多维信息在改善沿海地区图像分类精度中的应用方法

在某些专题研究中,由于研究目标、大气传输、下垫面及其他因素的限制,波谱分析的统计分类模式并不能完全满足研究需要。虽然多时相高精度图像可以提高分类精度,但常因其费用相当昂贵而难以实现。因此,如何在现有资料基础上,提取更多有效信息是亟需解决的问题。针对沿海地区特有的复杂地理现象,以TM图像为基础,通过量化手段进行最佳信息维数的确定与最佳信息维数组合的选择,探讨了信息维数对分类精度的影响。结果表明,在原有图像基础上,进行信息挖掘并重新组合可以得到能满足工作需要的分类精度,组合维数以6维最佳,更多的信息融合对精度影响不明显。     

Detecting significant sediment motion in a laboratory flume using digital video image analysis

A video analysis method for monitoring sediment transport and sorting processes in a laboratory flume is presented. Video taken through the glass side‐wall of a laboratory flume is captured using a digital CCD (charge‐coupled device) camera and significant movements between individual frames are detected using image analysis. This method involves direct subtraction of the brightness numbers of pixels in sequential video frames, followed by thresholding to produce binarized images of significant change, above the inherent level of system noise. Experimental results showing dilation of a gravel framework and rapid infiltration of fines just prior to entrainment are discussed. Copyright © 2000 John Wiley & Sons, Ltd.     

卫星通信在地震烈度速报数据传输中的应用

在分析地震烈度速报数据传输特点后,提出将卫星通信引入烈度速报系统。通过对目前中国使用较多的北斗卫星、海事卫星、铱卫星系统和VSAT卫星系统进行对比,选取铱星短消息和海事卫星数据流这两种典型通讯方式,设计由通用数字强震仪与卫星通信系统结合地震速报通讯模块组成的实验系统,实现数字强震动记录信息通过卫星信道进行的数据传输,展现卫星通信在地震烈度速报数据传输中的应用前景。     

Statistical facies classification from multiple seismic attributes: comparison between Bayesian classification and expectation–maximization method and application in petrophysical inversion

We present here a comparison between two statistical methods for facies classifications: Bayesian classification and expectation–maximization method. The classification can be performed using multiple seismic attributes and can be extended from well logs to three‐dimensional volumes. In this work, we propose, for both methods, a sensitivity study to investigate the impact of the choice of seismic attributes used to condition the classification. In the second part, we integrate the facies classification in a Bayesian inversion setting for the estimation of continuous rock properties, such as porosity and lithological fractions, from the same set of seismic attributes. The advantage of the expectation–maximization method is that this algorithm does not require a training dataset, which is instead required in a traditional Bayesian classifier and still provides similar results. We show the application, comparison, and analysis of these methods in a real case study in the North Sea, where eight sedimentological facies have been defined. The facies classification is computed at the well location and compared with the sedimentological profile and then extended to the 3D reservoir model using up to 14 seismic attributes.     

Application of Structure‐from‐Motion photogrammetry to river restoration

Structure‐from‐Motion (SfM) photogrammetry is now used widely to study a range of earth surface processes and landforms, and is fast becoming a core tool in fluvial geomorphology. SfM photogrammetry allows extraction of topographic information and orthophotos from aerial imagery. However, one field where it is not yet widely used is that of river restoration. The characterisation of physical habitat conditions pre‐ and post‐restoration is critical for assessing project success, and SfM can be used easily and effectively for this purpose. In this paper we outline a workflow model for the application of SfM photogrammetry to collect topographic data, develop surface models and assess geomorphic change resulting from river restoration actions. We illustrate the application of the model to a river restoration project in the NW of England, to show how SfM techniques have been used to assess whether the project is achieving its geomorphic objectives. We outline the details of each stage of the workflow, which extend from preliminary decision‐making related to the establishment of a ground control network, through fish‐eye lens camera testing and calibration, to final image analysis for the creation of facies maps, the extraction of point clouds, and the development of digital elevation models (DEMs) and channel roughness maps. The workflow enabled us to confidently identify geomorphic changes occurring in the river channel over time, as well as assess spatial variation in erosion and aggradation. Critical to the assessment of change was the high number of ground control points and the application of a minimum level of detection threshold used to assess uncertainties in the topographic models. We suggest that these two things are especially important for river restoration applications. Copyright © 2016 John Wiley & Sons, Ltd.     

抗震设计反应谱特征周期研究

搜集整理1933—2015年美国西部地区166个有详细钻孔资料台站场地上的1 237条水平方向强震记录,按照我国建筑抗震设计规范(GB 50011-2010)中反应谱的形状对强震记录的加速度反应谱进行拟合,提取反应谱的特征周期。分析特征周期随场地类别、震级、震中距的变化特征;按特征周期分区统计计算不同场地类别上的特征周期平均值,并与我国现行的建筑抗震设计规范中给定的特征周期值进行对比研究;最后探讨地震动峰值加速度对特征周期的影响。根据研究分析结果提出关于抗震设计反应谱特征周期值的改进建议。     

分区分类的生命线工程地震直接经济损失研究

生命线工程的震害及损失评估工作对于震害防御和震后地震应急工作有着极其重要的意义。 但是, 生命线工程是一个复杂庞大的网络系统, 目前对其开展的震害及损失评估研究工作存在着很大的局限性和不确定性。 本文充分利用研究较多且较系统的建筑物震害及损失评估结果, 结合历次典型历史地震震害中建筑物和生命线震害情况, 通过分析建筑物损失和生命线工程损失的数量关系, 建立二者之间的关联模型; 通过对人口、 GDP、 土地利用等公里网格数据进行分析, 给出中国大陆地区的分区分类原则, 建立分区分类的生命线工程地震直接经济损失分析模型; 基于GIS软件平台, 开发了生命线工程地震直接经济损失分析模块, 利用该模块, 得出了四川省不同地震烈度下的生命线工程直接经济损失空间分布情况。     

地理信息系统研究新范式

随着大数据时代的到来,地理信息系统（GIS）的时空范畴、信息内容和应用场景都得到了前所未有的扩展,地理信息系统需要由例外处理的被动适应方式,转变为内核支持的主动扩展方式,将地理信息系统扩展为新一代时空信息系统。本文在分析地理信息系统本质是以地图数据模型为核心的信息系统的基础上,从研究对象、基本原理和技术方法3个方面总结梳理了地理信息系统研究范式,并分析阐述了时空信息扩展对地理信息系统研究范式的新要求。其次,在分析全空间信息系统（PSIS）认知模型与多粒度时空对象数据模型的基础上,归纳出全空间信息系统基于时空实体的理论与技术路线,并总结其在多个领域的实践与应用。然后,系统分析了全空间信息系统对地理信息系统研究对象、基本原理和技术方法的具体扩展方式,提出全空间信息系统研究范式。最后,总结梳理了全空间信息系统研究范式的基本内容,并与地理信息系统研究范式进行了核心内容的分析对比,展望了地理信息系统研究范式进阶将带来的影响和变化。     

基于合成孔径雷达回波信号的海洋溢油监测方法研究

海洋油污染是各类海洋污染中最常见、分布面积最广且危害程度最大的污染之一。近年来,海洋特别是近海人类活动频繁,且随着海上运输和石油加工业的发展,油田井喷、钻井平台爆炸、船舶碰撞等所造成的溢油事故增多,因而,监测海洋溢油具有重要的经济和社会现实意义。研究采用MatLAB工具,通过图像预处理(图像校正和增强)、特征提取和神经网络识别等方法,对合成孔径雷达(SAR)海洋溢油图像进行处理,最终期望实现半自动区分SAR图像上各类目标,并进行多种神经网络方法效果比较。研究首先对SAR海洋溢油图像进行初步人工识别;然后进行图像预处理(几何校正、滤波处理等)和基于灰度共生矩阵的特征值计算;最后,借助神经网络方法对溢油区域和疑似溢油区域进行分类,输出分类处理后的图像。通过输出图像分析发现,神经网络能对SAR海洋溢油图像中溢油、海水、土地3类目标进行明确分类,且RBF神经网络模型精度高于BP神经网络。本文提出的半自动分类方法不仅能提高SAR图像处理效率,将分类目标扩充有溢油和非溢油扩充到溢油、海水、土地3类,提高图像处理的全面性,同时通过比较RBF和BP神经网络在SAR溢油图像分类上的具体优劣,有着较好实际意义。     

Hierarchically nested river landform sequences. Part 2: Bankfull channel morphodynamics governed by valley nesting structure

River corridors exhibit landforms nested within landforms repeatedly down spatial scales. In Pasternack et al. ( 2018 ), a new, scale‐independent, hierarchical river classification was developed that uses five landform types to map the domains of a single fluvial process – flow convergence routing – at each of three–five spatial scales. Given those methods, this study investigated the details of how flow convergence routing organizes nested landform sequences. The method involved analyzing landform abundance, sequencing, and hierarchical nesting along the 35 km gravel/cobble lower Yuba River in California. Independent testing of flow convergence routing found that hydraulic patterns at every flow matched the essential predictions from classification, substantiating the process–morphology link. River width and bed elevation sequences exhibit large, nonrandom, and linked oscillations structured to preferentially yield wide bars and constricted pools at base flow and bankfull flow. At a flow of 8.44 times bankfull, there is still an abundance of wide bar and constricted pool landforms, but larger topographic drivers also yield an abundance of nozzle and oversized landforms. The nested structure of flow convergence routing landforms reveals that base flow and bankfull landforms are nested together within specific floodprone valley landform types, and these landform types control channel morphodynamics during moderate to large floods. As a result, this study calls into question the prevailing theory that the bankfull channel of a gravel/cobble river is controlled by in‐channel, bankfull, and/or small flood flows. Such flows may initiate sediment transport, but they are too small to control landform organization in a gravel/cobble river with topographic complexity. Copyright © 2018 John Wiley & Sons, Ltd.