Linking the explicit probability of entrainment of instrumented particles to flow hydrodynamics

Obtaining a better understanding of the underlying dynamics of the interaction of turbulent flows and the bed surface that contains them, leading to the transport of coarse particles in fluvial, coastal, and aeolian environments, is considered as one of the fundamental objectives and the most complex problems in Earth surface dynamics and engineering. Recent technological advancements have made it possible to directly assess sediment entrainment rather than monitoring surrogate flow metrics, which could be related indirectly to sediment entrainment. In this work, a novel and low-cost instrumented particle, 7 cm in diameter, is used to directly assess the incipient entrainment of a coarse particle resting on a bed surface. The particle has inertial measurement units (IMUs) embedded within its waterproof shell, enabling it to track the particle's motions and quantify its inertial dynamics. The sensors of the instrumented particle are calibrated using simple and easy-to-validate theoretically physical motions to estimate the uncertainties in their readings, which are reduced using an inertial sensor fusion process. A series of well-designed laboratory flume incipient motion experiments are performed to assess the entrainment of the instrumented particle for a range of flowrates near the threshold of motion. The readings of the instrumented particle are used to derive metrics that are related to the probability of its incipient entrainment. The flow velocity measurements are obtained for the experiment runs, and the derived metrics are explicitly linked to the flow hydrodynamics responsible for the entrainment. The framework presented in this work can be used for a range of similar applications of low-cost instrumented particles, spanning the interface of sensing and instrumentation in engineering (i.e., infrastructure and environmental monitoring) and geosciences (e.g., habitat assessment).     

On the use of IMU (inertial measurement unit) sensors in geomorphology

Inertial measurement units (IMUs) are mobile sensors assemblies constructed using a combination of MEMS (micro electrical mechanical systems) accelerometers, gyroscopes and magnetometers. Both the technology and its applications to geomorphic problems are developing rapidly, since they demonstrate the prospect of monitoring individual sediment grains, of various sizes, during transport and at high frequency. This prospect has numerous implications which range from hazard identification and warning to complex theoretical derivations for sediment transport modelling. At the same time, the deployment of IMUs needs to be underpinned by a number of technical considerations regarding the limitations of the technology and the physics of the inertial measurements. IMU measurements should be reported in a manner that allows for clear understanding of the scope of the study, with sufficient detail for repeatability and clear error characterization. At a secondary level, IMU measurements should be linked clearly with the physics of sediment motion. Here the author highlights five technical issues which can lead to the misinterpretation of IMU measurements. His scope is to begin a dialogue towards a collective agreement on a presentation/reporting protocol for IMU measurements in geomorphic studies that will allow for the coherent contextualization of the technology and accelerate its scientific impact within geosciences.     

地质样品中铂族元素的分析测定方法

文中阐述并归纳了近年地质样品中铂族元素的分离、富集及测试方法方面的最新进展。铂族元素本身的超痕量性,要求实验过程中对空白值的控制,干扰元素的扣除和检测限的降低更为严格,同时要克服块金效应。文中对消解过程中常用的火试金法、酸溶、碱熔方法和卡洛斯管法(Carius tube),分离富集过程中的Te共沉淀和离子交换法,测试手段中的原子光谱法、中子活化法和等离子质谱法等方法的最新进展进行了总结。由于复杂的地质样品中PGE的浓度范围不一、赋存形式多样,要求在具体样品分析过程中灵活地搭配使用各种分离富集和检测方法,结合笔者所在实验室在实验过程中发现的问题,对各种不同类型地质样品中铂族元素的分离富集、样品处理及测定方法也进行了总结。     

虚拟地形环境中道路与地形模型融合算法研究及精度评价

以大比例尺地图构建的虚拟地形环境,由于观察视点的接近以及应用中对各种查询和分析的需要,所以要求构建的环境既能准确地表现地形特征又能使地物与地形精确融合,准确地查询出地物的属性,以满足目视及精确定位的要求.然而,实际应用中往往忽视地形与地物的密切关系,从而导致在目视比例尺条件下出现地物飘在空中或钻入地下等失真现象.为此,本文以道路为例提出了道路模型与地形模型的融合算法,同时对融合后道路与地形模型的精度进行了评估,为构建逼真的地理环境提供了基础.也为河流、岛屿、湖泊等地物与地形模型的融合提供参考.     

保持光谱信息的遥感图像融合方法研究

常用的遥感图像融合方法,如IHS变换法、Brovey变换法和主成分变换法等在实施图像融合时,均会有不同程度的光谱扭曲现象.探讨能有效保持光谱信息的EECN融合法.EECN融合法采用比值变换法,同时对参与融合的全色波段进行增强边缘,融合后的图像在光谱保持性能、分类精度等方面均较优.     

多帧图像融合提高分辨率的方法研究

多帧图像融合的目的在于复原截止频率之外的信息,以使图像获得更多的细节和信息,提高图像的分辨率。本文阐述了提高图像分辨率的关键技术,从图像匹配和运动估计入手,应用共轭梯度多帧图像融合方法对楔形空间分辨率测试图像进行了方法实验,证实了该方法的可行性与有效性。     

不同高分辨率遥感图像融合技术特征比较

简要回顾了图像融合技术的起源和发展情况。对图像融合的概念与基础理论作了阐述,剖析了其优缺点和使用领域。通过6种融合方法对杭州市滨江区QuickBird正射影像及数字化地形图进行了融合,并对融合图像进行了效果评价,结果表明,所有融合图像的方差和熵都大于配准后的图像,融合后图像的信息量大为增加。     

基于小波变换和局部相关系数改进IHS变换的图像融合方法

为得到分辨率高、光谱畸变小的融合图像,该文根据图像处理理论和小波变换的时频局部 特性,采用Quickbird数据,对多光谱波段经IHS变换的I分量和全波段图像分别进 行小波分解,用全波段图像经小波分解得到的高频系数替换I分量小波分解的高频系数, 替换时根据图像的地物光谱特性引入局部相关系数进行有选择的高频替换.经过IHS反变换得到空间分辨率高且没有光谱畸变的融合图像.     

Production of high-resolution remote sensing images for navigation information infrastructures

This paper introduces the image fusion approach of multi-resolution analysis-based intensity modulation (MRAIM) to produce the high-resolution multi-spectral images from high-resolution panchromatic image and low-resolution multi-spectral images for navigation information infrastructure. The mathematical model of image fusion is derived according to the principle of remote sensing image formation. It shows that the pixel values of a high-resolution multi-spectral images are determined by the pixel values of the approximation of a high-resolution panchromatic image at the resolution level of low-resolution multi-spectral images, and in the pixel valae computation the M-band wavelet theory and the d trous algorithm are then used. In order to evaluate the MRAIM approach, an experiment has been carried out on the basis of the IKONOS 1 m panchromatic image and 4 m multi-spectral images. The result demonstrates that MRAIM image fusion approach gives promising fusion results and it can be used to produce the high-resolution remote sensing images required for navigation information infrastructures.     

遥感影像的融合--SPOT全色波段和多光谱影像的融合

按照影像融合的一般理论,结合Erdas软件功能实现了SPOT全色波段和多光谱影像的融合。