基于贝叶斯模型的器测、古气候重建与气候模拟数据的融合试验

气象部门馆藏的西部最早的器测气象资料始于20世纪30年代,不能满足建立20世纪以来中国气候变化序列的需求,而古气候重建或气候模拟资料则可以延伸到器测时代以前。为了探讨长序列多源气候资料序列融合方法,采用贝叶斯方法对中国北疆地区8条树轮气温重建资料、器测资料与国际耦合模式比较计划第5阶段（CMIP5）模式模拟资料进行了融合试验。首先利用器测资料对气温代用资料进行校验与网格重建,并以此作为贝叶斯模型的先验分布,然后,用泰勒图选出了该区域气候模拟效果最佳的几个模式;最后将网格重建和气候模拟序列用贝叶斯模型进行了融合试验。结果表明,贝叶斯融合模型能有效提取各种数据来源的有用信息进行融合,融合结果的长期变化（线性）趋势更接近器测气候序列,并在一定程度上提高了序列的精度,减小了结果的不确定性;并且,融合结果能够纠正先验分布及气候模拟数据的明显偏差,为长年代气候序列重建提供了一个可行的思路。      

Biochemical‐genetic and meristic evidence that blue and copper moki (Teleostei: Latridae: Latridopsis) are discrete species

Specimens of blue moki Latridopsis ciliaris (Forster in Bloch & Schneider, 1801) from New Zealand were shown to differ from specimens of copper moki Latridopsis forsteri (Castelnau, 1872) using two genetic methods—allozymes and muscle proteins. Allozyme techniques revealed fixed differences between blue and copper moki at 4 out of 15 loci. There was a genetic distance of 0.31–0.34 between population samples of the two colour morphs. The two morphs were also distinguished by iso‐electric focusing of muscle proteins. Meristic characters, counted in the specimens studied with genetic markers, revealed diagnostic markers in tubed lateral line scales and scales in the lower transverse series. It is concluded that specimens of blue moki from New Zealand and copper moki from New Zealand and Tasmania are valid species.     

Optical detection of Prorocentrum donghaiense blooms based on multispectral reflectance

Prorocentrum donghaiense is one of the most common red tide causative dinoflagellates in the Changjiang （Yangtze） River Estuary and the adjacent area of the East China Sea. It causes large-scale blooms in late spring and early summer that lead to widespread ecologic and economic damage. A means for distinguish- ing dinoflagellate blooms from diatom （Skeletonema costatum） blooms is desired. On the basis of measure- ments of remote sensing refectance [Rrs（λ）] and inherent optical parameters, the potential of using a mul- tispectral approach is assessed for discriminating the algal blooms due to P. donghaiense from those due to S. costatum. The behavior of two reflectance ratios [R1 = Rrs（560）/Rrs（532） and Re = Rrs（708）/Rrs（665）], suggests that differentiation of P. donghaiense blooms from diatom bloom types is possible from the current band setup of ocean color sensors. It is found that there are two reflectance ratio regimes that indicate a bloom is dominated by P. donghaiense; （1） R1 〉 1.55 and R2 〈 1.0 or （2） R1 〉 1.75 and R2 ≥ 1.0. Various sensitivity analyses are conducted to investigate the effects of the variation in varying levels of chlorophyll concentration and colored dissolved organic matter （CDOM） as well as changes in the backscattering ratio （bbp/bp） on the efficacy of this muitispectral approach. Results indicate that the intensity and inherent op- tical properties of the algal species explain much of the behavior of the two ratios. Although backscattering influences the amplitude of Rrs（λ）, especially in the 530 and 560 nm bands, the discrimination between P. donghaiense and diatoms is not significantly affected by the variation of bbp/bp. Since aCDOM （440） in coastal areas of the ECS is typically lower than 1.0 m-1 in most situations, the presence of CDOM does not interfere with this discrimination, even as SCDOM varies from 0.01 to 0.026 nm-1. Despite all of these effects, the dis- crimination of P. donghaiense blooms from diatom blooms based on multispectral measurements of Rrs（λ） is feasible.     

山东某铁矿区地面塌陷成因判别及其意义

山东省济南市东郊某在建铁矿,于2009年7月产生了严重的地面塌陷。通过环境地质调查发现,该矿区地面塌陷并非通常所说的采空区塌陷,而是岩溶地面塌陷。该结论为矿山地面塌陷防治提供了依据,更重要的是否定了第四系厚度大(大于35m)不能产生岩溶地面塌陷的已有认识,并预示隐伏岩溶发育地区,随着上覆松散土体厚度的加大,一旦产生岩溶地面塌陷,其规模和危害也将随之增大。     

灰色关联度法和距离判别分析法在溪洛渡库区潜在滑坡判识中的应用

以溪洛渡库区深入研究的14个典型滑坡为研究对象,在初步建立潜在滑坡判识指标的基础上,运用灰色关联度理论优选确定了影响库区潜在滑坡孕育的8个关键主控因素:坡面平均坡度、滑体内冲沟切割程度、洼地封闭状况(或排水条件)、滑面平均倾角、滑面形态、下滑段长度与总滑面长度之比、滑体结构及近期活动迹象,并依据距离判别分析的理论和方法,建立了溪洛渡库区潜在滑坡的距离判识模型。该判识模型对库区5个待判滑坡样本和9个滑坡学习样本的判识准确率均达到了100%。     

基于贝叶斯网络的地下水环境系统决策管理研究

应用贝叶斯网络解决地下水环境管理中具有不确定性的多目标决策问题,通过对决策变量氮肥施用量以及灌溉模式的调控,减少水中的硝酸盐含量,达到既能有效改善水环境又不至使农民经济利益受到损害的目标。通过分析具体的地下水环境管理系统中变量间的相互关系,构建描述变量间不确定性关系的贝叶斯网络模型,其中包括表示其依赖关系的有向无环图和表示其具体概率依赖程度的条件概率表。并在多个水环境管理目标均达到最优的前提下进行概率推理,得到决策变量氮肥施用量以及灌溉模式取不同值时目标变量的概率分布情况。最终确定出能使所有目标均达到最优的合理的水环境管理决策:(1)使用喷灌,将氮肥施用量控制在0.01~0.03 kg/m2;(2)使用漫灌,将氮肥施用量控制在0.01~0.02 kg/m2。     

天津市潮间带柱状沉积物中重金属的污染历史及来源判别

利用因子分析和元素含量特征分析两种方法,对天津市潮间带的4个无扰动沉积物柱样的46个样品进行了重金属分析,并探讨了重金属的来源方式和富集原因。研究结果表明,天津市潮间带的重金属可分为3类:1)Fe、Cr、Al及Mn元素主要受环境背景值的影响,2)Hg和Cd受人为活动的影响较大,3)As、Zn、Pb、Cu及Ni受环境背景值及人类活动的双重影响,且影响大小随所在位置的不同而变化。结合210Pb和137Cs测年结果,定量确定了天津市潮间带小于0.063 mm粒级沉积物中Ni等11种重金属元素的环境背景值,并以此为基础,进一步探讨了重金属富集年代、富集量及污染历史和人类活动的关系,发现多数重金属的污染始于1910年代,并在1954年之后富集量增加。     

Semisupervised heterogeneous ensemble for ship target discrimination in synthetic aperture radar images

Ship detection using synthetic aperture radar (SAR) plays an important role in marine applications. The existing methods are capable of quickly obtaining many candidate targets, but numerous non-ship objects may be wrongly detected in complex backgrounds. These non-ship false alarms can be excluded by training discriminators, and the desired accuracy is obtained with enough verified samples. However, the reliable verification of targets in large-scene SAR images still inevitably requires manual interpretation, which is difficult and time consuming. To address this issue, a semisupervised heterogeneous ensemble ship target discrimination method based on a tri-training scheme is proposed to take advantage of the plentiful candidate targets. Specifically, various features commonly used in SAR image target discrimination are extracted, and several acknowledged classification models and their classic variants are investigated. Multiple discriminators are constructed by dividing these features into different groups and pairing them with each model. Then, the performance of all the discriminators is tested, and better discriminators are selected for implementing the semisupervised training process. These strategies enhance the diversity and reliability of the discriminators, and their heterogeneous ensemble makes more correct judgments on candidate targets, which facilitates further positive training. Experimental results demonstrate that the proposed method outperforms traditional tri-training.     

CSD和CDD结合下的最优遥感特征指数集构建及其在湿地信息提取中的应用

依托中分辨率成像光谱仪完整的数据序列和丰富的光谱信息,遥感特征指数在湿地生态系统发展变化的状态、趋向和规律研究方面发挥着不可替代的优势。传统类间距离判别的遥感特征指数选取中常存在过分依赖数据统计特征、入选指数与目标地类间生态学意义不明确、分类模型普适性差等局限性。基于此,本研究以河北省白洋淀湿地自然保护区为例,提出类可分离性距离判别（Class Separation Discrimination,CSD）与类间距离判别（Class Distance Discrimination,CDD）相结合的方法构建最优遥感特征指数集,并采用QUEST算法和马氏距离判别法构建分类决策树模型用于白洋淀湿地信息的提取研究,尝试克服传统类间距离指数选取中的不足。结果表明：运用CSD和CDD相结合的方法所选取的遥感特征指数在研究区湿地信息提取过程中的总体分类精度达到了91.32%,Kappa系数0.88,较传统的分类与回归树（Classification and Regression Tree,CART）方法,分类精度提高了1.67%;其次选取的最优指数与待提取的湿地类型均具有明确的生态学意义,如挺水植物在立地干湿交替条件下的潴育化过程决定了氧化铁比率IO可成功的将混分的耕地和挺水植物进一步分离;进一步将基于研究区2017年OLI影像构建的CSD和CDD相结合方法与CART方法的模型分别应用于研究区2019年OLI影像进行分类,基于CSD和CDD相结合方法构建的模型分类总体精度和Kappa系数分别为：86.97%、0.83,基于CART方法构建的模型无法满足分类需求,研究结果较好地证明了基于CSD和CDD相结合方法构建的模型在年际之间具有良好的适用性和稳定性。总之,CSD和CDD相结合的方法在不降低湿地信息提取精度的基础上,有效避免了传统遥感特征指数选择方法的局限性,提高了分类模型的普适性,是遥感特征指数选择算法和决策树相结合在湿地信息提取方面的有益尝试。     

东昆仑得尔龙地区华力西期花岗岩地质地球化学特征及构造环境分析

东昆仑得尔龙地区花岗岩体侵位于二叠纪—三叠纪早期,岩石类型为黑云母花岗闪长岩、黑云母二长花岗岩、二云母二长花岗岩。早期次的黑云母花岗闪长岩中含有暗色的镁铁质矿物包体。SiO2含量为65.04%~73.47%,全碱含量为5.29%~8.52%,K2O/Na2O平均值为0.70,Al2O3平均为14.79%;亏损高场强元素Ta,Nb;∑REE平均为142.9×10-6,轻稀土元素相对富集,(La/Yb)N平均为17.15,δEu平均为0.71,表现为弱亏损。研究表明得尔龙地区花岗岩属次铝-过铝(高钾)钙碱性S型花岗岩,形成于后造山环境;岩浆源区的物质是多源的,主要为地壳物质的重熔,其次为幔源岩浆的底侵。