Application of number–size (N-S) fractal model for separation of mineralized zones in Dareh-Ashki gold deposit, Muteh Complex, Central Iran

The goal of this study is to separate different mineralized zones in Dareh-Ashki gold deposit located in Muteh Complex, Central Iran, by using number–size (N-S) fractal model. The N-S log–log plot shows seven geochemical populations and four Au-mineralized zones. Based on obtained results, Au thresholds are 0.17, 0.32, 6.3, and 12.6 ppm which represent weakly, moderately, highly, and extremely mineralized zones in terms of Au grades, respectively. Au values lower than 0.17 ppm illustrate wall rocks. Main mineralization stage of gold commences from 6.3 ppm in this deposit. The moderately mineralized zone with Au values between 0.32 and 6.3 ppm has occupied the biggest part of the studied deposit. However, highly (with Au values between 6.3 and 12.6 ppm) and extremely (higher than 12.6 ppm) mineralized zones have small extension. Correlation between geological model and results from N-S fractal model reveals that the gold mineralized zones specifically the moderately mineralized zone are situated in green schist units.     

Mixed mode crack propagation in low brittle rock-like materials

Mixed mode fracture is quite common in rock structures. Numerous investigators have used the Brazilian disk specimens with a central crack for investigating modes I, II, and mixed fracture toughness in brittle materials. In this study, analytical, experimental, and numerical investigations were planned and performed on Central Straight Through Crack Brazilian Disk (CSCBD) specimens. Ranking of geometrical parameters effective on the value of stress intensity factors (SIFs) of CSCBD specimens were obtained using stochastic analysis. Furthermore, experimental tests were undertaken in order to evaluate the crack propagation in rock-like material of low brittleness. Finally, numerical modeling was performed to assess the effect of crack length on the failure mode of CSCBD specimens. Analytical analyses revealed that the inclination angle of the crack with respect to the diametrical load has the most important impact on the SIFs among the geometrical parameters of CSCBD specimen. Performed experimental and numerical analyses also confirmed the effect of inclination angle and crack length and their impact on the mode of failure of the tested specimen.     

Determining proper strategies for Iran’s dimensional stone mines: a SWOT–AHP analysis

Iran has very high potential for production and export of dimension stone (rock quarried to size and shape specifications); nevertheless, in spite of growing mine production during the past decade, in many instances this potential has been overlooked. Construction, decorative, and facing stones of Iran are among the highest-quality products in the world. In this paper, Iran’s dimensional stone mines are analyzed using strengths, weaknesses, opportunities and threats (SWOT) analysis in combination with analytic hierarchy process (AHP). SWOT analysis is a tool commonly used for analyzing both the internal and external environments in order to attain a systematic approach and support for a decision situation. Conventionally, SWOT analysis is qualitative and does not quantify the effect of the factors. Consequently, it is not effective in priority setting. To overcome this limitation, SWOT analysis has been used in combination with other quantitative multi-criteria decision making methods especially the AHP. In this study, first an environment analysis was performed by an expert team familiar with these mines. In this way, the SWOT factors were identified and the subfactors which had very significant effects on the success of these mines were determined. Using the SWOT subfactors, the SWOT matrix and alternative strategies based on these subfactors were developed. Subsequently, the strategies were prioritized and the best strategies for Iran’s dimensional stone mines were determined.     

Detection of soil salinity changes and mapping land cover types based upon remotely sensed data

Soil salinity is a major environmental hazard. The global extent of primary and secondary salt affected soils is about 955 and 77 M?ha, respectively. Soil salinity tends to increase in spite of considerable effort dedicated to land reclamation. This requires careful monitoring of the soil salinity status. The objectives of this study were: (a) to evaluate the capability of thematic mapper (TM) and multispectral scanner (MSS) imagery for mapping land cover types, (b) to analyse the spectral features of sail crusts relative to bare soil and gravely soil surface conditions, and (c) to detect the soil salinity changes during the period 1975–2004 in the Ardakan area located in the central Iranian Deserts. The Landsat MSS and TM on two different dates of September 14, 1975 and September 11, 2004, respectively, were used. Due to great confusion between some classes, the TM 6 was included in the band combination. The result of the image classification based on the combination of TM bands 3, 4, 5, and 6 showed of the classification results. For multi-temporal analysis, both TM and MSS images were classified with the same method but with a different number of training classes. The TM-classified image was regrouped to make it comparable with MSS regrouped classified image. The comparison between the classified images showed about 39% of the total area had changed in 29 years. The result of this study revealed the possibility of detecting important soil salinity changes by using Landsat satellite data     

Mapping of landslide hazard zonation using GIS at Golestan watershed, northeast of Iran

Landslide hazard zonation is essential for planning future developmental activities. At the present study, after the preparation of a landslide inventory of the study area, nine factors as well as sub-data layers of factor class weights were tested for an integrated analysis of landslide hazard in the region. The produced factor maps were weighted with the analytic hierarchy process method and then classified into four classes—negligible, low, moderate, and high. The final produced map for landslide hazard zonation in Golestan watershed revealed that: (1) about 53.85 % of the basin is prone to moderate and high threats of landslides. (2) Landslide events at the Golestan watershed were strongly correlated to the slope angle of the basin. It was observed that the active landslide zones, including moderate to high landslide hazard classes, have a high correlation to slope classes over 30° (R ²?=?0.769). (3) The regions most susceptible to landslide hazard are those located south and southwest of the watershed, which included rock topples, falls, and debris landslides.     

Landslide susceptibility mapping at Vaz Watershed (Iran) using an artificial neural network model: a comparison between multilayer perceptron (MLP) and radial basic function (RBF) algorithms

Landslide susceptibility and hazard assessments are the most important steps in landslide risk mapping. The main objective of this study was to investigate and compare the results of two artificial neural network (ANN) algorithms, i.e., multilayer perceptron (MLP) and radial basic function (RBF) for spatial prediction of landslide susceptibility in Vaz Watershed, Iran. At first, landslide locations were identified by aerial photographs and field surveys, and a total of 136 landside locations were constructed from various sources. Then the landslide inventory map was randomly split into a training dataset 70 % (95 landslide locations) for training the ANN model and the remaining 30 % (41 landslides locations) was used for validation purpose. Nine landslide conditioning factors such as slope, slope aspect, altitude, land use, lithology, distance from rivers, distance from roads, distance from faults, and rainfall were constructed in geographical information system. In this study, both MLP and RBF algorithms were used in artificial neural network model. The results showed that MLP with Broyden–Fletcher–Goldfarb–Shanno learning algorithm is more efficient than RBF in landslide susceptibility mapping for the study area. Finally the landslide susceptibility maps were validated using the validation data (i.e., 30 % landslide location data that was not used during the model construction) using area under the curve (AUC) method. The success rate curve showed that the area under the curve for RBF and MLP was 0.9085 (90.85 %) and 0.9193 (91.93 %) accuracy, respectively. Similarly, the validation result showed that the area under the curve for MLP and RBF models were 0.881 (88.1 %) and 0.8724 (87.24 %), respectively. The results of this study showed that landslide susceptibility mapping in the Vaz Watershed of Iran using the ANN approach is viable and can be used for land use planning.     

Application of weights-of-evidence and certainty factor models and their comparison in landslide susceptibility mapping at Haraz watershed, Iran

The main goal of this study was to investigate the application of the weights-of-evidence and certainty factor approaches for producing landslide susceptibility maps of a landslide-prone area (Haraz) in Iran. For this purpose, the input layers of the landslide conditioning factors were prepared in the first stage. The landslide conditioning factors considered for the study area were slope gradient, slope aspect, altitude, lithology, land use, distance from streams, distance from roads, distance from faults, topographic wetness index, stream power index, stream transport index and plan curvature. For validation of the produced landslide susceptibility maps, the results of the analyses were compared with the field-verified landslide locations. Additionally, the receiver operating characteristic curves for all the landslide susceptibility models were constructed and the areas under the curves were calculated. The landslide locations were used to validate results of the landslide susceptibility maps. The verification results showed that the weights-of-evidence model (79.87%) performed better than certainty factor (72.02%) model with a standard error of 0.0663 and 0.0756, respectively. According to the results of the area under curve evaluation, the map produced by weights-of-evidence exhibits satisfactory properties.     

Vacuum solution of a quadratic red-shift based correction in f(R) gravity

In the present paper, using action derivative with respect to Ricci scalar and its expansion relative to red-shift, to the second-order and consequently without needing dark energy, the history of cosmos expansion is reconstructed in vacuum. Then, employing supernova data, free parameters of the model which are the expansion coefficients, are calculated. It will be seen that if the free parameters of the model are zero, action of general relativity, which is a boundary mode of the gravity, is found. Also the cosmic age for this model in vacuum is calculated. Finally, it is attempted to reconstruct the reference action in terms of its Taylor expansion. Thus, it will be found that the reconstructed action and their actions definitely pass the Solar system tests.     

Soil Moisture Estimation in a Vegetated Area Using Combination of AIRSAR and Landsat5-TM Images

High difference between dielectric constant of water (dielectric constant about 80) and dielectric constant of dried soil (dielectric constant about 2–3) makes Synthetic Aperture Radar (SAR) highly capable in soil moisture estimation. However, there are other factors which affect on radar backscattering coefficient. The most important parameters are vegetation cover, surface roughness and sensor parameters (frequency, polarization and incidence angle). In this paper, the importance of considering the effects of these parameters on SAR backscatter coefficients is shown by comparing different soil moisture estimation models. Moreover, an experimental soil moisture estimation model is developed. It is shown that this model can be used to estimate soil moisture under a variety of vegetation cover densities. The new developed model is based on combination of different indices derived from Landsat5-Thematic Mapper and AIRSAR images. The AIRSAR image is used for extraction of backscattering coefficient and incidence angle while TM image is used for calculation of Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Normalized Difference Water Index (NDWI) and Brightness Temperature. Then a soil moisture estimation model which is named as Hybrid model is developed based on integration of all of these parameters. The accuracies of this model are assessed in the NDVI ranges of 0–0.2, 0.2–0.4 and 0.4–0.7 by using SAR data in C band and L band frequencies and also in different polarizations of HH, HV, VV and TP. The results show that for instance in L band with HV polarization, R-square values of 0.728, 0.628 and 0.527 are obtained between ground measured soil moisture and estimated soil moisture values using the Hybrid model for NDVI ranges of 0–0.2, 0.2–0.4 and 0.4–0.7, respectively.     

Hydrothermal Alteration Mapping Using ASTER Data for Reconnaissance Porphyry Copper Mineralization in the Ahar Area, NW Iran

The Ahar area is located in East Azarbaijan province, and covers an area of about 2,500 km². Spectral mapping techniques were applied on VNIR and SWIR of ASTER data for discriminating between hydrothermal alteration zones and the identification of high potential mineralized lithological unit associated with hydrothermal porphyry copper mineralization in the Ahar. In this research to remove atmospheric and topographic effects from ASTER data, the log-residual method (LRM) was used. Four methods, Relative Band Depth Ratios (RBD), Principal Component Analysis (PCA), Minimum Noise Fraction (MNF) and matched filtering (MF), were used to processing and interpretation of remote sensing data in the study area. Results show that ASTER images provide preliminary mineralogy information and geo-referenced alteration maps at low cost and with high accuracy for reconnaissance porphyry copper mineralizations.