Comparative analyses of East Texas forest cover maps generated from Landsat and AVHRR data

Comparing satellite data derived map products are affected by differences in data characteristics, image acquisition dates, processing techniques, and classification schemes used for assigning pixels to a thematic class. By comparing two forest maps generated from Landsat Enhanced Thematic Mapper Plus (ETM+) and Advanced Very High Resolution Radiometer (AVHRR) images acquired on the same day, and processed using identical classification scheme and methods these differences were minimized. The ETM+ derived map had higher classification accuracy values and more precise area estimates than the AVHRR derived map. In the ETM+ derived map, 87 of the 599 verification data were misclassified, whereas in the AVHRR derived map, 155 of the 469 verification data were misclassified. Detailed error analyses by land cover class revealed that a land use based definition of forest accounted for 74% (64 out of 87) and 57% (89 out of 155) of the classification errors in ETM+ and AVHRR derived maps, respectively.     

藏东东达山地区遥感找矿地质异常提取方法研究

文章旨在通过对遥感找矿地质方法的研究,总结出一套针对于藏东这种自然条件恶劣的特定地区的遥感找矿工作程序.通过运用比值分析 主成分分析提取矿化蚀变信息,运用方向滤波 掩膜的方法提取构造信息,从而确定了藏东东达山地区的遥感综合异常,并结合多源信息划分出了远景成矿区域,根据对东达山地区遥感找矿的方法研究,进而得到在东达山地区具有成矿潜力的区域范围,为藏东地区的进一步矿产资源开发与评价提供了依据.     

Influence of Structural Non-Stationarity of Surface Roughness on Morphological Characterization and Mechanical Deformation of Rock Joints

Summary Structural non-stationarity of surface roughness affects accurate morphological characterization as well as mechanical behaviour of rock joints at the laboratory scale using samples with a size below the stationarity threshold. In this paper, the effect of structural non-stationarity of surface roughness is investigated by studying the scale dependence of surface roughness and mechanical behaviour of rock joints. The results show that the structural non-stationarity mainly affects the accurate characterization of the surface roughness of the fracture samples. It also controls the amount and location of the contact areas during shear tests, which in turn affects the mechanical properties and asperity degradation of the samples. It is concluded that for accurate determination of the morphological and mechanical properties of rock joints at laboratory and field scales, samples with size equal to or larger than the stationarity threshold are required. Author’s address: Nader Fardin, Rock Mechanics Group, Department of Mining Engineering, Faculty of Engineering, University of Tehran, P.O. Box: 11365/4563, Tehran, Iran     

Ground motion estimation during the Kashmir earthquake of 8th October 2005

In this article, analytical methods have been used to estimate ground motion during the 8 October 2005, Kashmir earthquake. Peak ground acceleration (PGA) values at several stations in the epicentral region have been estimated by empirical analytical source mechanism models. As an alternate analysis, PGA estimates have also been obtained using the stochastic finite fault seismological model. The estimated PGAs are compared with that obtained from damage values. A PGA contour map in the near-source region is provided. It is found that very near to the epicenter, PGA would have reached more than 1 g. It is demonstrated that empirical analytical models can be effectively used to estimate ground motion due to rupture of active faults.     

Integration and magnitude homogenization of the Egyptian earthquake catalogue

The aim of the present work is to compile and update a catalogue of the instrumentally recorded earthquakes in Egypt, with uniform and homogeneous source parameters as required for the analysis of seismicity and seismic hazard assessment. This in turn requires a detailed analysis and comparison of the properties of different available sources, including the distribution of events with time, the magnitude completeness, and the scaling relations between different kinds of magnitude reported by different agencies. The observational data cover the time interval 1900–2004 and an area between 22°–33.5° N and 25°–36° E. The linear regressions between various magnitude types have been evaluated for different magnitude ranges. Using the best linear relationship determined for each available pair of magnitudes, as well as those identified between the magnitudes and the seismic moment, we convert the different magnitude types into moment magnitudes M _W, through a multi-step conversion process. Analysis of the catalogue completeness, based on the M _W thus estimated, allows us to identify two different time intervals with homogeneous properties. The first one (1900–1984) appears to be complete for M _W ≥ 4.5, while the second one (1985–2004) can be considered complete for magnitudes M _W ≥ 3.     

Implementation of reconstructed geomorphologic units in landslide susceptibility mapping: the Melen Gorge (NW Turkey)

In the international literature, although considerable amount of publications on the landslide susceptibility mapping exist, geomorphology as a conditioning factor is still used in limited number of studies. Considering this factor, the purpose of this article paper is to implement the geomorphologic parameters derived by reconstructed topography in landslide susceptibility mapping. According to the method employed in this study, terrain is generalized by the contours passed through the convex slopes of the valleys that were formed by fluvial erosion. Therefore, slope conditions before landsliding can be obtained. The reconstructed morphometric and geomorphologic units are taken into account as a conditioning parameter when assessing landslide susceptibility. Two different data, one of which is obtained from the reconstructed DEM, have been employed to produce two landslide susceptibility maps. The binary logistic regression is used to develop landslide susceptibility maps for the Melen Gorge in the Northwestern part of Turkey. Due to the high correct classification percentages and spatial effectiveness of the maps, the landslide susceptibility map comprised the reconstructed morphometric parameters exhibits a better performance than the other. Five different datasets are selected randomly to apply proper sampling strategy for training. As a consequence of the analyses, the most proper outcomes are obtained from the dataset of the reconstructed topographical parameters and geomorphologic units, and lithological variables that are implemented together. Correct classification percentage and root mean square error (RMSE) values of the validation dataset are calculated as 86.28% and 0.35, respectively. Prediction capacity of the different datasets reveal that the landslide susceptibility map obtained from the reconstructed parameters has a higher prediction capacity than the other. Moreover, the landslide susceptibility map obtained from the reconstructed parameters produces logical results.     

Nonlinear Analysis of Local Site Effects on Seismic Ground Response in the Bam Earthquake

The influence of local geologic and soil conditions on the intensity of ground shaking is addressed in this study. The amplification of the ground motion due to local site effects resulted in severe damage to dwellings in the Bam area during the 2003 Bam Earthquake. A unique set of strong motion acceleration recordings was obtained at the Bam accelerograph station. Although the highest peak ground acceleration recorded was the vertical component (nearly 1 g), the longitudinal component (fault-parallel motion) clearly had the largest maximum velocity as well as maximum ground displacement. Subsurface geotechnical and geophysical (down-hole) data in two different sites have been obtained and used to estimate the local site condition on earthquake ground motion in the area. The ground response analyses have been conducted considering the nonlinear behavior of the soil deposits using both equivalent linear and nonlinear approaches. The fully nonlinear method embodied in FLAC was used to evaluate the nonlinear soil properties on earthquake wave propagation through the soil layer, and compare with the response from the equivalent linear approach. It is shown that thick alluvium deposits amplified the ground motion and resulted in significant damage in residential buildings in the earthquake stricken region. The comparison of results indicated similar response spectra of the motions for both equivalent and nonlinear analyses, showing peaks in the period range of 0.3–1.5 s. However, the amplification levels of nonlinear analysis were less than the equivalent linear method especially in long periods. The observed response spectra are shown to be above the NEHRP building code design requirements, especially at high frequencies.     

Spatial Variability of Rock Depth in Bangalore Using Geostatistical, Neural Network and Support Vector Machine Models

Geospatial technology is increasing in demand for many applications in geosciences. Spatial variability of the bed/hard rock is vital for many applications in geotechnical and earthquake engineering problems such as design of deep foundations, site amplification, ground response studies, liquefaction, microzonation etc. In this paper, reduced level of rock at Bangalore, India is arrived from the 652 boreholes data in the area covering 220 km². In the context of prediction of reduced level of rock in the subsurface of Bangalore and to study the spatial variability of the rock depth, Geostatistical model based on Ordinary Kriging technique, Artificial Neural Network (ANN) and Support Vector Machine (SVM) models have been developed. In Ordinary Kriging, the knowledge of the semi-variogram of the reduced level of rock from 652 points in Bangalore is used to predict the reduced level of rock at any point in the subsurface of the Bangalore, where field measurements are not available. A new type of cross-validation analysis developed proves the robustness of the Ordinary Kriging model. ANN model based on multi layer perceptrons (MLPs) that are trained with Levenberg–Marquardt backpropagation algorithm has been adopted to train the model with 90% of the data available. The SVM is a novel type of learning machine based on statistical learning theory, uses regression technique by introducing loss function has been used to predict the reduced level of rock from a large set of data. In this study, a comparative study of three numerical models to predict reduced level of rock has been presented and discussed.     

SOME EXPERIMENTS CONCERNING THE PRIMARY SEISMIC PULSE*

Recordings were made with three types of detector of the primary compressional (P) and shear (S) wave pulses generated by explosions in boreholes. Charge weights varied from 0.08 kg to 9.5 kg and detector distances varied from about 3 m to about 80 m. Scaling by the simple factor W^1/3 where W is the charge weight, enabled observations from different sized charges to be fitted to a single expression. Experiments were carried out in the Bunter sandstone and the London clay and both fluid and solid tamping were used. This variation in tamping had no significant effect on the P-waves but it may have affected the generation of SV-waves. In both media the P-wave energy carried at 30 m from the shot by frequencies less than 100 Hz decreased rapidly with depth and was usually 1–2 % of the available chemical energy for a shot depth of 15 m. The S-wave energy was much less than this, but was highly directional. The P-wave pulse had the appearance of a damped sinusoid in very good agreement with the predictions of the ‘equivalent radiator’ hypothesis. However, the surface of this radiator should be identified not with the blown cavity but with the surface at which the tensile stresses associated with the stress wave become less than the tensile strength of the rock. The predominant frequency for a 1 kg charge at a depth of 15 m was 24 Hz in the clay and 52 Hz in the sandstone. In these and similar media, therefore, an effort should be made to keep individual charges less than 1 kg in reflection shooting and less than 10 kg in refraction shooting. The value of Q was about 50 in clay and about 25 in the sandstone. These estimates are rather uncertain because of the small distances over which the pulses were observed. The Z-transforms of the sampled pulses indicated that they were all of minimum phase, or very near to it.