Compositional Balance Analysis: An Elegant Method of Geochemical Pattern Recognition and Anomaly Mapping for Mineral Exploration

Natural Resources Research - Geochemical pattern recognition and anomaly mapping are always involved in the fields of environmental and exploration geochemistry. Principal component analysis (PCA)...     

Enhancement and Mapping of Weak Multivariate Stream Sediment Geochemical Anomalies in Ahar Area,NW Iran

In this study, stream sediment geochemical data have been subjected to robust principal components analysis (RPCA) and singularity mapping (SM) to enhance and map significant multivariate geochemical anomalies (i.e., mineralization-related) in Ahar area, NW Iran. The RPCA was applied to (a) account for the compositional nature of stream sediment geochemical data using suitable log-ratio transformation, (b) modulate the effect of outliers in component estimation and (c) derive a multivariate geochemical footprint of mineralization. The SM was applied to extract anomalous patterns of the multivariate geochemical footprint of mineralization. The exploration targets were then delineated using Student’s t-statistics analysis. The correlations of mapped exploration targets with the known mineral occurrences and mineralization-related patterns were further evaluated using normalized density index and overall accuracy analyses.     

Machine Learning of Mineralization-Related Geochemical Anomalies: A Review of Potential Methods

Research on processing geochemical data and identifying geochemical anomalies has made important progress in recent decades. Fractal/multi-fractal models, compositional data analysis, and machine learning (ML) are three widely used techniques in the field of geochemical data processing. In recent years, ML has been applied to model the complex and unknown multivariate geochemical distribution and extract meaningful elemental associations related to mineralization or environmental pollution. It is expected that ML will have a more significant role in geochemical mapping with the development of big data science and artificial intelligence in the near future. In this study, state-of-the-art applications of ML in identifying geochemical anomalies were reviewed, and the advantages and disadvantages of ML for geochemical prospecting were investigated. More applications are needed to demonstrate the advantage of ML in solving complex problems in the geosciences.     

Assessing Uncertainty Associated with the Delineation of Geochemical Anomalies

A pedogeochemical exploratory survey of gold deposits was carried out in the region of São Sepé (southernmost Brazil). The region comprises a predominantly metamorphosed belt of volcanoclastics, sediments, serpentinites, basalts, gabbros, chert, tuffs, and banded iron formation of the Proterozoic age. The anomalies were identified first by stream sediment heavy mineral survey at the regional scale of exploration. Once spatial continuity was modeled, ordinary block kriging was performed to generate geochemical maps. Indicator block kriging also was used as an alternative in analyzing and interpreting geochemical data. A novel approach is proposed, which combines both ordinary and indicator kriging for delineating geochemical anomalies. Probability maps proved to be appropriate for selecting new sites for further exploration. Gold anomalies in soils trending NE were well defined by geostatistical analysis and subsequently confirmed by drilling.     

Mapping of Regional-scale Multi-element Geochemical Anomalies Using Hierarchical Clustering Algorithms

Natural Resources Research - Mapping of multi-element geochemical anomalies is the basic goal of stream sediment sampling in worldwide, and especially at 1:100,000 scale in Iran. In the central...     

Geochemical Anomaly and Mineral Prospectivity Mapping for Vein-Type Copper Mineralization,Kuhsiah-e-Urmak Area,Iran: Application of Sequential Gaussian Simulation and Multivariate Regression Analysis

Natural Resources Research - In this paper, sequential Gaussian simulation (SGS) and number–size (N–S) fractal modeling were used for copper geochemical anomaly mapping in the western...     

An Indoor Routing Algorithm for the Blind: Development and Comparison to a Routing Algorithm for the Sighted

This paper presents a prototypical implementation of a non‐network‐based indoor routing algorithm for the sighted and the blind. The spatial abilities of the visually impaired are discussed. Former approaches of outdoor navigation systems for the blind are analyzed and deemed inappropriate for the purpose of modeling indoor navigation. The proposed routing algorithm for the blind calculates routes based on physical characteristics of traveling with a long cane. The algorithm distinguishes between clues, landmarks, obstacles, and hazards along the feasible paths and selects the optimal route by trading off distance and the number of landmarks and clues along a route. Subsequently, the routes for the blind are compared to routes calculated by the routing algorithm for the sighted. The paper asserts that the proposed indoor routing algorithm leads to more suitable routes for the blind.     

Multi-parameter Analysis of Local Singularity Mapping and Its Application to Identify Geochemical Anomalies in the Xishan Gold Deposit,North China

Natural Resources Research - Identification of geochemical anomalies from geological background is of great significance in the exploration of complex mineralization systems. For a 2D problem, the...     

克里雅河中下游流域地表沉积物的粒度与化学元素空间分布

通过对克里雅河流域的实地考察、地形测量、取样,分析其流经沙漠过渡带地表沉积物的粒度、化学元素的空间分布,得出以下结论：河流—沙漠过渡带地表沉积物的粒度组成以>2 φ的粒径为主,粒度特征明显表现出风成特点;化学组成上以Si、Al为主,和上陆壳平均化学组成相比,除Ca、Co、As外都有一定的亏损;不同河段自上游至下游,在不同动力条件下,地表物质粒度特征表现出河漫滩砂与阶地风成砂呈相反的递变趋势;不同河段A-CN-K图解及CIA揭示了克里雅河不同河段地表物质化学风化程度均很低,处于较弱的去Na、Ca阶段,其他元素未发生明显的化学风化或迁移,不同河段化学风化程度差异与物源及地貌格局息息相关;同一河段不同地貌单元,随距河道远近不同,粒度特征与化学风化程度呈现出一定的递变规律;克里雅河平均粒径与一些元素的相关性,说明粒径大小与表征化学风化程度数值的大小有一定关系。总之,在不同空间尺度上,克里雅河地表沉积物理化学特征的分异实质上反映风动力和水动力的差异性分选。     

A Novel Multiple-Kernel Support Vector Regression Algorithm for Estimation of Water Quality Parameters

Natural Resources Research - The quality of surface waters plays a key role in the sustainability of ecological systems. Measuring water quality parameters (WQPs) is of high...     

Recognition of Significant Surface Soil Geochemical Anomalies Via Weighted 3D Shortest-Distance Field of Subsurface Orebodies: A Case Study in the Hongtoushan Copper Mine,NE China

Natural Resources Research - Quantitative prediction of concealed mineralization is always confronted with difficulties in comprehensive analysis between 2D and 3D data and between qualitative and...     

矢量数据向栅格数据转换的一种改进算法

地理信息系统的发展与空间数据结构的优化密不可分,栅格数据与矢量数据之间的高效转换是GIS的关键技术之一。由于栅格数据十分有利于空间分析中的叠置分析,因而通常需要将矢量数据转换成栅格数据。该文分析对比了地理信息系统的两种基本数据结构,在总结已往矢量数据转换为栅格数据方法的基础上,依据边界代数多边形填充算法的基本原理,结合绘图作业时采用的正负法,提出了一种改进的折线边界(数据串)跟踪方法。该算法原理简单,不需进行复杂的距离比较运算,运算速度快,并且通过简单的角度判断保证了填充的精度。     

基于高光谱影像数据的戈壁表面砾石粒径定量反演潜力评估

在新疆哈密境内的噶顺戈壁选取样地,采集不同粒径砾石的光谱数据,分析光谱吸收特征,并利用光谱混合分析技术,以地物光谱为端元从EO-1 Hyperion 高光谱影像中提取了不同粒径的丰度图,分析戈壁表面砾石与高光谱影像的相关关系。结果表明:获取的地物光谱特征显示出粒径的差异对光谱具有明显的影响。所有光谱都展现出在2 250 nm处具有Al–OH 的吸收特性,而且粒径d=41 cm的吸收特性比其他粒径都更显著。而与更小粒径相比,粒径d=53 cm和d=83 cm在480 nm和920 nm处具有较弱的Fe³⁺ 吸收特性。粒径d=0.8 cm(R²=0.637)、d=3.4 cm(R²=0.687)、d=16.3 cm(R² =0.644)及d=41 cm(R²=0.622) 与相应的丰度影像具有显著相关性,而粒径d=53 cm(R²=0.181)和d=83 cm(R²=0.167)与相应的丰度影像相关性不显著。EO-1高光谱影像适用于对戈壁区砾石分布特征的确定,在进一步的研究中将高分辨率影像与高光谱影像相结合,可以提高判别精度。     

平面点集凸壳的一种快速算法

提出一种计算平面点集凸壳的快速算法———八方向极值快速凸壳算法。该算法首先对平面点集进行一次扫描,从而快速查找到东、南、西、北、东南、西南、东北、西北8个方向上的极值点,构造出一个更接近凸壳的初始凸壳,从而在后续的点集扫描中可以排除更多的内点,使该算法计算效率更高。该算法的空间复杂度为O(N);其时间复杂度虽然无法突破最坏情况下O(NlogN)的理论下限,但其期望时间复杂度已达到线性水平,并且可以容易地扩展到三维和高维空间。     

一种抗要素删除的矢量地理数据精确认证算法

脆弱水印是数字水印技术的一个重要分支,可以实现对数据内容真实性的认证,并能准确检测到数据的篡改位置、篡改量甚至篡改类型,是解决矢量地理数据完整性认证难题的有力手段。基于脆弱水印技术,该文提出了一种抗要素删除的矢量地理数据精确认证算法。在认证内容嵌入过程中,首先按照"Zig-Zag"排序方式建立矢量地理数据的空间位置关系;然后,提取坐标值精度位前的数值生成脆弱水印信息;最后,根据量化的思想将水印信息嵌入到排序后的相邻数据点上。在认证时,将提取到的水印信息与生成的水印信息进行对比,根据二者是否一致来鉴别数据是否发生更新。实验结果表明,该文提出的认证算法可实现数据更新时的精确认证,对各种篡改包括要素删除、增加、平移等能够精确定位与标记。     

一种基于TIN的地形剖面线生成算法

在目前已有基于规则格网(Grid)生成地形剖面线的基础上，提出了一种适用于不规则三角网(TIN)的剖面线生成算法。该算法充分利用TIN中各三角形间存在的拓扑关系，实现了与剖面线相交三角形的快速搜索，大大提高了算法的执行效率。由于地形简化后的TIN仍保留三角形间的拓扑关系，该剖面线生成算法还适用于多分辨率的海量TIN数据。     

一种基于数学形态学的沟壑密度提取算法

沟壑密度是反映地表破碎程度的重要因子 ,在土壤侵蚀、地貌演变等研究中有重要作用。本文介绍基于数学形态学的沟壑密度提取算法 ,从TM影像中提取沟谷线信息 ,从而有效地解决了土壤侵蚀评价中下垫面表征因子提取问题。并以黄河流域某小流域沟壑密度的计算作了实例验证。     

基于GDF的道路网完全拓扑生成算法

拓扑关系生成是导航空间数据库构建的一个关键环节。该文根据ISOGDF4.0的要求和道路网拓扑关系的特点,研究了一种道路网完全拓扑关系的生成算法,即根据点的几何坐标生成结点—边拓扑关系的算法,以及从标识点出发利用Qi算子生成部分非传统面拓扑关系的算法。实验表明,此算法的时间效率较高,特别是部分面拓扑关系的定义及生成算法能满足实际导航应用的需要。     

广州市人行天桥叶面滞尘粒度特征及其来源

对2009 年广州城区36 座人行天桥上采集的植被叶面滞尘样品进行粒度分析,粒度结果显示：叶面滞尘多为沙质粉沙,粉沙、沙和黏土体积分数的平均值分别为53.99%、41.34%和4.67%;粒度频率分布呈三峰型,主峰态在10~200 μm 之间。4 个市辖区叶面滞尘的粒度特征都较为相似,说明整个广州城区的叶面滞尘在成因和来源上都较为一致。叶面滞尘中的总悬浮颗粒物（TSP≤100 μm）体积分数极高,PM2.5 和PM10 体积分数略低;PM2.5/PM10 的平均值为0.36,推测其更多来自道路扬尘与建筑扬尘等局地污染源。风沙动力研究指示：其物源主要是由城区30km范围内短距离悬浮搬运而来,属内源性颗粒物。