热带气旋对黄、渤海影响的统计特征分析

本文统计分析了1949—2000年共52年影响黄、渤海的热带气旋时空分布特点及ENS0、西太平洋副热带高压与影响黄、渤海的热带气旋关系。结果表明，西太平洋热带气放以四种主要路径影响黄、渤海，其影响时间、频数及强度均有不同。ENSO和西太平洋副热带高压的强度、位置将影响热带气旋对黄、渤海影响的路径和频数。     

“深空大地测量导论”课程建设和教材编写的思考

介绍了"深空大地测量学导论"课程教材编写的背景、阐述了"深空大地测量学导论"教材编写的基本思路、总结了"深空大地测量学导论"教材的编写的特色.     

一种新的多通道GPS共视资料的处理算法

提出了一种按仰角加权的多通道GPS共视资料处理算法，充分利用了所有观测数据，同时抑制了多径等因素影响，从而可提高共视比对精度。对日本邮政省通讯研究所(CRL)和国家授时中心(NTSC)2002年5月～2003年3月的多通道共视比对的处理结果表明，新的处理算法结果更接近真实钟差。     

Spatial character of the gaseous and particulate state compound correlation of urban atmospheric pollution in winter and summer

The spatial/temporal variation information of atmospheric dynamic-chemical processes at observation site points of the "canopy" boundary of Beijing urban building ensemble and over urban area "surface", as well as the seasonal correlation structure of the gaseous and particulate states of urban atmospheric pollution (UAP) and its seasonal conversion feature at observation points are investigated, using the comprehensive observation data of the Beijing City Air Pollution Observation Experiment (BECAPEX) in winter and summer 2003 with a "point-surface" combined research approach. By using "one dimension spatial empirical orthogonal function (EOF)" principal component analysis (PCA) mode, the seasonal change of gaseous and particulate states of atmospheric aerosols and the association feature of pollutant species under the background of the complicated structure of urban boundary layer (UBL) are analyzed. The comprehensive analyses of the principal components of particle concentrations,gaseous pollutant species, and meteorological conditions reveal the seasonal changes of the complex constituent and structure features of the gaseous and particulate states of UAP to further trace the impact feature of urban aerosol pollution surface sources and the seasonal difference of the component structure of UAP. Research results suggest that in the temporal evolution of the gaseous and particulate states of winter/summer UAP, NOx, CO, and SO2 showed an "in-phase" evolution feature, however, O3 showed an "inverse-phase" relation with other species,all possessing distinctive dependent feature. On the whole, summer concentrations of gaseous pollutants CO, SO2, and NOx were obviously lower than winter ones, especially, the reduction in CO concentration was most distinctive, and ones in SO2 and NOx were next. However, the summer O3 concentration was more than twice winter one. Winter/summer differences in PM10and PM2.5 particle concentrations were relatively not obvious, which indicates that responses of PM10 and PM2.5 particle concentrations to the difference of winter/summer heating period emission sources are far less distinctive than those of NOx, SO2, and CO. The correlation feature of winter/summer gaseous and particulate states depicts that both PM10 and PM2.5 particles were significantly correlated with NOx, and their correlations with NOx are more significant than those with other pollutants. Through PCA, it is found that there was a distinctive difference in the principal component combination structure of winter/summer PM10 and PM2.5 particles: SO2 and NOx dominated in the principal component of winter PM10 and PM2.5 particles; while CO and NOx played the major role in the principal component of summer PM10 and PM2.5 particles. For winter/summer PM10 and PM2.5 particles, there might exist the gaseous and particulate states correlation structures of different "combinations" of such dependent pollutant species. Research results also uncover that the interaction processes of gaseous and particulate states were also related with the vertical structure of UBL, that is to say, the low value layer of UBL O3 concentration was associated with the collocation of atmospheric vertical structures of the low level inversion,inverse humidity, and small wind, which depicts summer boundary layer atmospheric character, i.e.the compound impact of the dependent factor "combination" of wind, temperature, and humidity elements and their collocation structure on the variations of different gaseous pollutant concentrations. Such a depth structure of the extremely low value of O3 concentration in the UBL accords with its "inverse-phase" relation with other gaseous pollutant species. The PCA of meteorological factors associated with PM10 and PM2.5 concentrations also reveals the sensitivity of PM10 and PM2.5 concentration to the combinatory feature of local meteorological conditions.     

A Case Study on the Occurrence and Mobility of the Shale Oil from the Muli Coalfield, Qilian Mountain

正Objective Shale oil occurs in free state(including condensate state),adsorption state(adsorbed on kerogen and mineral particles)and dissolved state(dissolved in natural gas,residual water,etc.)in shales and adjacent layers.The characterization of the occurrence of different hydrocarbons in shale oil,especially the quantitative     

电感耦合等离子体质谱法(ICP-MS)测定水系沉积物中的铌钽锆铪

建立电感耦合等离子体质谱法(ICP-MS)测定水系沉积物中铌、钽、锆、铪四种元素的分析方法。将样品与氢氧化钠、过氧化钠混合物放入高温炉中,熔融分解完全,用热水提取,过滤后弃去滤液,将滤纸及沉淀用酒石酸-盐酸溶液溶解,稀释至刻度测定。方法检出限(3s)为:LD(Nb)=0.08μg/g,LD(Ta)=0.04μg/g,LD(Zr)=0.5μg/g,LD(Hf)=0.04μg/g,精密度(RSD%,n=6)为:0.84%~4.21%。该测定方法具有灵敏度高、精密度好、分析速度快、线性范围宽、操作性强等优势。采用该方法对国家一级标准物质进行测定表明,其结果与标准值吻合。此方法已在实际地质调查样品分析中得到应用。     

山东海阳姜家白垩纪水南组化石的发现及保护

姜家位于山东省烟台海阳市北部。在进行烟台地区古生物化石调查的过程中,发现了姜家这一白垩纪水南组良好的露头剖面,在其页岩中赋存丰富的动植物化石,计有玉门延吉叶肢介、长壳延吉叶肢介、中华狼鳍鱼、松柏纲和银杏纲植物化石及昆虫化石。根据前人化石保护评价方法,结合化石的赋存层位、赋存条件、化石类型及保护现状,计算了海阳姜家质量综合指数,认为其属于重点保护区级别;最后根据当地自然情况及工程影响,圈定了保护区范围,并制定了相应的保护措施。     

大数据环境下内蒙古浩布高地区铅锌多金属矿智能矿产预测研究

传统机器学习算法已广泛应用于矿产预测,但面对地质大数据的高维稀疏、不平衡小样本等特性仍缺乏有效处理和分析的方法,设计适合地质大数据特点的机器学习算法是智能矿产预测亟需解决的新问题。本文以内蒙古浩布高地区的铅锌多金属矿产预测为例,提出了一种面向地质大数据的半监督协同训练矿产预测模型。首先对研究区地质找矿信息和地球化学异常信息进行定量分析,提取断裂构造、二叠系地层、燕山期侵入岩、地层与岩体接触带、围岩蚀变及Pb、Zn、Sn、Cu地球化学异常共9种找矿因子。然后利用递归特征消除法优选找矿因子组合,不包括Sn异常在内的8个找矿因子组合被选为最优组合。最后,利用支持向量机和随机森林算法作为基分类器进行半监督协同训练矿产预测,绘制成矿概率分布图。ROC曲线和预测度曲线分析结果表明,半监督协同训练模型的AUC值和预测效率都高于随机森林和支持向量机模型。研究结果也为大数据环境下的智能矿产预测提供了一种新的思路。     

基于高分二号卫星数据的煤矿区地质灾害信息提取研究

随着遥感数据获取技术和能力的全面提高,遥感数据呈现出明显的大数据特征。发展适应于遥感大数据的智能分析和信息挖掘技术,成为当前遥感技术研究的前沿。高分二号（GF-2）卫星数据是我国首颗自主研发的亚米级高分辨率卫星数据,具有观测幅宽、重访周期短、高辐射精度、高定位精度等优势,为未来我国地质灾害的长期、动态地监测和研究提供了高精度、稳定可靠的数据源。本文选取安徽谢桥煤矿2015年1月8日的GF-2卫星影像为研究数据,在对煤矿区主要地质灾害遥感地学分析的基础上,采用面向对象的影像分析方法对研究区由采煤活动所诱发的地质灾害信息进行自动提取。结果表明：利用GF-2卫星数据能够有效地识别地质灾害体的位置、范围、形态等空间分布特征;面向对象的自动提取方法对于煤矿区大面积的积水塌陷盆地、小规模的塌陷坑和线性的地裂缝都有很高的提取精度,识别精度达90% 以上;基于逐层剔除的思路构建的提取规则,为GF-2数据在地质灾害调查和大数据分析中的应用提供了很好的技术支持,也为其它地物目标的提取提供了参考,但在特征的选择和阈值的设定上需要具体分析。