Behnam Sadeghi

Delineation of geochemical anomalies using factor analysis and multifractal modeling based on stream sediments data in Sarajeh 1:100,000 sheet, Central Iran

The aim of this study is to delineate the Cu, Au, and Pb anomalies in Sarajeh 1:100,000 sheet located in Urumieh-Dokhtar ore belt, central Iran. The analyzed elements of stream sediment samples taken in the area can be classified into six groups (factors) by factor analysis. The concentration–area and number–size multifractal inverse distance weighted models were applied for recognition of the elemental thresholds which are similar in both used multifractal models. According to the thresholds, the elemental concentration distribution for Cu, Au, and Pb were divided to three lithological classifications, namely mainly c alkaline porphyry with Cu–Au mineralization, mafic and sedimentary rocks. The results illustrate that the major anomalies of Cu, Au, Pb and related factors are mostly located around intrusions, volcanics, and along NW–SE faults.

Prospection of Au mineralization based on stream sediments and lithogeochemical data using multifractal modeling in Alut 1:100,000 sheet, NW Iran

The Alut 1:100,000 sheet is located in the Sanandaj-Sirjan structural zone, NW Iran, which contains Au-Ag (Cu) mineralization. The aim of this research is to separate geochemical anomalies using concentration-number (C-N) multifractal modeling based on stream sediments and lithogeochemical data. Results obtained from the C-N method indicated the main anomalies of Au, Ag, Cu, and As accumulated in the central and eastern parts of the area which are associated with meta-volcanic and granitic rocks. Correlation between the elemental highly intensive anomalies and geological particulars consisting of alteration zones and faults revealed that the main Au anomalies are in the central and eastern parts of the Alut 1:100,000 sheet.

Application of target detection algorithms to identification of iron oxides using ASTER images: a case study in the North of Semnan province, Iran

In recent years, satellite sensor images have been commonly used in mineral detection. These images, with different spectral and spatial resolutions, can be used in detecting minerals which have surface indicators. Due to numerous sources of uncertainties in using spectral processes for mineral explorations and atmospheric effects on the spectrum of the pixels, in this research, mineral target detection methods were selected and implemented. The implementation of this research was done using an ASTER scene from the northern area of Semnan province in Iran. There were seven iron mines in the region covered by this scene. Three of them were used as training data and four other ones were used as test data. Several target detection methods were implemented and the mean of the results of these algorithms, which embrace the results of all algorithms, was evaluated. The output of the algorithm is an image where the gray value of each pixel corresponds to the probability of similarity to the training data. Considering the fact that the probabilities’ range is between 0 and 1, after implementing the algorithms, it was concluded that the spectral angle mapper (SAM) method has the best performance with mean probability value of 0.99 for the test mines. Based upon the fact that the mean value of the algorithms was 0.87, it was proved that these methods can be very practical thanks to their high accuracy in prospection of new exploration targets which may detect new equivalent iron potentials.

Development of the iterative edge detection method applied on blurred satellite images: state of the art

Abstract. This paper aims to implement an iterative fuzzy edge detection (IFED) method on blurred satellite images. Some degradation effects such as atmospheric effects, clouds and their shadows, atmospheric aerosols, and fog remarkably decline the quality satellite images. Hence, some processes such as enhancement and edge detection in satellite images are challenging. One group of methods that can deal with these effects is fuzzy logic methods. Therefore, IFED method was applied in this work on the subimages of the Ikonos, Landsat 7, and SPOT 5 satellite images, contaminated by aforementioned effects. Such as most FED methods, IFED has two components: enhancement and edge detection. In this context, a six-step iterative method, using the if-then-else mechanism, was implemented on the images to perform fuzzy enhancement, and subsequently, edge detection was done. To evaluate the merit of the enhancement and select the best number of iterations, edge gray-value rate criterion was applied. The peak signal-to-noise ratio (PSNR) is applied for the quantitative evaluation of the IFED method. The results of IFED, in comparison with some prior edge detection methods, showed higher PSNR values and a high performance in the edge detection of the earth features in the blurred satellite images.

Capturing Hidden Geochemical Anomalies in Scarce Data by Fractal Analysis and Stochastic Modeling

Fractal/multifractal modeling is a widely used geomathematical approach to capturing different populations in geochemical mapping. The rationale of this methodology is based on empirical frequency density functions attained from global or local distributions. This approach is quite popular because of its simplicity and versatility; it accounts for the frequency and spatial distribution of geochemical data considering self-similarity across a range of scales. Using this technique for detection of geochemical anomalies in scarce data, however, is problematic and can lead to systematic bias in the characterization of the underlying populations. In this paper, an innovative technique is presented that provides good results without a priori assumptions. A simulation approach is adopted for fractal analysis by generating different possible distribution scenarios for the variable under study to reveal the underlying populations that are frequently hidden due to lack of data. The proposed technique is called the global simulated size–number method, and it is validated in a case study with two synthetic datasets and another case study with real dataset from the Ushtagan gold deposit in northeast Kazakhstan.

DERE SEDİMANI VERİLERİNE “FRAKTAL MODEL” VE “FAKTÖR ANALİZİ” UYGULANARAK CR MİNERALİZASYONUNUN TANIMLANMASI: KHOY 1:100.000 PAFTASI, KB İRAN

Fraktal yontemler, sig ve derin mineralizasyon zonlarinin sinirlarinin birbirinden daha hassas bir sekilde ayrilmasi acisindan oldukca etkili yontemler olarak kabul edilmektedir. Bu arastirmada, KB Iran’da bulunan Khoy 1:100.000 olcekli jeoloji haritasi icinde, Cr, Co ve Ni gibi elementleri acisindan umutlu olabilecek alanlari saptamak amaciyla konsantrasyon-numara (C-N) ve konsantrasyon-alan (C-A) fractal yontemler uygulanmistir. Elementler uzerinde factor analizi uygulanmis olup her iki fractal yontem, elementler ile iliskili faktorler izole edilerek calisilmistir. Ekstrem anomalilerin guncel jeolojik konumlari arastirilmis olup sonuclar karsilastirildiginda bunlarin cok yakin iliski sunduklari ve cakistiklari gozlenmistir. Sunulan model sonuclarina bakildiginda, incelenen cogu elementin, paftanin merkez ve GB kesimlerinde kaldiklari anlasilmistir. Litoloji acisindan bakildiginda ise, bu alanlar serpantinitin harzburjit ve dunit gibi ultramafik kesimlerine karsilik gelmekte olup ayni zamanda Cr mineralizasyonu acisindan yuksek olasilikli alanlari gostermektedir. Ulasilan sonuclar ayni zamanda faktor analizi ile dogrulanmistir. Bu ise, bu elementlerin faktor akumulasyonunun her bir elementinki ile tam olarak ayni oldugu anlamina gelmektedir.