Numerical behaviour of the downward continuation of gravity anomalies

The numerical results of downward continuation (DWC) of point and mean gravity anomalies by the Poisson integral using point, single mean, and doubly averaged kernel are examined. Correct evaluation of the integral in its innermost zone is a challenging task. To avoid instabilities, an analytical planar approximation is used in the innermost integration zone. In addition it is shown that the single mean mode has the minimum discretization error. Downward continuation of point and mean anomalies by singly and doubly averaged kernel are the same mean anomalies on the geoid.     

A new indicator of elastic spectral shape for the reliable selection of ground motion records

How to select a limited number of ground motion records (GMRs) is an important challenge for the non‐linear analysis of structures. Since epsilon (ε_Sa) is an indicator of spectral shape, which has a significant correlation with the non‐linear response of a structure, the selection of GMRs based on the hazard‐related target ε_Sa is a reasonable approach. In this paper, an alternative indicator of spectral shape is proposed, which results in a more reliable prediction of the non‐linear response for the structures with the natural period of 0.25 to 3.0 s. This new parameter, named eta (η), is a linear combination of ε_Sa and the peak ground velocity epsilon (ε_PGV). It is shown that η, as a non‐linear response predictor, is remarkably more efficient than the well‐known and convenient parameter ε_Sa. The influence of η‐filtration in the collapse analysis of an eight‐story reinforced concrete structure with special moment‐resisting frames was studied. Statistical analysis of the results confirmed that the difference between ε‐filtration and η‐filtration can be very significant at some hazard levels. In the case of this structure, the resulting annual frequency of collapse was found to be lower in the case of η‐based record selection, in comparison with the ε‐based record‐selection approach. Copyright © 2011 John Wiley & Sons, Ltd.     

Smoothing impact of isostatic crustal thickness models on local integral inversion of satellite gravity gradiometry data

The effects of topographic masses on satellite gradiometric data are large and in order to reduce the magnitude of these effects some compensation mechanisms should be considered. Here we use the isostatic hypotheses of Airy-Heiskanen and the recent Vening Meinesz-Moritz for compensating these effects and to smooth the data prior to their downward continuation to gravity anomaly. The second-order partial derivatives of extended Stokes’ formula are used for the continuations over a topographically rough territory like Persia. The inversions are performed and compared based on two schemes of the remove-compute-restore technique and direct downward continuation. Numerical results show that the topographic-isostatic effect based on Vening Meinesz-Mortiz’s hypothesis smoothes the data better than that based on Airy-Heiskanen’s hypothesis. Also the quality of inversions of the smoothed data by this mechanism is twice better than that of the nonsmoothed ones.     

Nonlinear joint flexibility element for the modeling of jacket-type offshore platforms

A new nonlinear two-dimensional tubular joint element is developed in this study on the basis of flexibility equations and the interaction between the axial force and the in-plane bending moment in the joint. Empirical equations are used to define the joint yielding in the axial direction and the in-plane rotation. An elastic-perfectly plastic yield function is adopted to include the combined effects of axial loads and bending moments on the yielding of the joint. The element formulation is straightforward, and it can readily be implemented in nonlinear finite element programs. Verification studies are carried out for the element to prove its suitability for the modeling of tubular joints of offshore jacket structures. It is concluded that the nonlinear joint model that has been developed produces accurate results, verified against experimental data as well as against sophisticated multi-axial finite element joint models.     

Utilization of ASTER Data and Spectral Analysis to Discriminate Hydrothermally Altered Areas over Rabor,South of Kerman,Iran

This study attempts to evaluate the capability of the advanced spaceborne thermal emission and reflection radiometer (ASTER) and the advantages of ground knowledge for generating maps portraying hydrothermally altered areas in relation to porphyry copper deposits. The northern part of the Rabor area in the Urumieh–Dokhtar magmatic belt, containing some copper mineralization occurrences, was investigated as a case study. Several image processing techniques, namely minimum noise fraction, pixel purity index, and n-dimensional visualization, contributed to the extraction of pure pixels as endmembers. The spectra of some rock samples collected around the well-known altered zones of the study area were resampled to ASTER bands and used to identify the image-extracted endmembers. Spectral analysis of the endmembers and ground sample spectra led to the identification of three types of hydrothermal alterations: (1) phyllic, (2) propylitic, and (3) argillic. The identified endmembers were used as the specified targets for mapping hydrothermal alteration zones over the study area by using a mixture tuned match filtering algorithm. Results demonstrate that high abundances within pixels correspond closely to the altered areas. Field observations, thin section, and X-ray diffraction of collected samples confirmed the accuracy of the alteration maps prepared by the application of the proposed methods. The final classified hydrothermal alteration maps showed the overall accuracy and kappa coefficient values of 85.41 and 0.72%, respectively. These results ascertain that ASTER data that use suitable image processing techniques appear consistent in mapping out the distribution of hydrothermally altered areas. In addition, ground knowledge data can act as a valuable information source to increase the image classification accuracy and reliability.     

Modeling olive-crop forecasting in Tunisia

Tunisia is the world’s second largest olive oil-producing region after the European Union. This paper reports on the use of models to forecast local olive crops, using data for Tunisia’s five main olive-producing areas: Mornag, Jemmel, Menzel Mhiri, Chaal, and Zarzis. Airborne pollen counts were monitored over the period 1993–2011 using a Cour trap. Forecasting models were constructed using agricultural data (harvest size in tonnes of fruit/year) and data for several weather-related and phenoclimatic variables (rainfall, humidity, temperature, Growing Degree Days, and Chilling). Analysis of these data revealed that the amount of airborne pollen emitted over the pollen season as a whole (i.e., the Pollen Index) was the variable most influencing harvest size. Findings for all local models also indicated that the amount, timing, and distribution of rainfall (except during blooming) had a positive impact on final olive harvests. Air temperature also influenced final crop yield in three study provinces (Menzel Mhiri, Chaal, and Zarzis), but with varying consequences: in the model constructed for Chaal, cumulative maximum temperature from budbreak to start of flowering contributed positively to yield; in the Menzel Mhiri model, cumulative average temperatures during fruit development had a positive impact on output; in Zarzis, by contrast, cumulative maximum temperature during the period prior to flowering negatively influenced final crop yield. Data for agricultural and phenoclimatic variables can be used to construct valid models to predict annual variability in local olive-crop yields; here, models displayed an accuracy of 98, 93, 92, 91, and 88 % for Zarzis, Mornag, Jemmel, Chaal, and Menzel Mhiri, respectively.     

Prediction of monthly discharge volume by different artificial neural network algorithms in semi-arid regions

Arabian Journal of Geosciences - Prediction of monthly discharge volume is important for reservoir management and evaluation of drinking-water supplies. Also, it is very essential in arid and...     

Iranian earthquakes, a uniform catalog with moment magnitudes

A uniform earthquake catalog is an essential tool in any seismic hazard analysis. In this study, an earthquake catalog of Iran and adjacent areas was compiled, using international and national databanks. The following priorities were applied in selecting magnitude and earthquake location: (a) local catalogs were given higher priority for establishing the location of an earthquake and (b) global catalogs were preferred for determining earthquake magnitudes. Earthquakes that have occurred within the bounds between 23–42° N and 42–65° E, with a magnitude range of M _W 3.5–7.9, from the third millennium BC until April 2010 were included. In an effort to avoid the “boundary effect,” since the newly compiled catalog will be mainly used for seismic hazard assessment, the study area includes the areas adjacent to Iran. The standardization of the catalog in terms of magnitude was achieved by the conversion of all types of magnitude into moment magnitude, M _W, by using the orthogonal regression technique. In the newly compiled catalog, all aftershocks were detected, based on the procedure described by Gardner and Knopoff (Bull Seismol Soc Am 64:1363–1367, 1974). The seismicity parameters were calculated for the six main tectonic seismic zones of Iran, i.e., the Zagros Mountain Range, the Alborz Mountain Range, Central Iran, Kope Dagh, Azerbaijan, and Makran.     

Effect of Fines Type and Content of Sand on Correlation Between Shear Wave Velocity and Liquefaction Resistance

The use of shear wave velocity (V _s) measurements as an in situ test for evaluation of liquefaction potential has increased substantially due to its advantages. Relatively large numbers of studies have been performed to establish the correlation between V _s and liquefaction resistance (CRR) of clean sands. Usually, natural sands contain silt and/or clay, and previous studies have shown that both the amount of fines and their nature influence the values of CRR as well as V _s. Therefore, the CRR–V _s correlations may also be affected by fines content and type of sandy soils. However, effect of fines content and especially fines type of sandy soils on the correlation between V _s and CRR is inadequately addressed in the literature. In this study, cyclic triaxial and bender element tests were conducted on samples of sand containing various amounts of different types of fines, and the effects of fines on the values of CRR and V _s are investigated. The results show that G ₀ and CRR reduce even when small amounts of fines are added to sand. Therefore, use of plasticity index (PI) of the fines fraction is better than the PI of the overall soil when trying to assess the effects of fines. Using obtained experimental data as well as the established semiempirical CRR–V _s relationship, the CRR–V _s correlation was developed for all the tested soils, and the effect of fines type on the correlation is also examined. Based on the results obtained in this study, CRR–V _s correlation is affected by both the amount and the plasticity of the fines present in the sand, and this correlation is soil specific.     

Semi Automatic Road Extraction by Fusion of High Resolution Optical and Radar Images

Two new methods for fusion of high-resolution optical and radar satellite images have been proposed to extract roads in high quality in this paper. Two fusion methods, including neural network and knowledge-based fusion are introduced. The first proposed method consists of two stages: (i) separate road detection using each dataset and (ii) fusion of the results obtained using a neural network. In this method, the neural networks are separately applied on high-resolution IKONOS and TerraSAR-X images for road detection, using a variety of texture parameters. The outputs of two neural networks, as well as the spectral features of optical image, are used in a third neural network as inputs. The second method is a knowledge-based fusion using thresholds of narrow roads and vegetation gray levels. First roads are extracted from each source separately. The outputs are then compared and advantages and disadvantages of each data source are investigated . The results obtained from accuracy assessment show the efficiency of the proposed methods. Furthermore, the comparison of the results showed the superiority of the first algorithm.