hydrogeology
Mahshid Moavi; heeva elmizadeh
Abstract
From the point of view of fractal behaviors, the property of replication over time creates patterns in the bed of the basin that show unique performance during the maturity of a basin, depending on the reproductive characteristics and how they change. For this reason, in this study, investigates the ...
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From the point of view of fractal behaviors, the property of replication over time creates patterns in the bed of the basin that show unique performance during the maturity of a basin, depending on the reproductive characteristics and how they change. For this reason, in this study, investigates the bifurcations of drainage networks of the Ramhormoz basin using Tokunaga model and fractal dimension correlation, has been done. Ramhormoz River is one of the sub-basins of Jarahi basin located in the southwest of the country. This river originates from 50 km southeast of Izeh and flows to the southwest. In this study, river networks were extracted from Arc GIS software, and then input data were entered into the software to calculate two-dimensional fractal numbers using correlation function. In this regard, first Ramhormoz basin is divided into eastern and western parts and then using the Tokonaga method, irregular network and curve of Ramhormoz river are drawn in a regular, geometric and corresponding tree form. According to the length of the streams, the fractal dimension was calculated for both parts of the Ramhormoz basin. The fractal dimension of the correlation between the Ramhormoz basin and its eastern and western parts has been calculated between (1.42 to 1.68) with a high correlation coefficient, which indicates a relatively high turbulent behavior of the basin and its parts. The calculated fractal dimension represents the average bifurcation ratio and the short time to reach a constant flow.
Geomorphology
heeva elmizadeh; Hadi Mahdipour
Abstract
The purpose of this research is the automatic recognition of morphic patterns of drainage network in the center of Qeshm Island using High Resolution Panchromatic Remotely Sensed (HR-PRS) and fuzzy clustering algorithms. It also investigates the efficiency of these methods in the GeoEye-1 satellite imagery ...
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The purpose of this research is the automatic recognition of morphic patterns of drainage network in the center of Qeshm Island using High Resolution Panchromatic Remotely Sensed (HR-PRS) and fuzzy clustering algorithms. It also investigates the efficiency of these methods in the GeoEye-1 satellite imagery segmentation of the study area in order to detect geomorphic features in areas with cloud and shadow coverage. In this regard, fuzzy segmentation of HR-PRS panchromatic images of the study area, after radiometric and geometric preprocessing using FWS, MSA, IDF and CFM algorithms, was performed in MATLAB software. Finally, the studied fuzzy clustering algorithms with fuzzy parameters are applied to the input HR-PRS images and the results are discussed. The results show that the Classical Fusion Method and FCM (CFM) clustering algorithm has the best performance in the field of fuzzy segmentation and detection of the studied indices. . As a result, the image borders are well defined. The reason for this is the use of fuzzy numbers as well as efficient clustering methods in this method. These results also show that remote sensing technology, by providing multi-time images, can be a very good basis for monitoring and detecting environmental changes, detecting effects and accurately extracting information from images. Also, the use of clustering algorithms and fuzzy features is a suitable and optimal method for integrating HR-PRS satellite image information from a geographical area with the aim of segmentation.
