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。     

全球N-MORB和E-MORB分类方案对比

N-MORB与E-MORB是大洋中脊玄武岩常用的分类,二者地球动力学意义不同,备受学术界关注。对于N-MORB与E-MORB的分类识别标志,不同作者有不同的见解。MORB中可以根据Rb/Nd≤0.15、K/Ti≤0.11、(La/Sm)_N≤0.8、K_2O/TiO_20.09、ΔNb=1.74+lg(Nb/Y)-1.92lg(Zr/Y)0、(La/Sm)_N1、100K_2O/TiO_2≤13等7种指标来识别N-MORB,否则为E-MORB。究竟何种标志区分效果较好、比较适合大多数MORB的情况?学术界对此还较少有人讨论。为此,本文尝试利用大数据方法,采用全球全体扩张中心数据,对上述7种标志进行对比,发现(La/Sm)_N1的标志比较适合大多数MORB的情况。为此,我们将(La/Sm)_N1和(La/Sm)_N≥1的所有数据,选取La、Ce、Pr、Nd、Sm、Eu、Gd、Tb、Dy、Ho、Er、Tm、Yb、Lu、Ba、Cs、Hf、K、Nb、Pb、Rb、Sc、Sr、Ta、Th、Ti、Tl、U、V、Y、Zr等31个元素,利用两两元素对数比值进行投图,并计算85%置信度的置信椭圆交叠率,共得出36856个元素对组合,根据最小交叠率的原则,得出使用稀土元素La、Ce、Pr、Sm和其他高场强元素Nb、Zr、Hf、Y之间的比值关系判别效果较好。我们又利用以上得出的8种元素进行投图判定,发现以La为分子或以La/Hf、La/Zr元素比值做为区分标志可以得出更好的结果。因此建议考虑应用以上元素之间的相关关系共同判定N-MORB与E-MORB。     

A model for integrated spatial land use characteristics linking to surface nutrient concentration

Quantifying land use heterogeneity helps better understand how it influences biophysical systems. Land use area proportions have been used conventionally to predict water quality variables. Lacking an insight into the combined effect of various spatial characteristics could lead to the statistical bias and confused understanding in previous studies. In this study, using spatial techniques and mathematical models, a diagnostic model was developed and applied for quantifying and incorporating three spatial components, namely, slope, distance to sampling spots, and arrangement. The upper catchment of Miyun Reservoir was studied as the test area. Total nitrogen, total phosphorus, and chemical oxygen demand of water samples from field measurements were used to characterize the surface water quality in 52 sub-watersheds. Using parameter calibrations and determinations, combined spatial characteristics were explored and detected. Adjusted land use proportions were calculated by spatial weights of discriminating the relative contribution of each location to water quality and used to build the integrated models. Compared with traditional methods only using area proportions, our model increased the explanatory power of land use and quantified the effects of spatial information on water quality. This can guide the optimization of land use configuration to control water eutrophication.     

Supervised classification of electric power transmission line nominal voltage from high-resolution aerial imagery

For many researchers, government agencies, and emergency responders, access to the geospatial data of US electric power infrastructure is invaluable for analysis, planning, and disaster recovery. Historically, however, access to high quality geospatial energy data has been limited to few agencies because of commercial licenses restrictions, and those resources which are widely accessible have been of poor quality, particularly with respect to reliability. Recent efforts to develop a highly reliable and publicly accessible alternative to the existing datasets were met with numerous challenges – not the least of which was filling the gaps in power transmission line voltage ratings. To address the line voltage rating problem, we developed and tested a basic methodology that fuses knowledge and techniques from power systems, geography, and machine learning domains. Specifically, we identified predictors of nominal voltage that could be extracted from aerial imagery and developed a tree-based classifier to classify nominal line voltage ratings. Overall, we found that line support height, support span, and conductor spacing are the best predictors of voltage ratings, and that the classifier built with these predictors had a reliable predictive accuracy (that is, within one voltage class for four out of the five classes sampled). We applied our approach to a study area in Minnesota.     

Mapping cropland fallow areas in myanmar to scale up sustainable intensification of pulse crops in the farming system

Cropland fallows are the next best-bet for intensification and extensification, leading to increased food production and adding to the nutritional basket. The agronomical suitability of these lands can decide the extent of usage of these lands. Myanmar’s agricultural land (over 13.8 Mha) has the potential to expand by another 50% into additional fallow areas. These areas may be used to grow short-duration pulses, which are economically important and nutritionally rich, and constitute the diets of millions of people as well as provide an important source of livestock feed throughout Asia. Intensifying rice fallows will not only improve the productivity of the land but also increase the income of the smallholder farmers. The enhanced cultivation of pulses will help improve nutritional security in Myanmar and also help conserve natural resources and reduce environmental degradation. The objectives of this study was to use remote sensing methods to identify croplands in Myanmar and cropland fallow areas in two important agro-ecological regions, delta and coastal region and the dry zone. The study used moderate-resolution imaging spectroradiometer (MODIS) 250-m, 16-day normalized difference vegetation index (NDVI) maximum value composite (MVC), and land surface water index (LSWI) for one 1 year (1 June 2012–31 May 2013) along with seasonal field-plot level information and spectral matching techniques to derive croplands versus cropland fallows for each of the three seasons: the monsoon period between June and October; winter period between November and February; and summer period between March and May. The study showed that Myanmar had total net cropland area (TNCA) of 13.8 Mha. Cropland fallows during the monsoon season account for a meagre 2.4% of TNCA. However, in the winter season, 56.5% of TNCA (or 7.8 Mha) were classified as cropland fallows and during the summer season, 82.7% of TNCA (11.4 Mha) were cropland fallows. The producer’s accuracy of the cropland fallow class varied between 92 and 98% (errors of omission of 2 to 8%) and user’s accuracy varied between 82 and 92% (errors of commission of 8 to 18%) for winter and summer, respectively. Overall, the study estimated 19.2 Mha cropland fallows from the two major seasons (winter and summer). Out of this, 10.08 Mha has sufficient moisture (either from rainfall or stored soil water content) to grow short-season pulse crops. This potential with an estimated income of US$ 300 per hectare, if exploited sustainably, is estimated to bring an additional net income of about US$ 1.5 billion to Myanmar per year if at least half (5.04 Mha) of the total cropland fallows (10.08 Mha) is covered with short season pulses.     

The past in dust: current trends and future directions in Pleistocene geoarcheology of European loess

Loess is a main archive of Pleistocene landscapes and environments and therefore has an important connection to the preservation and interpretation of Paleolithic sites. In Europe, anthropogenic sites have been found in loess because of past local occupation. At one extreme, sites are well preserved with minimal disturbance often accompanied by embedded proxies to estimate ecological parameters. On the other hand, loess deposits have undergone post-depositional alterations such as weathering, pedogenesis or bioturbation due to changing environmental conditions or other disturbances that obscure anthropogenic sites. We outline the current state of research and connections between Paleolithic archeology and loess research while introducing a series of subsequent regional case studies as part of a special issue. We also make recommendations for future work to incorporate a wider variety of methods to create more robust inferences on hominin and environmental evolution and their connections.     

CSAMT与AMT数据“拼接”处理——以湖南仁里铌钽矿床7号剖面为例

音频大地电磁测深(AMT)与可控源音频大地电磁测深(CSAMT)均为深部勘查常用方法。AMT方法采集频带较宽,但存在“死频带”,在“死频带”范围无法完全得到地质体响应。CSAMT信噪比高,但通常受发射功率的限制,收发距离一般放置不够远,容易过早进入“近区”。本文展示了将两种方法数据拼接组合的一种处理方式:首先在前人理论研究的基础上,利用CSAMT和AMT均匀半空间模型进行了正演计算,结果表明,CSAMT远区与AMT数据拼接具有可行性;选择湖南仁里铌钽矿床7号剖面的野外实测数据进行实验,将同测点位置的CSAMT远区数据和AMT同测点同模式数据相“拼接”,合成新AMT数据;最后进行反演,反演结果与钻探结果对应较好,表明该方法具有一定的效果。     

地球科学大数据的管理与共享：以英国地质调查局为例

大数据驱动的研究范式正在引起地学领域的革命,而海量大数据的有效管理和共享是数据高效利用的前提。英国地质调查局作为最早成立的国家地质调查局,拥有海量的地学数据资源,通过近年来对数字化工作的全面推进,在数据的开放共享方面走在了世界各国的最前沿。文章对英国地质调查局的数据资源管理和数据共享方式进行了分析调研,详细介绍了他们的一站式管理平台——开放地学的主体组成,以及他们与同行合作建设的数据库。开放地学全面汇总了地调局内的数据资源,并通过一系列数据共享将所有数据集有机链接,通过数据和模型的巧妙结合,在满足用户数据需求的同时,对数据的应用进行了全方位的拓展,是地球系统科学研究框架下地球科学数字化工作的良好典范。     

Brittleness index predictions from Lower Barnett Shale well-log data applying an optimized data matching algorithm at various sampling densities

The capability of accurately predicting mineralogical brittleness index(BI)from basic suites of well logs is desir-able as it provides a useful indicator of the fracability of tight formations.Measuring mineralogical components in rocks is expensive and time consuming.However,the basic well log curves are not well correlated with BI so correlation-based,machine-learning methods are not able to derive highly accurate BI predictions using such data.A correlation-free,optimized data-matching algorithm is configured to predict BI on a supervised basis from well log and core data available from two published wells in the Lower Barnett Shale Formation(Texas).This transparent open box(TOB)algorithm matches data records by calculating the sum of squared errors be-tween their variables and selecting the best matches as those with the minimum squared errors.It then applies optimizers to adjust weights applied to individual variable errors to minimize the root mean square error(RMSE)between calculated and predicted(BI).The prediction accuracy achieved by TOB using just five well logs(Gr,pb,Ns,Rs,Dt)to predict BI is dependent on the density of data records sampled.At a sampling density of about one sample per 0.5 ft BI is predicted with RMSE～0.056 and R2～0.790.At a sampling density of about one sample per 0.1 ft BI is predicted with RMSE～0.008 and R2～0.995.Adding a stratigraphic height index as an additional(sixth)input variable method improves BI prediction accuracy to RMSE～0.003 and R2～0.999 for the two wells with only 1 record in 10,000 yielding a BI prediction error of＞±0.1.The model has the potential to be applied in an unsupervised basis to predict BI from basic well log data in surrounding wells lacking mineralogical measure-ments but with similar lithofacies and burial histories.The method could also be extended to predict elastic rock properties in and seismic attributes from wells and seismic data to improve the precision of brittleness index and fracability mapping spatially.     

西昌市1989—2018年林地草地湿地动态变化特征分析

遥感技术已被广泛应用于生态环境调查与研究。为获取西昌市近30 a生态环境演化趋势,利用1989年、2000年、2010年的专题绘图仪(Thematic Mapper,TM)遥感影像和2018年的陆地成像仪(Operational Land Imager,OLI)遥感影像,通过图像处理、目视解译和野外验证等方法,获得了西昌市1989—2018年的土地利用/覆盖数据,并对林地、草地和湿地的动态变化特征进行了研究。结果表明: 1989—2018年,西昌市林地、湿地和草地面积持续增加,生态环境持续向好; 林地主要分布于安宁河谷和邛海盆地四周山地,在牦牛山、螺髻山一带形成主要林区; 草地主要呈星岛状分布于牦牛山、螺髻山一带林地之间; 湿地以河流湿地与湖泊湿地为主,主要沿安宁河及邛海分布。但仍存在一些问题: 森林存在针叶化现象较普遍、树种单一等问题,需要重点加强林区火灾防范; 草地多数呈零星片状分布,不具有完整的系统结构和良好的功能,多数草地承载力和生产力较低,不宜大规模开发利用,应通过封山育林促使其向森林转化; 湿地分布也比较局限,需要着力予以保护。研究成果可为西昌市生态保护修复措施的制定及经济社会可持续发展提供科学依据。