick zones with large relative steepness near the outlets of large watersheds are related to the tectonic activity and most of them are actually close to the known locations of the active faults. The most important active faults in the study area are Mafaron, Agha-jari, Andakan, Lahbari, Mordehfel, Maron, North Behbahan Dezfol and Mishdagh. Knick zones occur along upstream steep reaches can be related to active hydraulic and erosional conditions regardless of geological or tectonic conditions. Effects of rock properties on the frequency and form of knick zones are observed, but they seem to play only a subordinate role. This study concludes that tectonics and geology are more important than topographic and hydraulic conditions in knick zone existence.
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.
