固体矿产储量估算系统的研究与实现

通过对固体矿产储量估算过程的详细调研,对储量估算过程中的单工程圈定算法、矿体剖面连接以及传统的储量估算方法中的平行剖面法和地质块段法做了详细研究,并针对储量计算的可视化及交互技术进行了研究,实现了一种基于Windows操作系统、MapGIS地理信息系统平台的固体矿产储量估算原型系统,实现了对固体矿产勘查数据的有效存储、管理、可视化分析及评价。     

基于自适应参数估计的多时相遥感图像变化检测

提出一种基于自适应参数估计实现多时相遥感图像的变化检测算法.首先应用分层Markov随机场模型建立多时相差分图像的统计模型;然后通过非监督的迭代自适应参数估计实现差分图像的分类,从而检测出变化的像元.在每次参数估计过程中,先将上次估计出的参数用于最大后验估计实现差分图像的分类,然后根据分类结果再对参数进行修正,并将修正后的参数用于下一次迭代分类,如此循环迭代,能够自适应地完成差分图像的参数估计与分类.     

静力平衡近似下大气中非线性对称运动的稳定性、分岔和突变

本文在考虑基本气流具有非线性切变情况下,导出了对称运动所满足的非线性常微分方程,并用非线性系统的稳定、分岔、突变理论,严格地讨论了非线性对称运动的稳定性、分岔和突变问题,获得了一个推广的对称不稳定判据,找到了突变产生的条件。     

Improved seismic risk estimation for Bucharest,based on multiple hazard scenarios and analytical methods

Bucharest, capital of Romania, is one of the most exposed big cities in Europe to seismic damage, due to the intermediate-depth earthquakes in the Vrancea region, to the vulnerable building stock and local soil conditions.This paper tries to answer very important questions related to the seismic risk at city scale that were not yet adequately answered. First, we analyze and highlight the bottlenecks of previous risk-related studies. Based on new researches in the hazard of Bucharest (recent microzonation map and ground-motion prediction equations, reprocessed real recorded data) and in vulnerability assessment (analytical methods, earthquake loss estimation software like SELENA and ELER, the recently implemented Near Real-Time System for Estimating the Seismic Damage in Romania) we provide an improved estimation of the number of buildings and population that could be affected, for different earthquake scenarios. A new method for enhancing the spatial resolution of the building stock data is used successfully.     

自适应虚同相轴方法压制地震层间多次波

地震数据中发育的层间多次波是影响速度分析和偏移成像的精度和可靠性的关键.通常情况下,层间多次波的动校正量、叠加速度和频率与一次波并无明显差异,从而对识别、预测和压制多次波带来了极大挑战.传统虚同相轴方法基于物理图像和定性公式,其预测的层间多次波振幅和相位精度难以满足实际需求,造成了其对匹配算法的过度依赖.本文针对传统虚同相轴方法的理论缺陷和计算精度问题,通过理论推导得到了新的自适应虚同相轴方法.相比于传统方法,自适应虚同相轴方法能够显著提高压制多次波能力,同时减少对匹配算法的依赖.本文给出了自适应虚同相轴方法的推导过程,并运用一维和二维模型算例验证了方法相较于传统虚同相轴方法的多次波预测精度优势.通过在PLUTO模型和实际陆地地震数据上的应用实例,证明了本文新研究的自适应虚同相轴方法对去除层间多次波,恢复并突出目标储层同相轴,提高地震成像分辨率的显著作用.

     

Investigating the propagation mechanism of unmodelled systematic errors on coordinate time series estimated using least squares

The propagation of unmodelled systematic errors into coordinate time series computed using least squares is investigated, to improve the understanding of unexplained signals and apparent noise in geodetic (especially GPS) coordinate time series. Such coordinate time series are invariably based on a functional model linearised using only zero and first-order terms of a (Taylor) series expansion about the approximate coordinates of the unknown point. The effect of such truncation errors is investigated through the derivation of a generalised systematic error model for the simple case of range observations from a single known reference point to a point which is assumed to be at rest by the least squares model but is in fact in motion. The systematic error function for a one pseudo-satellite two-dimensional case, designed to be as simple but as analogous to GPS positioning as possible, is quantified. It is shown that the combination of a moving reference point and unmodelled periodic displacement at the unknown point of interest, due to ocean tide loading, for example, results in an output coordinate time series containing many periodic terms when only zero and first-order expansion terms are used in the linearisation of the functional model. The amplitude, phase and period of these terms is dependent on the input amplitude, the locations of the unknown point and reference point, and the period of the reference point's motion. The dominant output signals that arise due to truncation errors match those found in coordinate time series obtained from both simulated data and real three-dimensional GPS data.     

Method of Data Reduction and Uncertainty Estimation for Platinum-Group Element Data Using Inductively Coupled Plasma-Mass Spectrometry

A data reduction method is described for determining platinum-group element (PGE) abundances by inductively coupled plasma-mass spectrometry (ICP-MS) using external calibration or the method of standard addition. Gravimetric measurement of volumes, the analysis of reference materials and the use of procedural blanks were all used to minimise systematic errors. Internal standards were used to correct for instrument drift. A linear least squares regression model was used to calculate concentrations from drift-corrected counts per second (cps). Furthermore, mathematical manipulations also contribute to the uncertainty estimates of a procedure. Typical uncertainty estimate calculations for ICP-MS data manipulations involve: (1) Carrying standard deviations from the raw cps through the data reduction or (2) calculating a standard deviation from multiple final concentration calculations. It is demonstrated that method 2 may underestimate the uncertainty estimate of the calculated data. Methods 1 and 2 do not typically include an uncertainty estimate component from a regression model. As such models contribute to the uncertainty estimates affecting the calculated data, an uncertainty estimate component from the regression must be included in any final error calculations. Confidence intervals are used to account for uncertainty estimates from the regression model. These confidence intervals are simpler to calculate than uncertainty estimates from method 1, for example. The data reduction and uncertainty estimation method described here addresses problems of reporting PGE data from an article in the literature and addresses both precision and accuracy. The method can be applied to any analytical technique where drift corrections or regression models are used.     

利用参考图像的遥感图像模糊估计与恢复

提出一种新的利用参考图像的模糊估计与恢复方法。同一场景不同时相的图像,由于拍摄条件的不同,清晰化程度也往往不同,将高质量的图像作为参考,为模糊估计和恢复提供先验知识,在Bayes统一的框架内进行快速PSF估计,然后使用总变分最小化方法进行恢复。通过真实遥感图像实验,结果表明所提出的方法可以有效地估计退化模糊、恢复未失真图像。     

Defining dynamic pelagic habitats in oceanic waters off eastern Australia

Although many species in the pelagic ocean are widespread, they are not randomly distributed. These species may have associations with particular water masses or habitats, but to best understand patterns in the ocean, these habitats must be identified. Previous efforts have produced static or seasonal climatologies, which still represent smearing over habitats. The Eastern Tuna and Billfish Longline Fishery (ETBF) targets a range of high trophic level species in oceanic waters off eastern Australia. In this study, dynamic ocean habitats in the region were identified for each month based on cluster analysis of five oceanographic variables averaged at a monthly time scale and a spatial scale of 0.5° for the period 1995-2006. A total of seven persistent habitats were identified off eastern Australia with intra and interannual variation in size and location, indicating the importance of spatial and temporal variation in the dynamics of the region. The degree to which these dynamic habitats were distinguished was tested using (i) stable isotope analysis of top fish predators caught in the region and (ii) estimates of variation in estimated abundance generated from catch data from the fishery. More precise estimates (measured as lower total CV) of isotopic values from swordfish (Xiphias gladius), yellowfin tuna (Thunnus albacares) and albacore (Thunnus alalunga) were obtained for 4 of 6 isotope comparisons using the dynamic habitat groupings, which indicate that stratifying by pelagic habitat improved precision. Dynamic habitats produced more precise abundance estimates for 7 of 8 large pelagic species examined, with an average reduction in total CV of 19% compared to when abundance was estimated based on static habitat stratification. These findings could be used to guide development of effective monitoring strategies that can distinguish patterns due to environmental variation, and in the longer term, climate change.     

基于高光谱遥感反射比的太湖水体叶绿素a含量估算模型

旨在寻找叶绿素a的高光谱遥感敏感波段并建立其定量估算模型。通过对太湖水体的连续监测，获得了从2004年6月到8月3个月的太湖水体高光谱数据和水质化学分析数据。利用实测的高光谱数据分析计算太湖水体的离水辐亮度和遥感反射比；然后，通过相关分析寻找反演叶绿素a浓度的高光谱敏感波段，进而建立反演太湖水体叶绿素a浓度的高光谱遥感定量估算模型，并用相关数据对模型进行精度分析。研究发现，水体的遥感反射比光谱在719nm和725nm存在两个峰，其中719nm处的峰更明显且稳定。通过模型的对比分析，发现用这两个峰值处的遥感反射比参与建模可以提高叶绿素a的估算精度；并且认为由反射比比值变量R719／R670所建立的线性模型对叶绿素a浓度的估算精度最理想。