航空摄影最佳曝光量的选择

分解力是评定影象质量的重要指标。本文介绍利用改进后的国产9 w测微密度仪,测定航空软片静态分解力与曝光量的关系。以最大分解力所相应的曝光量作为确定航摄软片感光度的基准,以此为基础,确定航摄底片的最大密度( D _max )、最小密度( D _min )、影象反差(△ D )和平均密度( D _R )本文对国产1022T、1022P、柯达2402、2412等航摄软片进行了研究,其试验结果可作为今后修改航摄规范的基础。     

Primary cracking of kerogens. Experimenting and modelling C1, C2–C5, C6–C15 and C15+ classes of hydrocarbons formed

Mathematical models of hydrocarbon formation can be used to simulate the natural evolution of different types of organic matter and to make an overall calculation of the amounts of oil and/or gas produced during this evolution. However, such models do not provide any information on the composition of the hydrocarbons formed or on how they evolve during catagenesis.From the kinetic standpoint, the composition of the hydrocarbons formed can be considered to result from the effect of “primary cracking” reactions having a direct effect on kerogen during its evolution as well as from the effect of “secondary cracking” acting on the hydrocarbons formed.This report gives experimental results concerning the “primary cracking” of Types II and III kerogens and their modelling. For this, the hydrocarbons produced have been grouped into four classes (C₁, C₂–C₅, C₆–C₁₅ and C₁₅₊). Experimental data corresponding to these different classes were obtained by the pyrolysis of kerogens with temperature programming of 4°C/min with continuous analysis, during heating, of the amount of hydrocarbons corresponding to each of these classes.The kinetic parameters of the model were optimized on the basis of the results obtained. This model represents the first step in the creation of a more sophisticated mathematical model to be capable of simulating the formation of different hydrocarbon classes during the thermal history of sediments. The second step being the adjustment of the kinetic parameters of “secondary cracking”.     

基于Erdas Image 9.2 LPS区域网平差处理Spot5卫星影像实现方法

介绍基于LPS的正射影像处理流程,以图文的形式描述区域网平差处理Spot-5卫星影像的具体过程,最后得到正射纠正影像,用于1∶50 000DOM生产。     

稀疏信号恢复理论在CT图像重建中的应用

新的图像重建算法一直是CT成像前沿研究中的热点问题之一,而实际中常常遇到的有限角度重建问题则是其中的难点.Terence Tao和他的同事提出了一种稀疏信号恢复理论,为解决这个问题提出了可能的应用策略.我们在本文中介绍了这个理论并给出了在锥束CT重建中应用的初步结果.这种理论和策略的实现对很多应用情况都有重要的意义,为该领域的发展开辟了新的方向,也必将对该领域的发展产生重大影响.     

控制点影像库在遥感影像几何纠正中的应用

影像几何纠正是遥感图像处理的重要技术。为了克服现有方法在实际应用中的不足,提出利用控制点影像库进行影像自动匹配,然后进行几何变化的方式。这种方法简单有效,快速稳定,匹配得到的同名点数量足够且分布均匀,并通过引入最小二乘匹配使配准达到子像素精度,提高几何纠正的速度与可靠性。     

Study on projection of water resources of Dongting Lake catchment based on emission scenarios assumptions

ABSTRACT

With global climate change and impacts of human activity, the water cycle, which has a close relationship with local water resources, has changed rapidly. Based on different greenhouse gas emission scenarios, five relatively independent global climate models are selected from 47 CMIP5 models to simulate future climatic conditions. Data are downscaled to the local projection, with bias neutralized before applying them to the hydrological models, by which availability of future water resources are calculated for the Dongting Lake basin. The results show that the water resources of the Dongting Lake basin are likely to increase in the future, but be distributed more unevenly. All scenarios indicate that water availability will increase during the flood season and decrease during the dry season, with a prominent increase in annual discharge. The scenarios also predict that the greater the greenhouse gas emissions, the more uneven the water distribution becomes. Overall, the water resources of the Dongting Lake catchment show the same increasing and unevenly distributed trend in the future, which could be further accelerated by human activities.

Editor Z.W. Kundzewicz; Associate editor Q. Zhang     

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。     

胶州湾浮游植物遗传多样性及其季节变化研究

分别于春、夏、秋三季提取了胶州湾浮游生物总DNA,用PCR方法扩增了浮游植物核酮糖1,5-二磷酸羧化/氧化酶大亚基(rbcL)基因片段,构建了三季节rbcL基因片段质粒文库.随机从各文库中选择约50个克隆,测定了这些克隆的序列.以氨基酸序列相同为标准,共获得59个分类操作单元(OTUs),其中春季特有的21个,夏季特有的13个,秋季特有的23个.有两个OTUs为春、夏季表层海水共有.基于OTU丰度计算的香农氏指数能反映遗传多样性水平.胶州湾春、夏、秋三季的香农氏指数分别为2.69,2.44和2.76,表明秋季胶州湾浮游植物遗传多样性最丰富.春、夏、秋三季浮游植物群落组成差异显著.除夏秋季有两个OTUs相同外,其他OTUs在季节间完全不同.表层海水浮游植物群落结构是动态的,随时间、空间的不同而变化.     

基于植被指数的高光谱遥感水陆识别方法初探

提出了一种判别两类地物分类效果的依据——显著性度量,并采用植被指数的形式,给出了应用高光谱图像进行水陆识别的方法。以滩涂为例进行水陆识别实验,结果表明,基于显著性度量遴选得到的最佳植被指数类型及其最佳波段组合,适合于解决以高光谱图像为数据源的水陆识别问题。     

Prediction of Seaward Slope Recession in Berm Breakwaters Using M5'' Machine Learning Approach

In the design process of berm breakwaters, their front slope recession has an inevitable rule in large number of model tests, and this parameter being studied. This research draws its data from Moghim’s and Shekari’s experiment results. These experiments consist of two different 2D model tests in two wave flumes, in which the berm recession to different sea state and structural parameters have been studied. Irregular waves with a JONSWAP spectrum were used in both test series. A total of 412 test results were used to cover the impact of sea state conditions such as wave height, wave period, storm duration and water depth at the toe of the structure, and structural parameters such as berm elevation from still water level, berm width and stone diameter on berm recession parameters. In this paper, a new set of equations for berm recession is derived using the M5'' model tree as a machine learning approach. A comparison is made between the estimations by the new formula and the formulae recently given by other researchers to show the preference of new M5'' approach.