皖南云岭金矿地球物理找矿模型

皖南云岭金矿位于长江中下游多金属成矿带与华南成矿带之间,属于江南造山带上的一个热液脉型矿床。基于云岭金矿区域地质背景,在该区开展了岩石露头测定、岩石标本物性测定和地球物理学相关研究。运用地面高精度磁测法,识别本区主要控矿构造为NE向断裂带。根据激发极化法圈定高极化率异常区,并结合相应区域电阻率(可控源音频大地电磁法)和磁异常分布特征建立4种地球物理模型:低阻-高极化模型、高阻-高极化模型、高极化-磁异常过渡带模型和高极化-高磁异常模型。这4种地球物理模型建立在该区岩石物性与矿床成因基础之上,分别对应不同含矿模型:低阻-高极化模型对应接触带上硫铁矿成矿区;高阻-高极化模型对应含矿硅化带;高极化-磁异常过渡带模型对应围岩蚀变带;高极化-高磁异常模型对应岩浆侵入区。依据以上模型,可圈定NE向断裂带、断裂带西侧高阻硅化带及东侧蚀变岩体为找矿有利靶区。     

山东单县覆盖区铁矿特征及找矿方向研究

鲁西南单县地区赋存沉积变质型铁矿,近年来,该地区铁矿找矿取得了较大的进展。为了更好地指导区内铁矿勘查工作,通过介绍单县地区铁矿地质特征、地球物理特征,剖析大刘庄铁矿床、龙王庙铁矿的矿床特征,建立找矿标志,并对今后铁矿找矿方向进行研究。单县大刘庄、龙王庙铁矿赋存于新太古代泰山岩群山草峪组中;铁矿体总体呈层状、似层状,局部呈透镜状,铁矿体产状与围岩一致。通过分析认为,区内的铁矿总体受山草峪组控制,构造、侵入岩对铁矿有破坏作用。经过对重磁测量成果分析,总体认为磁异常及其化极明显部位是区内铁矿勘查中最重要的指示标志,重力梯度带是铁矿赋存的重点位置。通过对以往勘查成果的综合分析认为,辛羊庙异常区应为今后铁矿勘查工作的首选地区。     

Cycle graph analysis for 3D roof structure modelling: Concepts and performance

The paper presents a cycle graph analysis approach to the automatic reconstruction of 3D roof models from airborne laser scanner data. The nature of convergences of topological relations of plane adjacencies, allowing for the reconstruction of roof corner geometries with preserved topology, can be derived from cycles in roof topology graphs. The topology between roof adjacencies is defined in terms of ridge-lines and step-edges. In the proposed method, the input point cloud is first segmented and roof topology is derived while extracting roof planes from identified non-terrain segments. Orientation and placement regularities are applied on weakly defined edges using a piecewise regularization approach prior to the reconstruction, which assists in preserving symmetries in building geometry. Roof corners are geometrically modelled using the shortest closed cycles and the outermost cycle derived from roof topology graph in which external target graphs are no longer required. Based on test results, we show that the proposed approach can handle complexities with nearly 90% of the detected roof faces reconstructed correctly. The approach allows complex height jumps and various types of building roofs to be firmly reconstructed without prior knowledge of primitive building types.     

Assessing the performance of two unsupervised dimensionality reduction techniques on hyperspectral APEX data for high resolution urban land-cover mapping

Despite the high richness of information content provided by airborne hyperspectral data, detailed urban land-cover mapping is still a challenging task. An important topic in hyperspectral remote sensing is the issue of high dimensionality, which is commonly addressed by dimensionality reduction techniques. While many studies focus on methodological developments in data reduction, less attention is paid to the assessment of the proposed methods in detailed urban hyperspectral land-cover mapping, using state-of-the-art image classification approaches. In this study we evaluate the potential of two unsupervised data reduction techniques, the Autoassociative Neural Network (AANN) and the BandClust method – the first a transformation based approach, the second a feature-selection based approach – for mapping of urban land cover at a high level of thematic detail, using an APEX 288-band hyperspectral dataset. Both methods were tested in combination with four state-of-the-art machine learning classifiers: Random Forest (RF), AdaBoost (ADB), the multiple layer perceptron (MLP), and support vector machines (SVM). When used in combination with a strong learner (MLP, SVM) BandClust produces classification accuracies similar to or higher than obtained with the full dataset, demonstrating the method’s capability of preserving critical spectral information, required for the classifier to successfully distinguish between the 22 urban land-cover classes defined in this study. In the AANN data reduction process, on the other hand, important spectral information seems to be compromised or lost, resulting in lower accuracies for three of the four classifiers tested. Detailed analysis of accuracies at class level confirms the superiority of the SVM/Bandclust combination for accurate urban land-cover mapping using a reduced hyperspectral dataset. This study also demonstrates the potential of the new APEX sensor data for detailed mapping of land cover in spatially and spectrally complex urban areas.     

基于机载 Lidar 的地貌数据快速更新方案研究

空间地理信息作为国家信息资源的重要组成部分之一,承担着越来越重要的作用,地貌数据作为空间数据的组成部分,其数据采集及更新十分重要。机载 Lidar 问世以来受到测绘行业广泛重视,其应用不断扩展。该文以地貌数据的快速更新为研究目的,深入分析了地貌更新流程以及机载 Lidar 数据成果,并在此之上提出基于机载 Lidar 数据的地貌快速更新方案,研究其具体步骤以及核心技术,同时采用 CAD 二次开发实现地貌更新数据预处理,大幅提高地貌更新效率。     

A lithological assessment of the resistivity data acquired during the airborne geophysical survey of Anglesey,North Wales

A recent airborne geophysical survey has provided high resolution estimates of the electrical resistivity of the near-surface and deeper (bedrock) formations found across Anglesey and a portion of the coastal area of North Wales. This single small survey provides new geophysical information on both the complex configuration of the Neoproterozoic and Cambrian bedrock units and the shallow near-surface geology and glacial features.     

芦山地震同震和震后地表形变及重力变化的理论模拟

为了研究芦山地震的孕震过程和震源区的长期构造过程以及解释实测的震后形变和重力资料, 采用分层介质模型, 利用数值模拟的方法, 考虑区域流变系数, 计算了地震引起的地表同震、震后的形变和重力变化以及区域内部分GPS与重力连续观测台站的震后形变和重力变化的时间序列.结果表明: 芦山地震的地表同震形变显示出发震断层明显的逆冲特性; 粘弹性松弛效应引起的震后地表形变和重力变化比同震形变和重力变化的范围明显扩大, 但随着粘滞系数的增加, 变化量明显减小; 观测台站的震后变化时变曲线显示震后形变和重力变化在震后50 a间变化显著, 100 a后基本平缓, 趋于稳定; 模拟计算的GPS台站中除了MEIG台和MYAN台以外, 其余台站的震后观测必须考虑粘弹性松弛的影响.      

Acta Geologica Sinica （English Edition） Calls For Submission of Review Papers

正Acta Geologica Sinica(English Edition)is a bimonthly,SCI-indexed academic journal produced by the Geological Society of China.Having an impact factor ranging from 1.5 to 2.15,it has long been indexed by many international databases and websites,such as SCI,CA,BIG,etc.Internationally,the journal cooperates with John WileySons Co.Ltd     

Aims and Scope

正Acta Geologica Sinica(English Edition)mainly reports the latest and most important achievements in the theoretical and basic research in geological sciences,together with new technologies,in the world.Papers published involve various aspects of research concerning geosciences and related disciplines,such as stratigraphy,paleontology,