On the recovery of surface wave by pressure transfer function

Except the commonly selected pressure transfer function derived from the linear wave theory, a previous study on the pressure transfer function for recovering surface wave from underwater pressure transducer suggested that the pressure transfer function is a function of frequency parameter only. With careful analysis, this study showed that the pressure transfer function should include a transducer submergence parameter as that given by the linear theory. It was found that the previously suggested empirical formula should be restricted to measurements with the pressure transducer close to the surface; otherwise overestimation of wave height would result. Field measurements were carried out with an acoustic wave gauge and a synchronized pressure transducer located at various depths with submergence parameter close to 1 (near the sea floor). It was shown that the previous one-parameter empirical formula might overestimate the significant wave height by more than 30%. This study found that with deep-water wave bursts excluded, the transfer function based on the linear wave theory provided a fairly good estimation on the significant wave heights, with an average deviation of 3.6%.     

Approaches for comparative evaluation of raster GIS-based landslide susceptibility zonation maps

Evaluation of maps generated from different conceptual models or data processing approaches at spatial level has importance in many geoenvironmental applications. This paper addresses the spatial comparison of different landslide susceptibility zonation (LSZ) raster maps of the same area derived from various procedures.     

Artificial neural network and liquefaction susceptibility assessment: a case study using the 2001 Bhuj earthquake data,Gujarat, India

This study pertains to prediction of liquefaction susceptibility of unconsolidated sediments using artificial neural network (ANN) as a prediction model. The backpropagation neural network was trained, tested, and validated with 23 datasets comprising parameters such as cyclic resistance ratio (CRR), cyclic stress ratio (CSR), liquefaction severity index (LSI), and liquefaction sensitivity index (LSeI). The network was also trained to predict the CRR values from LSI, LSeI, and CSR values. The predicted results were comparable with the field data on CRR and liquefaction severity. Thus, this study indicates the potentiality of the ANN technique in mapping the liquefaction susceptibility of the area.     

短周期仪器记录在远震分析中的应用

地震泼由多种频率成份组成,在其传播过程中。由于地球介质的滤波作用,随着传播距离的增大。高频成份逐渐被衰减。周期越大的成份传播越远。因此,在地震观测上,不同频带的地震仪用于观测不同震中距范围的地震,使仪器较好地响应,就我国台网而言,短周期仪用于地方震、近震的监测,中长周期仪和长周期仪用于远震,极远震的监测,其中长周期仪偏重于记录极远震。但作者在实际分析工作中注意到,短周期仪的记录应用于远震,极远震的分析,显示出独特的作用,充分挖掘和利用短仪资料,将会更加丰富远震、极远震的震相资料。本文以高台地震台的资料为依据,从震中距和震级角度,与中长仪和长仪作比较,对短仪记录远震、极远震的震相及特征作了统计分析与初步探讨,并对新疆地区“影区”地震S波的记录、日本地区地震_PPcP等震相的出现提出了现象的存在,给出了相应的观测结果,以待步一步研究。     

Attenuation of body waves in Southeastern Sicily (Italy)

The attenuation of P- and S-waves in Southeastern Sicily was estimated by applying two different methods in time and frequency domains. We analyzed waveforms from about 290 local events (0.6≤M_L≤4.6) recorded at a three-component digital network.By applying the pulse broadening method to the first P-wave pulse, we found an average Q_p value of ca. 140. The application of the frequency decay method provided a Q_p value of ca. 120, in the low-frequency band (3-9 Hz). Conversely, in the high frequency range (16-27 Hz) the average Q_p is significantly larger (ca. 640). The frequency decay method was also applied to S-waves spectra. In the low frequency range (2-5 Hz) the estimated average Q_s is ca. 190. As for Q_p, also Q_s, in the high frequency range (16-27 Hz), is larger (ca. 700). These results evidenced a frequency dependence of both the quality factors Q_p and Q_s, as commonly observed in tectonically active zones characterized by high degree of heterogeneity.     

The anisotropy of magnetic susceptibility in biotite, muscovite and chlorite single crystals

The anisotropy of magnetic susceptibility (AMS) of single crystals of biotite, muscovite and chlorite has been measured in order to provide accurate values of the magnetic anisotropy properties for these common rock-forming minerals. The low-field AMS and the high-field paramagnetic susceptibility are defined. For the high-field values, it is necessary to combine the paramagnetic deviatoric tensor obtained from the high-field torque magnetometer with the paramagnetic bulk susceptibility measured from magnetization curves of the crystals. This leads to the full paramagnetic susceptibility ellipsoid due to the anisotropic distribution of iron cations in the silicate lattice. The ellipsoid of paramagnetic susceptibility, which was obtained for the three phyllosilicates, is highly oblate in shape and the minimum susceptibility direction is subparallel to the crystallographic c-axes. The anisotropy of the susceptibility within the basal plane of the biotite has been evaluated and found to be isotropic within the accuracy of the instrumental measurements. The degree of anisotropy of biotite and chlorite is compatible with previously reported values while for muscovite the smaller than previously published values. The shape of the chlorite AMS ellipsoid for all the samples is near-perfect oblate in contrast with a wide distribution of oblate and prolate values reported in earlier studies. Reliable values are important for deriving models of the magnetic anisotropy where it reflects mineral fabrics and deformation of rocks.     

Validation of Landslide Susceptibility Maps; Examples and Applications from a Case Study in Northern Spain

A procedure for validating landslide susceptibility maps wasapplied in a study area in northern Spain and the results obtained compared. Validationwas used to carry out sensitivity analysis for individual variables and combinationsof variables. The validity of different map-making methods was tested, as well as theutility of different types of Favourability Functions. The results obtained show thatvalidation is essential to determine the predictive value of susceptibility maps. Italso helps to better select the most suitable function and significant variables, thus improving the efficiency of the mapping process. Validation based on a temporal strategy makes it possible to derive hazard maps from susceptibility maps.     

广东及邻区地震活动熵值的异常特征

应用文献」１「的方法，对广东及部分邻近地区进行了熵值计算和分析处理，结果表明，时间熵，频度熵和强度熵在ＭＬ≥４．７级地震之前，大都存在较明显的低值变化，即存在减熵现象，地震大多数以生在减熵的中，后期，少数发生在减熵初期。三种熵值变化基本同步，震级越大，熵值波动越大，其中尤以强度熵变化幅度最大，频度熵次之，时间熵最弱。     

Recovering magnetic susceptibility from electromagnetic data over a one-dimensional earth

While the inversion of electromagnetic data to recover electrical conductivity has received much attention, the inversion of those data to recover magnetic susceptibility has not been fully studied. In this paper we invert frequency-domain electromagnetic (EM) data from a horizontal coplanar system to recover a 1-D distribution of magnetic susceptibility under the assumption that the electrical conductivity is known. The inversion is carried out by dividing the earth into layers of constant susceptibility and minimizing an objective function of the susceptibility subject to fitting the data. An adjoint Green's function solution is used in the calculation of sensitivities, and it is apparent that the sensitivity problem is driven by three sources. One of the sources is the scaled electric field in the layer of interest, and the other two, related to effective magnetic charges, are located at the upper and lower boundaries of the layer. These charges give rise to a frequency-independent term in the sensitivities. Because different frequencies penetrate to different depths in the earth, the EM data contain inherent information about the depth distribution of susceptibility. This contrasts with static field measurements, which can be reproduced by a surface layer of magnetization. We illustrate the effectiveness of the inversion algorithm on synthetic and field data and show also the importance of knowing the background conductivity. In practical circumstances, where there is no a priori information about conductivity distribution, a simultaneous inversion of EM data to recover both electrical conductivity and susceptibility will be required.     

Determination and application of the weights for landslide susceptibility mapping using an artificial neural network

The purpose of this study is the development, application, and assessment of probability and artificial neural network methods for assessing landslide susceptibility in a chosen study area. As the basic analysis tool, a Geographic Information System (GIS) was used for spatial data management and manipulation. Landslide locations and landslide-related factors such as slope, curvature, soil texture, soil drainage, effective thickness, wood type, and wood diameter were used for analyzing landslide susceptibility. A probability method was used for calculating the rating of the relative importance of each factor class to landslide occurrence. For calculating the weight of the relative importance of each factor to landslide occurrence, an artificial neural network method was developed. Using these methods, the landslide susceptibility index (LSI) was calculated using the rating and weight, and a landslide susceptibility map was produced using the index. The results of the landslide susceptibility analysis, with and without weights, were confirmed from comparison with the landslide location data. The comparison result with weighting was better than the results without weighting. The calculated weight and rating can be used to landslide susceptibility mapping.