ANISOTROPY OF MAGNETIC SUSCEPTIBILITY AND IDENTIFICATION OF TILTED SEDIMENT CORES FROM THE BOHAI SEA

Anisotropy of magnetic susceptibility (AMS) is a well-developed technique increaseingly used in petro-fabric determination. ItS application to two Mackereth cores JX91-2A and JX91-2B, taken from thesame site in the central Bohai Sea, revealed 3D magnetic fabrics of the sediments as expressed with susce-ptibility ellipsoids. The flat seafloor and the relatively quiet depositional environment in the semi-isolatedBohai Sea should asult in a primary fabric with horisontally obate susocptibility el1ipsoids. Mormwr,the inaxing downcore totaI anisotropy comprising mainly of magntic foliation nsulting fIrom sedimentcompaction should also lead to flat ellipsoids. Therefore, the off-pole meam dindions of minimurn axes ofaseptibility ellipsoids on stermnets must indicate that the two coas are ti]ted re1ative to the flat anfloor.Use of Fisher statisties showh the tilt angles to be 14° for JX91-2A and 23°for JX91 -2B from whichthe tna depths of the coas were dedded accordingly.     

GIS based spatial data analysis for landslide susceptibility mapping

Landslide susceptibility map delineates the potential zones for landslides occurrence. The paper presents a statistical approach through spatial data analysis in GIS for landslide susceptibility mapping in parts of Sikkim Himalaya. Six important causative factors for landslide occurrences were selected and corresponding thematic data layers were prepared in GIS. Topographic maps,satellite image,field data and published maps constitute the input data for thematic layer preparation. Numerical weights for different categories of these factors were determined based on a statistical approach and the weighted thematic layers were integrated in GIS environment to generate the landslide susceptibility map of the area. The landslide susceptibility map classifies the area into five different landslide susceptible zones i.e.,very high,high,moderate,low and very low. This map was validated using the existing landslide distribution in the area.     

昆明市松华坝水源区表土磁学特征及其环境意义

采用环境磁学研究方法研究了昆明市松华坝水源区表土的磁学特征,结果表明,松华坝上游地区表土未受或很少受到污染,土壤磁化率偏低,土壤中的主要载磁矿物为磁铁矿、磁赤铁矿,另外还含有少量弱磁性的磁黄铁矿和针铁矿。松华坝下游坝区土壤受到了一定程度的污染,污染表土的磁学特征表现为：高磁化率,磁化率与频率磁化率呈现较强的负相关,污染土壤中的主要载磁矿物为强磁性的磁铁矿。松华坝下游土壤污染主要局限于距水面2m的范围之内．污染物主兽来源干农业面源污染．     

氮气气氛下黄铁矿热分解的矿物相变研究

通过差热-热重分析、X射线粉末衍射（XRD）及磁化率分析等手段,对天然黄铁矿样品在氮气中受热发生的矿物相 变过程进行了综合研究。不同温度下黄铁矿煅烧产物的XRD物相分析结果显示,低于500℃时,黄铁矿无显著变化;随着 温度的升高（500~600℃）,黄铁矿开始转变为单斜磁黄铁矿,进而生成六方磁黄铁矿,磁化率显著升高;700℃~800℃的 煅烧产物主要为六方磁黄铁矿,磁化率明显下降,直至900℃进一步形成更稳定的陨硫铁（FeS）,磁化率接近于零。在黄 铁矿物相开始转变的温度（500~600℃）区间,黄铁矿生成单斜磁黄铁矿的速率大于单斜磁黄铁矿转化为六方磁黄铁矿的速 率;高温（700~900℃）时,黄铁矿转化为单斜磁黄铁矿的速率低于单斜磁黄铁矿转化为六方磁黄铁矿的速率,表现为黄铁 矿直接生成六方磁黄铁矿。     

基于遥感影像多尺度分割与地质因子评价的滑坡易发性区划

区域滑坡易发性的研究是滑坡空间预测的核心内容之一。从影像多尺度分割和面向对象的分类理论出发,以研究区遥感影像的熵、能量、相关性、对比度共4个参数作为影像纹理因子提取易发性特征,利用滑坡所处区域的库水影响等级、坡度、斜坡结构、工程岩组4类地质因子分析地质背景,搭建C5.0决策树的易发性分类模型,实现了对研究区内4类滑坡易发性单元的预测。结果表明：高易发性单元的工程岩组通常发育为软岩岩组和软硬相间岩组,且坡度在15°～30°之间;模型显示该区域训练样本和测试样本平均正确率达91.64%,Kappa系数分别为0.84,0.51,因此这种基于影像多尺度分割与地质因子分级的滑坡易发性分类研究具有一定的适用性。     

Preliminary Study on the Effect of Water Glass Impregnation on the Rock-Magnetic Properties of Baked Clay

A common practice in archaeomagnetic studies in many laboratories is the impregnation of the material with water glass (siliceous gel) in order to achieve better consolidation before cutting. The purpose of this study is to establish if and how the presence of water glass in the burnt clay material affects its magnetic properties during heating. We describe experiments designed to monitor the alterations in isothermal remanence and magnetic susceptibility for two sets of specimens - non-impregnated and impregnated with water glass. Our results show that water glass can cause considerable changes in magnetic susceptibility, but the remanent magnetization is not influenced significantly.     

Magnetic anisotropy of calcite at room-temperature

The intrinsic room temperature magnetic properties of pure calcite were determined from a series of natural crystals, and they were found to be highly dependent on the chemical composition. In general, dia-, para-, and ferromagnetic components contribute to the magnetic susceptibility and the anisotropy of magnetic susceptibility (AMS). With a combination of magnetic measurements and chemical analysis these three contributions were determined and related to their mineralogical sources. The intrinsic diamagnetic susceptibility of pure calcite is − 4.46 ± 0.16 × 10^− 9 m³/kg (− 12.09 ± 0.5 × 10^− 6 SI) and the susceptibility difference is 4.06 ± 0.03 × 10^− 10 m³/kg (1.10 ± 0.01 × 10^− 6 SI). These diamagnetic properties are easily dominated by other components. The paramagnetic contribution is due to paramagnetic ions in the crystal lattice that substitute for calcium; these are mainly iron and manganese. The measured paramagnetic susceptibility agrees with the values calculated from the known concentration of paramagnetic ions in the crystals according to the Curie law of paramagnetic susceptibility. Substituted iron leads to an increase in the AMS. The paramagnetic susceptibility difference was found to correlate linearly with the iron content for concentrations between 500 and 10,000 ppm. An empirical relation was determined: (k₁ − k₃)^para (kg/m³) = Fe-content (ppm) × (1 ± 0.1) × 10^− 12 (kg/m³/ppm). The maximum susceptibility difference (Δk = k₁ − k₃) was found to be unaffected by iron contents below 100 ppm. Ferromagnetic contributions due to inclusions of ferromagnetic minerals can dominate the susceptibility. They were detected by acquisition of isothermal remanent magnetization (IRM) and their contribution to the AMS was separated by high-field measurements.     

四川康定城地质灾害易发分区评价

根据西南地区崩塌、滑坡、泥石流等灾种的形成条件、诱发因素以及稳定状态和发展趋势,建立不同灾种的地质灾害易发程度的判别模式。对四川康定城地质灾害易发性进行分区评价。     

Magnetic characterization of a retroarc extensional basin: The Loncopué Trough

The Loncopué Trough is a Pliocene to Quaternary extensional basin developed over the hinterland area of the Southern Central Andes. This basin is bounded by two neotectonic extensional fault systems delimiting a narrow topographic low. Previous studies have mostly focused on structural and geochemical aspects of this feature. However, geophysical surveys, aimed to unravel deep structure beneath a thick-younger than 5 My volcanic coverage, are scarce and based their interpretations on low resolution data sets. In this study, we collected new aeromagnetic data with the objective of characterizing the magnetic properties of the crust in the Loncopué Through and nearby zones. Additionally, we analyze the spatial relation between geological structures, volcanic fields and magnetic data. In order to highlight the boundaries of the magnetic sources and calculate the basement depth, we applied derivative techniques and the source parameter imaging. Also, we estimated an effective susceptibility model using the Magnetization Vector Inversion method, which takes into account the combined effects of remanence and induced magnetization. To determine the thermal structure of the area, we calculated the Curie depth points through the spectral analysis technique. From the analysis of magnetic data we were able to characterize the main structures and lineaments associated with this retroarc extensional trough. Notably, only the Loncopué eastern fault system seems to be a crustal-scale tectonic feature, while E-W-, ENE- and ESE-trending lineaments are interpreted as relatively minor structures segmenting the basement. Finally, our susceptibility model, together with the analysis of the Curie point, revealed potential magmatic/hydrothermal reservoirs in the Copahue volcano, and the Codihue and Cajón de Almanza regions that could be connected at depth forming a regional magmatic body.     

基于XGBoost模型的三峡库区燕山乡滑坡易发性评价与区划

滑坡易发性评价是精细化滑坡灾害风险评价的基础。为了提升滑坡易发性评价模型的精度和稳健性,以三峡库区万州区燕山乡为例,选取工程地质岩组、堆积层厚度等九个影响因子构建滑坡易发性评价指标体系,应用信息量模型定量分析滑坡发育与指标之间的关系。在此基础上,随机选取70%/30%的滑坡样本作为训练/验证数据集,应用极致梯度提升模型(extreme gradient boosting, XGBoost)开展易发性评价。随后从模型预测精度和模型稳定性两方面将其与决策树模型(decision tree, DT)和梯度提升树模型(gradient boosting decision tree, GBDT)进行对比。结果表明：研究区堆积层滑坡主要受长江水系、堆积层厚度和工程地质岩组影响。XGBoost模型具有最高的准确率(94.3%)和预测精度(97.3%)。在模型稳定性验证中,平均预测精度最高(97.3%),优于DT(91.3%)和GBDT(95.7%),模型标准差和变异系数均为0.01,低于其余两种模型。XGBoost在区域滑坡易发性评价与制图中得到了可靠的结果,为滑坡灾害空间预测提供了新的技术支撑。