Multivariate statistical approach to identify metal contamination sources in agricultural soils around Pb–Zn mining area,Isfahan province,Iran     

Mohsen Nekoeinia  Reza Mohajer  Mohammad Hassan Salehi  Omran Moradlou 《Environmental Earth Sciences》2016,75(9):760

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A hybrid computational intelligence method for predicting dew point temperature     

Mohsen Amirmojahedi  Kasra Mohammadi  Shahaboddin Shamshirband  Amir Seyed Danesh  Ali Mostafaeipour  Amirrudin Kamsin 《Environmental Earth Sciences》2016,75(5):415

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Database extension for digital soil mapping using artificial neural networks     

Mohsen Bagheri Bodaghabadi  José A. Martínez-Casasnovas  I. Esfandiarpour Borujeni  M. H. Salehi  J. Mohammadi  N. Toomanian 《Arabian Journal of Geosciences》2016,9(18):701

Cost and time are the two most important factors conditioning soil surveys. Since these surveys provide basic information for modelling and management activities, new methods are needed to speed the soil-mapping process with limited input data. In this study, the polypedon concept was used to extend the spatial representation of sampled pedons (point data) in order to train artificial neural networks (ANNs) for digital soil mapping (DSM). The input database contained 97 soil profiles belonging to 7 different soil series and 15 digital elevation model (DEM) attributes. Pedons were represented in raster format as one-cell areas. The corresponding polypedons were then spatially represented by neighbouring raster cells (e.g. 2 × 2, … up to 6 × 6 cells). The primary database contained 97 pedons (97 cells) that were extended up to 3492 cells (in the case of 6 × 6-cell regions). This approach employed test and validation areas to calculate the respective accuracies of data interpolation and extrapolation. The results showed increased accuracies in training and interpolation (test area) but a poor level of accuracy in the extrapolation process (validation area). However, the overall precision of all predictions increased considerably. Using only topographic attributes for extrapolation was not sufficient to obtain an accurate soil map. To improve prediction, other soil-forming factors, such as landforms and/or geology, should also be considered as input data in the ANN. The proposed method could help to improve existing soil maps by using DSM results in areas with limited soil data and to save time and money in soil survey work.  相似文献   

Erratum to: Numerical modeling of flow due to consolidation of mine waste tailings     

Mojtaba Nosrati  Emad Ghazavi Baghini  Mohammad Mohsen Toufigh 《Arabian Journal of Geosciences》2016,9(7):495

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Extent of diagenetic transformations in severely altered biogenic silica deposits from Tunisia: new insights from mineralogy and geochemistry     

Mohsen Henchiri  Nabil Fattah 《Arabian Journal of Geosciences》2014,7(3):1179-1186

Sedimentary biogenic silica from Redeyef in Gafsa basin (southern Tunisia) was analysed for its ²⁹Si and ²⁷Al magic angle spinning nuclear magnetic resonance (MAS NMR) spectra and complemented by X-ray diffraction and SEM observations. The ²⁹Si MAS NMR spectrum is characterized by the abundance of hydroxylated silicon, displayed in resonance intensities and reflects a clear tendency towards dissolution of diatomaceous amorphous silica and the occurrence of the hydrated silica, which is the main component that ensures the diagenetic transition via the mechanism of dissolution–precipitation to other more crystalline silica phases, after the lost of its hydroxyls groups (water) by heating (burial). ²⁷Al MAS NMR reveals two coordinations of Al; the octahedrally coordinated Al suggests the presence of clay relics trapped during crystal growth or a microcrystalline zeolite (clinoptilolite detected by SEM observations), while the tetrahedrally coordinated Al suggests the presence of minor quantities of minerals with tetrahedral Al, such as an Al-rich fluid and/or minerals such as feldspars.  相似文献   

First microbialites associated to organic-rich facies of the Oceanic Anoxic Event 2 (Northern Tunisia,Cenomanian–Turonian transition)     

Mohsen Layeb  Moez Ben Fadhel  Yosra Layeb-Tounsi  Mohamed Ben Youssef 《Arabian Journal of Geosciences》2014,7(8):3349-3363

From northern Tunisia, small-scale well-preserved microbialites, contemporaneous to the global oceanic anoxic event 2 (OAE 2) are first reported on the southern Tethyan Margin. These microbialites are encased within the pelagic organic-rich black shales of the Bahloul Formation (Cenomanian–Turonian transition). Biostratigraphic, petrographic, and geochemical investigations carried out to constrain their biogenicity and genesis character led to consider them as thrombolites and stromatolites occurring in lenticular bioherms/biostromes and columnar bodies co-relatable to the global ‘filament event’ of the authors, close to the base of the Watinoceras ammonite zone. Abundant clotted micrite, cyanobacterial filaments, and algal tissues point to the key process of microbial carbonate precipitation and to a major role played by microbes in the stabilisation and subsequent lithification, which in turn favoured the preservation of the original structure of the microbialites. These microbially induced carbonate formations are considered as favoured by chemosynthetic fauna of bivalve molluscs and lithistid sponges which were able to host symbiotic microbial communities. The latter contributed to the precipitation of authigenic calcite and non-carbonate minerals (e.g. pyrite) fuelled by microbial activity under sulphate-reducing conditions. The carbonate body onset is considered to be initiated by seafloor instability due to syndepositional fault acting that induced the appraisal of uplifted tilted blocks within oxygenated waters but near the anoxic water masses. Generated depressions allowed the development of chemosynthetic-based communities. Deep faults related to Triassic salt domes acted as conducts for hydrocarbon and salt brine expulsion to the seafloor and the microbialite growth was enhanced by an abrupt uprising sea level under warmer conditions.  相似文献   

Comparing Training-Image Based Algorithms Using an Analysis of Distance   总被引：1，自引：1，他引：0  

Xiaojin Tan  Pejman Tahmasebi  Jef Caers 《Mathematical Geosciences》2014,46(2):149-169

As additional multiple-point statistical (MPS) algorithms are developed, there is an increased need for scientific ways for comparison beyond the usual visual comparison or simple metrics, such as connectivity measures. In this paper, we start from the general observation that any (not just MPS) geostatistical simulation algorithm represents two types of variability: (1) the within-realization variability, namely, that realizations reproduce a spatial continuity model (variogram, Boolean, or training-image based), (2) the between-realization variability representing a model of spatial uncertainty. In this paper, it is argued that any comparison of algorithms needs, at a minimum, to be based on these two randomizations. In fact, for certain MPS algorithms, it is illustrated with different examples that there is often a trade-off: Increased pattern reproduction entails reduced spatial uncertainty. In this paper, the subjective choice that the best algorithm maximizes pattern reproduction is made while at the same time maximizes spatial uncertainty. The discussion is also limited to fairly standard multiple-point algorithms and that our method does not necessarily apply to more recent or possibly future developments. In order to render these fundamental principles quantitative, this paper relies on a distance-based measure for both within-realization variability (pattern reproduction) and between-realization variability (spatial uncertainty). It is illustrated in this paper that this method is efficient and effective for two-dimensional, three-dimensional, continuous, and discrete training images.  相似文献