塔克拉玛干沙漠腹地边界层风场特征

利用CFL-03边界层风廓线雷达在塔中开展了边界层风场探测研究,根据2010年4月1日至2010年11月30日连续的边界层风场探测资料,分析了塔克拉玛干沙漠腹地大气边界层风场时空分布特征,得到了4月至11月各月的高空风廓线。结果表明,塔中春秋季风场结构类似,中高层多为西风,风速较大,低层多为东风,风速较小,整层风速与高度成正比;夏季高层风速变小,低层风速增大,东风层增厚,夏季塔中地区上空100～200 m高度层存在明显风速切变带。     

Tuning the second-generation SDI: theoretical aspects and real use cases

Spatial data infrastructure (SDI) actors have great expectations for the second-generation SDI currently under development. However, SDIs have many implementation problems at different levels that are delaying the development of the SDI framework. The aims of this article are to identify these difficulties, in the literature and based on our own experience, in order to determine how mature and useful the current SDI phenomena are. We can then determine whether a general reconceptualization is necessary or rather a set of technical improvements and good practices needs to be developed before the second-generation SDI is completed. This study is based on the following aspects: metadata about data and services, data models, data download, data and processing services, data portrayal and symbolization, and mass market aspects. This work aims to find an equilibrium between user-focused geoportals and web service interconnection (the user side vs. the server side). These deep reflections are motivated by a use case in the healthcare area in which we employed the Catalan regional SDI. The use case shows that even one of the best regional SDI implementations can fail to provide the required information and processes even when the required data exist. Several previous studies recognize the value of applying Web 2.0 and user participation approaches but few of these studies provide a real implementation. Another objective of this work is to show that it is easy to complement the classical, international standard-based SDI with a participative Web 2.0 approach. To do so, we present a mash-up portal built on top of the Catalan SDI catalogues.     

GIS and remote sensing integration for environmental applications

Abstract

The combined use of remotely-sensed images and vector GIS data has received considerable interest in recent years. This review article discusses the historical move towards closer integration of remote sensing and GIS technologies and the requirements of integrated software systems to enable remotely-sensed data to be combined with vector datasets for maximum effect. The benefits of integration to users of both GIS and remote sensing for environmental applications are reviewed and some thoughts are given on terminology and future directions in this field.     

数字地质填图研究现状与发展趋势

数字地质填图是指区域地质调查数据的野外获取及其成果的数字化统一性再现.当前数字地质填图现状和发展趋势已基本上实现了数字填图系统的采集、存储、管理、描述、分析和再现地质实体在地球表面空间分布有关的数据信息.在计算机辅助下, 通过野外观测路线的调查, 对地质、地理、地球物理、地球化学和遥感等多源地学数据进行综合分析和地质制图.在掌上机WindowsCE平台上, 实现了数字填图所需的基本GIS基本功能(GPS定位路线采集、素描), 实现了遥感系统与数字填图系统的一体化整合.      

A Review of: “Applications of Spatial Data Structures: Computer Graphics,Image Processing,and GIS”. By H. SAMET. (Addison-Wesley Publishing Company,Inc, 1989.) [Pp. xv + 507; figures,tables, appendix,references, name and credit index,subject index.] Price US $49.95. ISBN 020150300 X (hardback).

The introduction of automated generalisation procedures in map production systems requires that generalisation systems are capable of processing large amounts of map data in acceptable time and that cartographic quality is similar to traditional map products. With respect to these requirements, we examine two complementary approaches that should improve generalisation systems currently in use by national topographic mapping agencies. Our focus is particularly on self‐evaluating systems, taking as an example those systems that build on the multi‐agent paradigm. The first approach aims to improve the cartographic quality by utilising cartographic expert knowledge relating to spatial context. More specifically, we introduce expert rules for the selection of generalisation operations based on a classification of buildings into five urban structure types, including inner city, urban, suburban, rural, and industrial and commercial areas. The second approach aims to utilise machine learning techniques to extract heuristics that allow us to reduce the search space and hence the time in which a good cartographical solution is reached. Both approaches are tested individually and in combination for the generalisation of buildings from map scale 1:5000 to the target map scale of 1:25 000. Our experiments show improvements in terms of efficiency and effectiveness. We provide evidence that both approaches complement each other and that a combination of expert and machine learnt rules give better results than the individual approaches. Both approaches are sufficiently general to be applicable to other forms of self‐evaluating, constraint‐based systems than multi‐agent systems, and to other feature classes than buildings. Problems have been identified resulting from difficulties to formalise cartographic quality by means of constraints for the control of the generalisation process.     

Estimation of statistical parameters for censored lognormal hydraulic conductivity measurements

Field tests of hydraulic conductivity (e.g., injection test, pumping test, etc.) in low permeability formations are subject to censoring due to the detection limit of the instruments used. An iterative method of estimating the mean and variance of hydraulic conductivity data with a presumed log-normal distribution function is presented. This method accounts for the data that are actually below the lower detection limit (called truncated data) and thus gives distribution parameters that are more representative for the underlying distribution. The proposed method is then tested on two simulated normally distributed random datasets having different variances. The results show that the means and variances estimated by the proposed method are very accurate. Finally, the method is used to estimate the mean and variance of hydraulic conductivity data from single hole water injection tests in a fractured geological formation.     

Quality control and homogeneity of Turkish precipitation data

Outlier trimming and homogeneity checking/correction were performed on the monthly precipitation time series of various lengths from 267 stations in Turkey. Outlier values are usually found during dry summer months, and are concentrated mostly over the southern parts of the country, where the dry period is most pronounced, implying natural extremes rather than wrong measurements. Homogeneity analysis was done using the Standard Normal Homogeneity Test, on an individual monthly basis, which led to many non‐testable series due to lack of reference stations, especially during summer months. Yet, remaining testable months were usually helpful for the assessment of homogenity, revealing a well distributed set of stations that proved to be homogeneous. There were still a number of stations which either could not be tested efficiently, or were classified as inhomogeneous. Lack of metadata is argued to be largely responsible for inefficient homogeneity testing. Copyright © 2008 John Wiley & Sons, Ltd.     

Automatic morphological classification of galaxy images

We describe an image analysis supervised learning algorithm that can automatically classify galaxy images. The algorithm is first trained using manually classified images of elliptical, spiral and edge-on galaxies. A large set of image features is extracted from each image, and the most informative features are selected using Fisher scores. Test images can then be classified using a simple Weighted Nearest Neighbour rule such that the Fisher scores are used as the feature weights. Experimental results show that galaxy images from Galaxy Zoo can be classified automatically to spiral, elliptical and edge-on galaxies with an accuracy of ∼90 per cent compared to classifications carried out by the author. Full compilable source code of the algorithm is available for free download, and its general-purpose nature makes it suitable for other uses that involve automatic image analysis of celestial objects.     

顾及起算数据误差的整体平差法

因起算数据误差的存在 ,导致了用普通的平差方法求得的结果精度降低。本文提出了顾及起算数据误差的计算方法 ,即从整体平差的角度出发 ,将起算数据作为虚拟观测值 ,与观测值一起进行平差。