基于GIS的区域地质调查数字制图--以1∶5万<里庄幅>为例

本文以 1∶5万里庄幅为例 ,阐述了运用GIS系统对区调过程中各种资料的处理与编辑方法 ,并介绍了数字制图方法及工艺流程 ,提出了GIS系统在 1∶5万区调工作中的应用前景     

人工值守台数字化地震仪标定原理

推导了人工台数字化地震仪的分段标定公式，提出数字化记录系统的微分近似标定和拾震器阻尼衰减法标定的方法，并提供了不同短周期地震仪与数字化地震仪并行的藕合方式和标定计算公式。     

数字化射线照相技术对轻物质的判断

本文介绍了数字化射线照相技术对轻物质进行判断的方法。经实践证明，该方法是合理和有效的，可大大增强对轻物质的识别能力，是一种非常可行的识别技术。     

中国大陆及邻近海域的Rayleigh波群速度分布

利用Rayleigh波群速度资料反演得到中国大陆及其临近海域的(70°E-145°E,10°N-55°N)15-120s周期的群速度分布图像. 塔里木盆地在15s处清楚地显示为低速,在16-33s左右没有显示,但在36-5s显示为高速,说明塔里木盆地有较深的根. 青藏高原块体是44s至120s图像中最为突出的低速块体,南面与印度板块的分界线以及与北面的塔里木盆地、柴达木盆地的分界清晰,其块体中西部的速度低于东部. 泰国清迈附近存在一尺度为1000km左右的低速带,可能是青藏高原块体的物质向东南方向迁移造成上地幔物质上涌的结果. 南北地震带表现为强烈的速度梯度带,西面为低速,东面为高速. 中国南海的中央、日本海中央、菲律宾海表现为海洋性地壳. 菲律宾海的图像与地形及地震带完全吻合. 环绕菲律宾海及日本海存在400km左右宽的低速带,可能是岩浆活动带.     

基于DEM的分布式水文模型构建方法

基于 DEM的分布式水文模型是现代水文学同高科技 (如计算机技术、 3S技术等 )相结合的产物 ,是研究变化环境下水文循环与水资源演化规律的理想工具 ,代表了水文模型的最新发展方向。从 DEM的特性出发 ,本文探讨并总结了分布式水文模型的特点、建模思路和模型基本结构框图。在流域离散化方面 ,重点介绍了分布式水文模型常用的三种单元划分方法 ;最后 ,针对分布式水文模型构建问题 ,从“输入模块”、“单元水文模型”、“河网汇流模型”三方面 ,阐述了分布式水文模型微结构构建方法。     

洪水演进三维模拟仿真系统可视化研究

洪水演进仿真系统的研制，是实施“数字流域”工程的重要组成部分；结合洪水演进可视化目标的分析，基于Visual C 系统开发平台，融GIS技术和Opengl开发技术，采用三角形逼近、光滑处理和加入法向量以控制光照的方式，实现了流域地形及河床的三维可视化仿真；应用广度优先搜索算法确定了运动水体与流域河床形态的自适应与自相依的关系，使流域洪水演进模拟具有真实自然的可视化效果。所研制的系统雏形，可有效的模拟流域洪水的三维演进过程；     

Use of Noise to Augment Training Data: A Neural Network Method of Mineral–Potential Mapping in Regions of Limited Known Deposit Examples

One of the main factors that affects the performance of MLP neural networks trained using the backpropagation algorithm in mineral-potential mapping isthe paucity of deposit relative to barren training patterns. To overcome this problem, random noise is added to the original training patterns in order to create additional synthetic deposit training data. Experiments on the effect of the number of deposits available for training in the Kalgoorlie Terrane orogenic gold province show that both the classification performance of a trained network and the quality of the resultant prospectivity map increasesignificantly with increased numbers of deposit patterns. Experiments are conducted to determine the optimum amount of noise using both uniform and normally distributed random noise. Through the addition of noise to the original deposit training data, the number of deposit training patterns is increased from approximately 50 to 1000. The percentage of correct classifications significantly improves for the independent test set as well as for deposit patterns in the test set. For example, using ±40% uniform random noise, the test-set classification performance increases from 67.9% and 68.0% to 72.8% and 77.1% (for test-set overall and test-set deposit patterns, respectively). Indices for the quality of the resultant prospectivity map, (i.e. D/A, D × (D/A), where D is the percentage of deposits and A is the percentage of the total area for the highest prospectivity map-class, and area under an ROC curve) also increase from 8.2, 105, 0.79 to 17.9, 226, 0.87, respectively. Increasing the size of the training-stop data set results in a further increase in classification performance to 73.5%, 77.4%, 14.7, 296, 0.87 for test-set overall and test-set deposit patterns, D/A, D × (D/A), and area under the ROC curve, respectively.     

Use of Fuzzy Membership Input Layers to Combine Subjective Geological Knowledge and Empirical Data in a Neural Network Method for Mineral-Potential Mapping

Use of GIS layers, in which the cell values represent fuzzy membership variables, is an effective method of combining subjective geological knowledge with empirical data in a neural network approach to mineral-prospectivity mapping. In this study, multilayer perceptron (MLP), neural networks are used to combine up to 17 regional exploration variables to predict the potential for orogenic gold deposits in the form of prospectivity maps in the Archean Kalgoorlie Terrane of Western Australia. Two types of fuzzy membership layers are used. In the first type of layer, the statistical relationships between known gold deposits and variables in the GIS thematic layer are used to determine fuzzy membership values. For example, GIS layers depicting solid geology and rock-type combinations of categorical data at the nearest lithological boundary for each cell are converted to fuzzy membership layers representing favorable lithologies and favorable lithological boundaries, respectively. This type of fuzzy-membership input is a useful alternative to the 1-of-N coding used for categorical inputs, particularly if there are a large number of classes. Rheological contrast at lithological boundaries is modeled using a second type of fuzzy membership layer, in which the assignment of fuzzy membership value, although based on geological field data, is subjective. The methods used here could be applied to a large range of subjective data (e.g., favorability of tectonic environment, host stratigraphy, or reactivation along major faults) currently used in regional exploration programs, but which normally would not be included as inputs in an empirical neural network approach.     

数字城市建设研究

数字城市建设是一项复杂的系统工程，需要做好规划，解决管理、制度、标准以及必须的关键技术等问题。文章在分析了数字城市建设目标和内容的基础上，探讨了数字城市建设的基本原则，提出了数字城市建设的具体实施方案。