Effect of sensor modelling methods on computation of 3-D coordinates from Cartosat-1 stereo data

The orbital and the rational polynomial coefficients (RPC) models are the two most commonly used models to compute a three-dimensional coordinates from an image stereo-pair. But it is still confusing that with the identical user provided inputs, which one of these two models provides more accurate digital elevation model (DEM), especially for mountainous terrain. This study aimed to find out the answer by evaluating the impact of used models on the vertical accuracy of DEM extracted from Cartosat-1 stereo data. We used high-accuracy photogrammetric DEM as the reference DEM. Apart from general variations in statistics, surprisingly in a few instances, both the DEMs provided contrasting results, thus proving the significance of this study. The computed root mean square errors and linear error at 90% (LE90) were lower in case of RPC DEM for various classes of slope, aspect and land cover, thus suggesting its better relative accuracy.     

Seismic attenuation estimation using a complete ensemble empirical mode decomposition-based method

The frequency attenuation gradient method can provide important information for hydrocarbon detection. In this paper, a method using Complete Ensemble Empirical Mode Decomposition (CEEMD), Hilbert transform and the least-squares curve-fitting is proposed for seismic attenuation estimation as an effective frequency attenuation gradient estimation approach. We first use CEEMD to obtain the different Intrinsic Mode Functions (IMFs), which have a narrow band and can enhance the physical meaning of instantaneous attributes trace by trace. The time-frequency spectrum, which is computed using a Hilbert transform of each IMF, is represented as a spectrum with a single-peak that has narrow side lobes, which is conducive to frequency attenuation gradient estimation. Second, for each time sample, the frequency-amplitude spectrum of each IMF trace is extracted from the time-frequency spectrum to conduct the attenuation gradient computation. Then, the logarithm operation is performed for each IMF trace. Due to the very narrow bands of some IMFs in some seismic traces, a variable frequency window is adopted along the IMF trace according to the local data characteristics. Finally, the attenuation gradient for each IMF in a seismic trace can be computed using least-squares fitting. A different IMF reflects a seismic trace with a different spatiotemporal scale and can highlight different geologic and stratigraphic information. The correlation weighted average operation is used to highlight some useful details in seismic trace and obtains the attenuation gradient for each seismic trace. Field data examples demonstrate our method and its effectiveness. The proposed method can stably estimate the frequency attenuation gradient.     

Nonparametric Estimation of Undrained Shear Strength for Normally Consolidated Clays

For decades, various well-known empirical correlations have been established and commonly used to estimate the undrained shear strength of normally consolidated clays in geotechnical practice. However, there are still many contradictory cases regarding the validity of these correlations, so their applicability and reliability are questionable. In this study, an extensive geotechnical database for normally consolidated clays has been compiled. Next, a Bayesian nonparametric method is exploited to identify the most critical soil index properties in inferring the undrained shear strength and a new predictive model is proposed. Finally, the performance of the proposed predictive model is assessed and compared with two well-known correlations using an independent testing database. It confirms that the proposed model not only possesses high predictability, but also provides superior performance over other existing empirical correlations.     

基于改进K-SVD字典学习方法的地震数据去噪

为实现更好的地震数据去噪技术,笔者引入一种新的算法:快速迭代收缩阀值法(FISTA),通过FISTA和K-奇异值分解(K-SVD)不断迭代更新K-SVD字典,利用更新得到的K-SVD字典对地震数据进行稀疏表示,去除稀疏系数中较小的数值,使数据中的随机噪声得到压制。对层状模型合成地震记录,Marmousi模型合成地震记录以及实际地震数据进行对比实验,得出FISTA算法较OMP算法能更好地提高地震数据的信噪比,同时有效地保护了反射信号。     

The effects of visual realism,spatial abilities,and competition on performance in map-based route learning in men

We report on how visual realism might influence map-based route learning performance in a controlled laboratory experiment with 104 male participants in a competitive context. Using animations of a dot moving through routes of interest, we find that participants recall the routes more accurately with abstract road maps than with more realistic satellite maps. We also find that, irrespective of visual realism, participants with higher spatial abilities (high-spatial participants) are more accurate in memorizing map-based routes than participants with lower spatial abilities (low-spatial participants). On the other hand, added visual realism limits high-spatial participants in their route recall speed, while it seems not to influence the recall speed of low-spatial participants. Competition affects participants’ overall confidence positively, but does not affect their route recall performance neither in terms of accuracy nor speed. With this study, we provide further empirical evidence demonstrating that it is important to choose the appropriate map type considering task characteristics and spatial abilities. While satellite maps might be perceived as more fun to use, or visually more attractive than road maps, they also require more cognitive resources for many map-based tasks, which is true even for high-spatial users.     

同轴双向回转钻进破岩效率研究

国内外相关研究均显示同轴双向回转可有效降低钻具振动和提高破岩效率,但双向回转相对传统单向回转的钻进效率的提升水平研究较少。据此,本文建立双向回转钻头以及单向回转钻头与岩石相互作用的有限元模型,以破岩比功作为评价指标量化比较分析了2种钻头的破岩效率。通过定义双向钻头内外壁尺寸差、内外钻头的间隙、内钻头壁厚与双向钻头内外壁尺寸差之比、内外钻头转速比和内外钻头底部高度差5种核心参数,并设计正交试验完成了仿真分析。结果显示,内外钻头高度差与内外钻头间隙对于破岩比功影响比较小,内外钻头尺寸差、内外钻头转速比和内钻头壁厚与双向钻头内外尺寸差之比对破岩比功影响显著。     

基于优化经验模态分解和聚类分析的滑坡位移智能预测研究

针对三峡库区"阶跃式"滑坡的变形特征,提出了一种新的滑坡位移预测方法。以白水河滑坡ZG118和XD-01监测点位移数据为例,采用基于软筛分停止准则的经验模态分解(SSSC-EMD)将累计位移-时间曲线和影响因子时间序列自适应地分解为多个固有模态函数(IMF),并采用K均值(K-Means)聚类法对其进行聚类累加,得到有物理含义的位移分量(趋势性位移、周期性位移以及随机性位移)和影响因子分量(高频影响因子和低频影响因子)。使用最小二乘法对趋势性位移进行拟合预测;采用果蝇优化-最小二乘支持向量机(FOA-LSSVM)模型对周期性位移和随机性位移进行预测。将各位移分量预测值进行叠加处理,实现滑坡累计位移的预测。研究结果表明,所提出的(SSSC-EMD)-K-Means-(FOA-LSSVM)模型能够预测"阶跃式"滑坡的位移变化规律,且预测精度高于传统的支持向量机回归(SVR)、最小二乘支持向量机(LSSVM)模型;并通过改变训练集长度,进行单因素分析,发现其与预测精度之间呈正相关关系。     

静压桩承载力时间效应的研究进展

由于静压桩沉桩后桩周土重塑,静压桩承载力表现出随着休止期的延长而增长的特性。本文从静压桩沉桩后桩周土体内孔隙水消散固结的角度出发,对静压桩承载力时间效应的理论和试验分别进行归纳,结合孔隙水消散路径及固结模型,对桩周土体初始超静孔隙水压力大小及其分布特征进行总结,分析承载力各种测试方法的优缺点,对静压桩承载力的时效性进行深化研究,并探讨了不同地质条件、不同桩的类型对休止期内静压桩承载力的影响,进一步对基于实测数据得出的经验公式进行总结。讨论了基于不同本构关系模型的应力场及位移场解答和沉桩后孔隙水压力消散解答,在此基础上总结了桩基极限承载力理论公式;探讨了黏性土、砂土条件下,考虑超固结比、不排水抗剪强度和塑性指数比对桩基极限承载力系数A的影响,在此基础上归纳了桩基极限承载力经验公式。建议在经验公式基础上设置多重参数,以提升经验公式的精确度,并完善对不同桩、土类型的参数解答;利用BP神经网络,导入静压桩承载力相关参数,以得到针对不同地质条件、桩型、休止期的承载力最优解。     

基于相干特征的岩石薄片序列图像边缘提取及颗粒分割

针对岩石颗粒边缘模糊、结构复杂的特点,为了更有效地识别颗粒边缘,在基于特征值的C3相干算法的基础上,融合多尺度和多角度的特征表达,提出了一种改进的C3相干算法。该算法综合考虑岩石薄片图像角度域光学特征、空间尺度信息和各向异性信息,能更有效地表征颗粒边缘特征,表现出对复杂矿物结构的适应能力。在采集的岩石薄片正交偏光图像上验证提出的算法,实验结果表明,与原生C3相干算法相比,改进后的C3相干算法在全局图像上的方差和灰度差分乘积分别提升了68.41%和22.91%,信息熵下降了21.61%。     

我国华南江南春季雷暴气候特征分析

基于我国华南江南地区274个基本地面气象观测站数据、全国闪电定位数据以及欧洲中心的全球大气再分析数据(ERA-Interim),对1981—2017年华南江南地区的春季雷暴日采用经验正交函数分解方法(EOF),并与气象要素场做回归分析。得出以下主要结论:(1)我国华南江南地区春季雷暴活动高发区主要在广西东部至广东西部;其高峰期在下午18:00和凌晨4:00左右,且大多数雷暴活动持续时间不超过3 h;山区雷暴活动主要在傍晚至夜间;平原雷暴活动主要在白天,高峰在17:00及06:00前后;(2)华南江南地区的雷暴活动存在着3~5年的短周期和16年左右的长周期变化;(3)雷暴日距平EOF分析的前3个主成分累计方差贡献达到72.3%。按其向量场的方差贡献分型,Ⅰ型表现为华南江南雷暴活跃特征呈现较统一的变化规律。深厚西南低涡槽前、上干下湿的水汽层结、上冷下暖的温度层结为华南江南地区发生大范围雷暴天气提供良好的动力、水汽和位势不稳定条件,是华南江南雷暴活跃异常的主要模态;Ⅱ型表现为从华南南部到江西与浙江南部有一条西南-东北向、下宽上窄的雷暴活跃正距平异常区,而两侧为负距平异常区。其环流特征表现为温度整层偏冷,水汽整层偏湿,而西南槽前动力抬升有利于水汽抬升凝结触发对流形成雷暴;Ⅲ型表现为华南和江南地区雷暴活跃特征呈南北反位相异常,其分界线在26 °N附近。其环流特征表现为较强的干冷空气南下与南方暖湿空气在南岭山区对峙形成异常的垂直环流圈。在其上升支,低层干冷空气被卷入中高层使得中高层暖湿空气凝结释放潜热形成对流,造成华南地区多雷暴发生,而江南地区处于垂直环流的下沉支,整层湿度偏干,造成江南地区雷暴相对偏少。