面向矿产资源信息的空间关联性分析

关联性分析是综合多源、多类数据,发现和挖掘数据中潜在的相关关系,提取和挖掘数据之间的关联性。该方法对于充分利用地质大数据、发现地质要素之间的共生组合规律具有重要的意义。本文首先基于数据的空间位置,将不同类型的地质空间数据建立联系,形成空间属性数据库;其次应用统计方法,对不同来源数据中的属性特征进行分析,发现热液型金矿的形成与火山作用存在明显相关性;最后基于Apriori算法提取热液型金矿的伴生矿与侵入岩的频繁项集,发现伴生矿与侵入岩酸碱性二者密切相关。因此,在今后的工作中,有望应用空间关联性的方法对地球物理、地球化学、遥感等多源地质数据开展深入的研究分析。     

柴达木盆地鱼卡地区中侏罗统石门沟组砂岩碎屑组分特征及其物源构造环境分析

利用砂岩碎屑骨架成分统计和碎屑颗粒结构特征分析,研究柴达木盆地北缘鱼卡地区中侏罗统石门沟组碎屑岩的源岩类型及其构造环境。石门沟组砂岩成分成熟度中等、结构成熟度较低,具有近源物源的特点。砂岩碎屑骨架成分统计结果表明石门沟组的物源区构造背景属于再旋回造山带。结合柴达木盆地北缘中侏罗统古地理特征,确认鱼卡地区石门沟组物源区为祁连山造山带。砂岩碎屑组分可能来自于南祁连山上石炭世宗务隆山群火山岩和达肯达坂山群变质岩。     

长春地区粉质黏土导热系数与其物性参数相关性研究

为研究导热系数与影响因素之间的相关关系,建立导热系数的推算公式,以长春地区粉质黏土为研究对象,对原状土样的导热系数与其物理参数之间的相关性进行回归分析。制作9个重塑土样,测其相关的参数值,以验证回归方程的适用性。结果表明,回归分析建立导热系数与2个物理参数之间的关系式不成立;考虑天然密度、含水率和孔隙度为自变量,其分别对应的相关性系数T检验显著值(Sig)都0. 05,复决定系数为0. 886,建立的回归方程成立,自变量能准确解释因变量的变化,且含水率与导热系数呈负相关,天然密度和孔隙度呈正相关。重塑土样相关参数代入回归方程得到的导热系数值与实验实测值之间相对误差低于4%,验证了该回归方程的普遍性和适用性。     

云南个旧多金属矿石门坎—保和地区Sn、Sb元素的成矿信息识别与提取

石门坎—保和地区位于云南个旧多金属成矿区西南部,成矿背景复杂,成矿作用具有多期性和多样性。利用研究区1∶1万土壤化探数据,采用泛克里格法和因子分析相结合的方法,提取不同层次的成矿异常信息。结果表明:主因子F_3包含Mo-Au-Sb等元素,反映成矿过程中的岩体和热液相关信息;主因子F_4包含Sn-Bi-W元素,指示中低温热液矿化环境; Sb沿杨家田断裂呈串珠状分布,反映了由北东向构造控制的空间变化特征,与已知矿点对应良好; Sn元素异常在研究区北部呈双峰状环形分布,推测受隐伏岩体或者断层控制。根据元素组合异常F_3和F_4的分布规律,结合地质资料圈定出2个找矿靶区,为进一步找矿工作提供了方向。     

页岩压裂影响因素三维模型数值分析

不同影响因素对页岩水力压裂效果有不同的影响。基于三维数值计算模型介绍了水力压裂的典型过程,针对水平最小主应力、页岩的弹性模量和渗透系数对压裂的影响进行了分析。结果表明:随着水平最小主应力的增加,裂缝高度也随之增加;随着页岩的弹性模量增加,裂缝的高度随之降低;随着渗透系数的增加,裂缝高度也随之增加;随着压裂液的黏度系数提高,裂缝的高度降低。     

Objective Analysis on Large-scale Circulation Type and Its Links to Precipitation over China

Atmospheric circulation anomaly is a direct cause of weather and climate change. In the past, most researches for the relationship between Weather Type (WT) and precipitation have mainly focused on the subjective classification and diagnosis. Compared to the subjective analysis, objective classification uses more consistent index and standard unification, thus, we can get more WTs, and it has been widely used in many areas. By using daily 12UTC Sea Level Pressure (SLP), Precipitable Water (PW), and 700 hPa wind speed (UV700) data from ECMWF’s Interim Reanalysis, the classification of WTs over China was performed with the method of obliquely rotated T-mode principle component analysis. WT and its link to precipitation over China were further analyzed. The results show that the influence of different WTs on precipitation is not uniform over China, and also show distinctly difference in different seasons. A common feature is that WTs great impact on the regions and months with large precipitation, while less impact on regions and months have with less precipitation. In addition, precipitation trends originating from WT intensity changes are much more deterministic, significant, and predictable than trends from WT frequency changes.     

三峡库区四方碑滑坡稳定性与变形趋势预测

三峡水库建成后,库水位周期性涨落和暴雨产生的渗流作用导致大量古滑坡的复活或新滑坡的发生。以库区近水平层状结构的四方碑滑坡为例,依据库水位实际调动,将水位从175 m至145 m不同降速与50年一遇暴雨进行工况组合,计算4种工况下滑坡的稳定性及破坏概率。然后采用Geo-studio软件的Sigma模块对滑坡进行变形模拟,运用R/S分析方法判断滑坡的变形持续性,并结合野外调查情况,综合评价分析四方碑滑坡的稳定性。结果表明:滑坡在各工况下整体均处于基本稳定状态,具有低危险性;变形模拟结果显示滑坡前缘位移最大,与野外调查情况一致;各监测点Hurst指数均介于0.5~1,表明时间序列具有正持续性,在研究的时间限度内滑坡的局部破坏增强,应在汛期加强对滑坡前缘的巡查和预警。     

基于小波分析与Mann-Kendall法的岩溶大泉动态研究

研究地下水动态是认识地下水资源的有效手段。根据1956－2013年济南岩溶泉域大气降水及地下水水位动态监测资料,采用小波分析法、Mann-Kendall趋势检验、突变检验法研究了58个水文年泉水位对大气降水的响应,可以看出:（1）大气降水和泉水位呈现出多尺度的变化特征,长时间尺度上两者的变化周期基本相同,变化周期为16年和12年,说明大气降水对泉水位有直接影响;（2）在1956—2013年,济南泉域地下水水位具有0.65 m·（10a）-1的年际显著下降趋势,但降水具有12.65 mm·（10a）-1的不显著上升趋势,说明在人为因素影响下泉水动态的影响因素的权重发生了变化;（3）大气降水在1999年发生突变,1999年之后年降水为增加趋势;而地下水水位突变年份为1967年,1967年以后水位持续降低,2004年以后水位快速上升,泉水位未来趋势应与降水保持一致,呈上升趋势,说明大气降水并非泉水动态的唯一影响因素;（4）通过建立不同时段的多元回归模型,表明近58年来地下水水位的主要影响因素由大气降水到人工开采之间的转换,同时验证了小波分析和Mann-Kendall法研究地下水动态的适宜性和可靠性,也为济南市的保泉提供了参考依据。      

Evaluation of effectiveness of three fuzzy systems and three texture extraction methods for building damage detection from post-event LiDAR data

Building damage maps after disasters can help us to better manage the rescue operations. Researchers have used Light Detection and Ranging (LiDAR) data for extracting the building damage maps. For producing building damage maps from LiDAR data in a rapid manner, it is necessary to understand the effectiveness of features and classifiers. However, there is no comprehensive study on the performance of features and classifiers in identifying damaged areas. In this study, the effectiveness of three texture extraction methods and three fuzzy systems for producing the building damage maps was investigated. In the proposed method, at first, a pre-processing stage was utilized to apply essential processes on post-event LiDAR data. Second, textural features were extracted from the pre-processed LiDAR data. Third, fuzzy inference systems were generated to make a relation between the extracted textural features of buildings and their damage extents. The proposed method was tested across three areas over the 2010 Haiti earthquake. Three building damage maps with overall accuracies of 75.0%, 78.1% and 61.4% were achieved. Based on outcomes, the fuzzy inference systems were stronger than random forest, bagging, boosting and support vector machine classifiers for detecting damaged buildings.     

Quantifying land use/land cover spatio-temporal landscape pattern dynamics from Hyperion using SVMs classifier and FRAGSTATS®

This study aims to quantify the landscape spatio-temporal dynamics including Land Use/Land Cover (LULC) changes occurred in a typical Mediterranean ecosystem of high ecological and cultural significance in central Greece covering a period of 9 years (2001–2009). Herein, we examined the synergistic operation among Hyperion hyperspectral satellite imagery with Support Vector Machines, the FRAGSTATS^® landscape spatial analysis programme and Principal Component Analysis (PCA) for this purpose. The change analysis showed that notable changes reported in the experimental region during the studied period, particularly for certain LULC classes. The analysis of accuracy indices suggested that all the three classification techniques are performing satisfactorily with overall accuracy of 86.62, 91.67 and 89.26% in years 2001, 2004 and 2009, respectively. Results evidenced the requirement for taking measures to conserve this forest-dominated natural ecosystem from human-induced pressures and/or natural hazards occurred in the area. To our knowledge, this is the first study of its kind, demonstrating the Hyperion capability in quantifying LULC changes with landscape metrics using FRAGSTATS^® programme and PCA for understanding the land surface fragmentation characteristics and their changes. The suggested approach is robust and flexible enough to be expanded further to other regions. Findings of this research can be of special importance in the context of the launch of spaceborne hyperspectral sensors that are already planned to be placed in orbit as the NASA’s HyspIRI sensor and EnMAP.