基于SVM的含约束地球化学单元素异常圈定方法及应用

地球化学元素异常的空间分布受限于地质背景、矿产空间分布和景观特征等因素,单元素异常图的绘制不应仅依据采样数据由计算机追踪等值线图的方法自动勾绘。传统的手工圈定方法效率低、受人为因素影响大。基于SVM(Support Vector Machine,支持向量机)提出了一种可以考虑地质约束的单元素异常圈定方法,并加入地质单元分区、地质构造等约束条件。该方法可以高效绘制出单元素异常图,并成功应用于2个实例中。     

基于吸收边界条件的瞬变电磁法三维矢量有限元快速正演

瞬变电磁法的三维有限元正演通常采用齐次边界条件,为满足该边界条件,需要构建较大尺寸的模型,这降低了正演问题的求解速度.针对该问题,本文采用吸收边界条件代替齐次边界条件,以缩小模型体积,加快正演速度:首先,从时间域麦克斯韦方程组出发,推导了基于库伦规范的矢量势的微分控制方程,结合一阶吸收边界条件推导了相应的的弱形式方程;在此基础上采用一阶四面体矢量单元进行单元分析、Newmark法进行时间离散,实现了瞬变电磁法的快速三维正演.通过均匀半空间模型的解析解,H型地电断面的CR1Dmod解和相应模型有限元解的对比,验证了本文算法的正确性.均匀半空间模型分别采用吸收边界条件和齐次边界条件的正演结果对比表明:吸收边界条件确实可以提高三维正演的精度或者缩小模型尺寸、加快计算速度.     

基于SVM的资源三号测绘卫星影像分类

以江苏省宜兴市为研究区,利用支持向量机(SVM)方法对资源三号测绘卫星影像进行了分类,其总分类精度为97.76%,Kappa精度为0.968 7。为了评价算法的适用性,同时应用最大似然法与最小距离法对同一影像进行分类测试,支持向量机分类法精度高于其他2种方法,可以满足土地覆盖分类调查需求。     

A Review of: Environmental Modelling with GIS.

Cartographic modelling operations provide powerful tools for analysing and manipulating geographic data in the raster data model. This research extends these operations to the vector data model. It first discusses how the spatial scopes of analysis can be defined for point, line, and polygon features analogous to the raster cell. Then it introduces the local, focal, and zonal operations available for vector features, followed by providing a prototype syntax that might guide the implementation of these operations. Through example applications, this research also demonstrates the usefulness of these operations by comparing them with traditional vector spatial analysis.     

A proposed framework for feature‐level geospatial data sharing: a case study for transportation network data

Current data sharing in the Internet environment is supported using metadata at the file level. This approach has three fundamental shortcomings. First, sharing data from different sources with different semantics, data models, and acquisition methods usually requires data conversion and/or integration like data conflation. This can be tedious and error‐prone. Second, data updated from one source cannot be automatically propagated to other related data or applications. Finally, data sharing at the file level makes it difficult to provide feature‐level data for searching, accessing, and exchanging in real time over the Internet. This paper addresses these three issues by proposing a standards‐based framework for sharing geospatial data in the transportation application domain. The proposed framework uses a standard data model—geospatial data model proposed by the Geospatial One‐Stop initiative to harmonize the semantics and data models without the use of data integration methods. It uses Geography Markup Language (GML) for geospatial data coding and feature relationship, which provides a basis to propagate the data update from one source to related other sources and applications, and to search and extract data at the feature level. The framework uses the Web Feature Service (WFS) to search, access and extract data at the feature level from distributed sources. Finally, the Scalable Vector Graphics (SVG) standard was used for data display on the Web browser. Two transportation network datasets are used in the prototype case study to implement the proposed framework. The prototype allows the user to access and extract data at the feature level on the Web from distributed sources without downloading the full data file. It shows that the proposed standards‐based feature‐level data‐sharing system is capable of sharing data without data conflation, accessing, and exchanging data in real time at the feature level. The prototype also shows that changes in one database can be automatically reflected or propagated in another related database without data downloading.     

Application of support vector machine and relevance vector machine to determine evaporative losses in reservoirs

This article employs Support Vector Machine (SVM) and Relevance Vector Machine (RVM) for prediction of Evaporation Losses (E) in reservoirs. SVM that is firmly based on the theory of statistical learning theory, uses regression technique by introducing ε‐insensitive loss function has been adopted. RVM is based on a Bayesian formulation of a linear model with an appropriate prior that results in a sparse representation. The input of SVM and RVM models are mean air temperature (T) ( °C), average wind speed (WS) (m/sec), sunshine hours (SH)(hrs/day), and mean relative humidity (RH) (%). Equations have been also developed for prediction of E. The developed RVM model gives variance of the predicted E. A comparative study has also been presented between SVM, RVM and ANN models. The results indicate that the developed SVM and RVM can be used as a practical tool for prediction of E. Copyright © 2011 John Wiley & Sons, Ltd.     

Replication of a terrain stability mapping using an Artificial Neural Network

Subjective geomorphic mapping is a method commonly used for landslide hazard zonation. This method relies heavily on the skills and experience of the mapper, and therefore, its major drawbacks are the high costs and lack of consistency between products generated by different terrain mappers. In this study a method for cost-effective and consistent replication of subjective geomorphic mappings is demonstrated, by using a type of Artificial Neural Network named Learning Vector Quantization. This paper presents a study conducted in the Canadian province of British Columbia employing a high-quality data set. By utilizing Learning Vector Quantization, stable and unstable terrains were delineated with a similarity of approximately 91%, compared to the mapping produced by terrain specialists. Also, in this process, slope, elevation, aspect, and existing geomorphic processes were identified as the terrain attributes that contributed most to the quality of the mapping.     

基于电场矢量波动方程的三维可控源电磁法有限单元法数值模拟

从可控源电磁法的基本原理出发,推导了基于电场矢量波动方程的三维边值问题,利用广义变分原理,把边值问题转换为变分问题,并引入散度条件,避免了伪解的出现,使有限元计算在理论上更加完备.在准静态近似条件下,把水平电偶极子在空中和大地的远区电场闭合表达式作为有限元计算中的区域外边界条件,解决了边界条件加载的困难;把应用于地震模拟中的伪delta函数引入到可控源电磁法中的三维有限元模拟中,消除了源点的奇异性,提高了方程组的稳定性.通过对均匀大地和层状介质模型的模拟,检验了程序的正确性,并对典型的地质体模型进行了数值模拟,分析了其变化规律.     

基于SVG的WebGIS

网络技术的飞速发展不但在于技术的深化．更在于新技术元素的创立。SVG作为网络图形的新家族成员,一改过去网络图形只重形式,忽略内容的缺点,渐渐显示其独特且强大之处,也为GIS提供了一个方便快捷的网络平台。本文探究基础地理信息系统功能在SVG中的实现技术。