Impact of mega-scale sand extraction on tidal dynamics in semi-enclosed basins: An idealized model study with application to the Southern North Sea

Long-term considerations of repeated and increasing sand extraction on the Netherlands Continental Shelf (North Sea) may lead to the creation of a mega-scale extraction trench in front of the Dutch coast (length hundreds of km, width over 10 km, depth several m). We investigate the impact of such a huge topographic intervention on tidal dynamics, which is a key aspect in hydrodynamics, and indirectly also affecting morphodynamics and ecology.     

地震活动性参数b值和年发生率的一种取值方法

介绍了一种将历史地震与现代小震统计结果相协调,去不可靠或不稳定数据段确定地震活动性参数ｂ值,以及通过不同震级下限地震频度的时间滑动分析,选取现今与历史相近,且具较高震级下限的统计结果,推算４级以上地震年发生度ｖ４的方法。计算给出了东南沿海地震带及其南带,北带的ｂ值和ｖ４值。     

海岸水边线提取方法在GF-2卫星影像中的适应性研究

准确提取海岸水边线是海岸线变迁研究中必不可少的基本工作。本文以海南省陵水黎族自治县2016年的GF-2影像为数据源,在大气校正和正射校正等预处理的基础上,结合数学形态学处理等方法,采用NDWI (Normalized Difference Water Index)阈值法、ISOADTA (Iterative Self-Organizing Data Analysis Technique Algorithm)、SVM (Support Vector Machine)和面向对象法（Object-Oriented Classification,OOC）等4种不同方法来对海岸水边线进行提取,并对其提取结果进行定性和定量评估,进而分析比较了这4种方法在提取人工海岸、砂质海岸和基岩海岸等3种不同海岸类型的水边线时的提取效果和提取精度。结果表明,SVM方法在3种海岸水边线上的总体提取效果最好,总体提取精度最高。     

尾砂库重金属元素表生地球化学行为的初探

通过重金属含量分析,分级提取化学形态分析,结合矿物成分和化学成分分析,对黄龙铺矿区1号尾矿库重金属元素在风化过程中的地球化学行为进行了研究。研究结果表明在横向上,尾矿库中心排水口处地势低洼,铜、铁因相对活泼易于迁移而流失,铅、锌、铬、镉在尾矿库四周的地表浅部淋失,在尾矿库中心则相对富集。化学形态分析表明尾砂中各重金属元素赋存状态各有不同,一般以T6原生硫化物态和T7残渣态为主,铜、锌、铁迁移性较强;其他则较弱,表明对环境威胁不是很大。重金属的迁移明显的分为氧化带和次氧化带,研究结果显示尾矿覆盖方法也不一定能够有效地阻滞污染元素的迁移。     

中国地震历史资料的信息开发与利用

本文对全国历史地震资料的有用信息作了进一步的开发和利用，按统一方法处理了大量有感以上地震的文字记载，确字每个独立地震的时间与地点；分区求得地震的有感区长半径与震级的关系式；确定了历史有感地震的最低震级为４；取得了８０００余次有感地震垢基本参数；用等震线测定了巨大地震的参数；将有感强震目录统编成全国与几个大区Ｍ≥４．０地震目录，按《地震学地震预报实用程序系统》（ＥＰＳＥＩＳ）的格式要求建库；同时编制     

Generalized plasticity state parameter‐based model for saturated and unsaturated soils. Part 1: Saturated state

The behavior of granular materials is known to depend on its loose or dense nature, which in turns depends both on density and confining pressure. Many models developed in the past require the use of different sets of constitutive parameters for the same material under different confining pressures. The purpose of this paper is to extend a basic generalized plasticity model for sands proposed by Pastor, Zienkiewicz and Chan by modifying the main ingredients of the model flow—rule, loading–unloading discriminating direction and plastic modulus—to include a dependency on the state parameter. The proposed model is tested against the available experimental data on three different sands, using for each of them a single set of material parameters, finding a reasonably good agreement between experiments and predictions. Copyright © 2010 John Wiley & Sons, Ltd.     

同位素信息确定Philip入渗模型稳定入渗率

通过流域水循环中各要素同位素含量的测定,扩大建模信息利用量,增加确定模型参数所需信息,提高参数可识别性,可在一定程度上减少参数的不确定性.以仅有两个参数且物理意义明确的Philip入渗模型为例,利用同位素信息确定Philip入渗模型参数稳定入渗率,并通过室内降雨入渗实验来检验同位素信息确定模型参数结果.结果表明,利用同位素信息确定的Philip入渗模型稳定入渗率与实测值接近.氢氧稳定同位素的分析精度对利用同位素信息确定模型参数结果有一定影响.     

地理国情普查时点核准作业方法探讨

通过核实从数据采集到标准时点阶段发生变化的内容,补充新增内容,消除普查前阶段由于资料时效性和外业局限性等导致的现势性不统一现象,对变化的地理国情信息进行核准,使地理国情普查数据成果在时间上达到统一,是开展地理国情监测的基础。     

TWR-01型天气雷达回波特征参数的提取和应用

TWR-01型天气雷达是小型数字化雷达,具备GIS和GPS功能,可适应移动式、固定式的增雨防雹作业指挥和气象保障服务.TWR-01型天气雷达回波特征参数的提取技术是基于影像的目标轮廓提取方法.目标轮廓提取方法在图像识别与图像分析中占有重要地位,广泛应用于测量和遥感领域.TWR-01型天气雷达同波特征参数提取的技术方法是...     

Novel Folded-PCA for improved feature extraction and data reduction with hyperspectral imaging and SAR in remote sensing

As a widely used approach for feature extraction and data reduction, Principal Components Analysis (PCA) suffers from high computational cost, large memory requirement and low efficacy in dealing with large dimensional datasets such as Hyperspectral Imaging (HSI). Consequently, a novel Folded-PCA is proposed, where the spectral vector is folded into a matrix to allow the covariance matrix to be determined more efficiently. With this matrix-based representation, both global and local structures are extracted to provide additional information for data classification. Moreover, both the computational cost and the memory requirement have been significantly reduced. Using Support Vector Machine (SVM) for classification on two well-known HSI datasets and one Synthetic Aperture Radar (SAR) dataset in remote sensing, quantitative results are generated for objective evaluations. Comprehensive results have indicated that the proposed Folded-PCA approach not only outperforms the conventional PCA but also the baseline approach where the whole feature sets are used.