千兆网支持下的城市公众GIS

当前GIS技术的发展已经进入到一个新的阶段,呈现出网络化、专业化、智能化、大众化等特点。公众GIS是近年来新兴的GIS应用领域,它主要的目的是面向公众提供信息服务。介绍了城市公众GIS的基本概念、特点和系统功能,在分析了当前公众GIS存在的问题之后,继而提出一种适合宽带网络(千兆以太网)支持下的公众GIS系统结构,并进一步分析了它的功能和用途。     

叶面积指数(LAI)的遥感定量方法综述

总结了当前遥感定量研究叶面积指数(LAI)的两种主要方法:统计模型法和光学模型法,阐述了各自的机理和研究进展,在此基础上,讨论了两种方法的优缺点及未来的发展趋势。     

苏州市轻轨精密工程控制网的建立

根据精密工程控制网的高精度要求，结合沉降地区的特点，进行GPS、精密水准作业中误差分析及精度控制分析，提出满足轻轨工程施工的控制方案。     

Digital model of corrected accumulated flow for peak discharge data acquisition and drainage system design

The design of a drainage system for a roofing slate quarry was implemented by the enhancement of discharge peak estimation, and the uncertainty inevitably associated with the engineering model was reduced.

The development of a topographical, geological, and vegetation cover database developed from a Geographical Information System (GIS) allowed for the definition of the drainage network for a hydraulic system, along with the calculation of the runoff coefficient. This is applied to the digital model of accumulated flow (DMF) as a weight correction coefficient, using a matrix-based model at 5×5 m resolution. The new digital model of corrected accumulated flow (DMCF) is the result of combining the thematic maps with the map of slope <3%, which was previously created from the slope model. It is demonstrated that this new model allows to apply the “Rational Method” on cartographic units defined by the GIS.

The DMCF is compared with other traditional applications of the Rational Method based on the calculation of the discharge peak considering: (1) the drainage basin as a single watershed or (2) defining an average runoff coefficient in each sub-watershed. Both approaches have bigger discharge peaks than those obtained by the DMCF since the slope, lithology, and vegetation cover have average values, and the runoff coefficient is poorly defined, increasing the uncertainty in the discharge peak.     

Application of visual,statistical and artificial neural network methods in the differentiation of water from the exploited aquifers in Kuwait

The ability of artificial neural network to differentiate water samples from the two aquifers of Kuwait on the basis of their major ion chemistry has been demonstrated. The major ion concentration distribution in the groundwater of the Kuwait Group and the Dammam Formation aquifers of Kuwait appears very similar. Cross-plots, supported by the discriminant function analysis of the data, however, suggest that there are some subtle differences in the overall composition of the water from the two aquifers that make it possible to differentiate the water from the two aquifers in almost 80% of the cases. An artificial neural network improved the differentiation capability to 90% of the cases. It is also possible to estimate the fraction of Kuwait Group water in the flow stream of dually completed wells with the help of an artificial neural network developed for this purpose. Electronic Publication     

Stepwise Conditional Transformation for Simulation of Multiple Variables

Most geostatistical studies consider multiple-related variables. These relationships often show complex features such as nonlinearity, heteroscedasticity, and mineralogical or other constraints. These features are not handled by the well-established Gaussian simulation techniques. Earth science variables are rarely Gaussian. Transformation or anamorphosis techniques make each variable univariate Gaussian, but do not enforce bivariate or higher order Gaussianity. The stepwise conditional transformation technique is proposed to transform multiple variables to be univariate Gaussian and multivariate Gaussian with no cross correlation. This makes it remarkably easy to simulate multiple variables with arbitrarily complex relationships: (1) transform the multiple variables, (2) perform independent Gaussian simulation on the transformed variables, and (3) back transform to the original variables. The back transformation enforces reproduction of the original complex features. The methodology and underlying assumptions are explained. Several petroleum and mining examples are used to show features of the transformation and implementation details.     

Impact of horizontal resolution on prediction of tropical cyclones over Bay of Bengal using a regional weather prediction model

The present study is carried out to examine the performance of a regional atmospheric model in forecasting tropical cyclones over the Bay of Bengal and its sensitivity to horizontal resolution. Two cyclones, which formed over the Bay of Bengal during the years 1995 and 1997, are simulated using a regional weather prediction model with two horizontal resolutions of 165 km and 55 km. The model is found to perform reasonably well towards simulation of the storms. The structure, intensity and track of the cyclones are found to be better simulated by finer resolution of the model as compared to the coarse resolution. Rainfall amount and its distribution are also found to be sensitive to the model horizontal resolution. Other important fields, viz., vertical velocity, horizontal divergence and horizontal moisture flux are also found to be sensitive to model horizontal resolution and are better simulated by the model with finer horizontal grids.     

Disjunctive Kriging with Hard and Imprecise Data

This paper presents a methodology for assessing local probability distributions by disjunctive kriging when the available data set contains some imprecise measurements, like noisy or soft information or interval constraints. The basic idea consists in replacing the set of imprecise data by a set of pseudohard data simulated from their posterior distribution; an iterative algorithm based on the Gibbs sampler is proposed to achieve such a simulation step. The whole procedure is repeated many times and the final result is the average of the disjunctive kriging estimates computed from each simulated data set. Being data-independent, the kriging weights need to be calculated only once, which enables fast computing. The simulation procedure requires encoding each datum as a pre-posterior distribution and assuming a Markov property to allow the updating of pre-posterior distributions into posterior ones. Although it suffers some imperfections, disjunctive kriging turns out to be a much more flexible approach than conditional expectation, because of the vast class of models that allows its computation, namely isofactorial models.     

桩基模型试验研究现状

简要地介绍了桩基现场模型试验、桩基渗水力模型试验、桩基室内普通模型试验的研究成果及其模拟桩基特性的局限性,并着重分析了桩基离心模型试验的研究成果及其模拟桩基特性时的优点和局限性。     

Spectral and Multiscale Signal-to-Noise Thresholding of Spherical Vector Fields

The basic concepts of spectral and multiscale selective reconstruction of (geophysically relevant) vector fields on the sphere from error-affected data is outlined in detail. The reconstruction mechanism is formulated under the assumption that spectral as well as multiscale approximation is well-representable in terms of only a certain number of expansion coefficients at the various resolution levels. It is shown that spectral denoising by means of orthogonal expansions in terms of vector spherical harmonics reflects global a priori information of the noise (e.g., in form of a covariance tensor field), whereas multiscale signal-to-noise thresholding can be performed under locally dependent noise information within a multiresolution analysis in terms of spherical vector wavelets. An application of the multiscale formalism to Earth's magnetic field determination is presented.