EGNOS系统进展情况

EGNOS是欧洲建设的第一个卫星导航系统，它通过增强两个军用导航系统来向系统服务区内提供差分改正数据和系统完好性信息，来满足高安全用户的需求。本文全面介绍了欧洲EGNOS系统总体设计、技术亮点、系统体系结构、工程现状、系统性能以及系统开发和走向等有关方面的最新情况，为我们国家建设自己的卫星导航增强系统积累经验。     

Seabirds in the diet of Cape fur seals Arctocephalus pusillus pusillus at three mainland breeding colonies in Namibia

Predation by Cape fur seals Arctocephalus pusillus pusillus on seabirds has previously been attributed to a few individuals, mainly males. Scat samples were collected at three mainland breeding colonies of seals in Namibia to determine the extent of seabird predation. Mainly females were sampled. No scats from the van Reenen Bay and Atlas-Wolf Bay colonies, and only two from Cape Cross, contained feather remains, giving an overall frequency of occurrence of feathers in scats of 0.1%. The feathers found were of African penguin Spheniscus demersus and a species of cormorant (Phalacrocorax sp.).     

A Statistical Model for Stock Assessment of Southern Bluefin Tuna with Temporal Changes in Selectivity

Assessment of the status of southern bluefin tuna (SBT) by Australia and Japan has used a method (ADAPT) that imposes a number of structural restrictions, and is similar to methods used for a number of stocks world-wide. A flexible method for assessment of the SBT population is presented that is much less restrictive and has potentially wide applicability. The three key features are: (1) all fitting to data is within the context of maximum likelihood, (2) catch-at-age data are not assumed to be without error (as in existing methods), but rather to be random variables, while age-specific selectivity is allowed to change over time within the bounds of specific structure, and (3) autocorrelation in recruitment processes is considered within the likelihood framework of the model. While the results suggest the stock has been depleted considerably from its virgin biomass, and are generally consistent with previous assessments, they also indicate that it is not as much below the biomass that will produce maximum suitable yield as previously estimated and that the extent of stock rebuilding necessary may not be as large as has been argued. The available data are shown to provide little information on the steepness parameter of the stock-recruitment function, and hence on sustainable catch levels for the stock.     

A transition in weather over the Agulhas Current

Aircraft observations were used to investigate contrasting weather conditions over the northern edge of the warm Agulhas Current south of George, South Africa, during June 1989. A sea surface temperature front of 7°C over 10 km was observed near 35°S, 23°E. Surface-sensible and latent heat fluxes increased by a factor of five on the warm side. A deepening of the moist unstable layer was indicated by increased equivalent potential temperatures over the warm side. Most significantly, convectively generated turbulence, as inferred from variances in air pressure, increased exponentially with sea surface temperature and surface layer winds doubled south of 35°S. The sea state, initially smooth over the continental shelf, became rough seawards of the northern edge of the Agulhas Current. Numerical model simulations were performed to assess air-sea interactions. Model-simulated thermodynamic variables responded in close agreement with observations, but the increase in cross-frontal winds was not fully resolved. The aircraft observations provide evidence that the Agulhas Current affects the large-scale pressure field and may enhance the rain-bearing capacity of transient weather systems.     

Application of the sequential t-test algorithm for analysing regime shifts to the southern Benguela ecosystem

Long-term ecosystem changes, such as regime shifts, have occurred in several marine ecosystems world-wide. Multivariate statistical methods have been used to detect such changes. A new method known as the sequential t-test algorithm for analysing regime shifts (STARS) is applied to a set of biological state variables as well as environmental and anthropogenic forcing variables in the southern Benguela. The method is able to correct for auto-correlation within time-series by a process known as prewhitening. All variables were tested with and without prewhitening. Shifts that were detected with both methods were termed robust. The STARS method detected shifts in relatively short time-series and identified when these shifts occurred without a priori hypotheses. Shifts were generally well detected at the end of time-series, but further development of the method is needed to enhance its performance for auto-correlated time-series. Since 1950, two major long-term ecosystem changes were identified for the southern Benguela. The first change occurred during the 1960s, caused predominantly by heavy fishing pressure but with some environmental forcing. The second change occurred in the early 2000s, caused mainly by environmental forcing. To strengthen these findings, further analyses should be carried out using different methods.     

Rate-of-Change Maps

Mapping spatial change is a fundamental theme in geography. The analytical and numerical application of differential calculus to continuous geographic data produces first-derivative distributions that can be mapped to show gradient magnitude and gradient direction, and second-derivative measures that can be mapped to show the form (convexity, concavity) of the geographic surface. When these differential measures are obtained for spatially distributed temporal data, a velocity/acceleration change map can be constructed. Cartographic applications of the methodology presented in this paper include slope and curvature landform mapping, derivative trend-surface mapping of urban housing value gradients and the velocity/acceleration mapping of mobile-home residency in the United States from 1950 to 1980.     

Exploratory Analysis of Spatial Data Using Interactive Maps and Data Mining

We present new methods for analyzing geo-referenced statistical data. These methods combine visualization and direct manipulation techniques of exploratory data analysis and algorithms for data mining. The methods have been implemented by integrating two hitherto separate software tools: Descartes for interactive thematic mapping, and the data mining toolbox Kepler. In using these tools, data analysis may proceed as a steady interaction between visual inspiration and insights gained from mathematical–statistical calculations. After introducing the various components of the methods and tools, the paper guides the reader through in-depth examples of using the tools in the context of analysis of urban demographic data. In particular, it is shown how geography-based classifications of urban districts can be related to available thematic characteristics by applying the data mining algorithms classification tree derivation, attribute weighting, and subgroup discovery.     

Semi-Automatic Modeling of Buildings from Digital Surface Models

Semi-automatic building detection and extraction is a topic of growing interest due to its potential application in such areas as cadastral information systems, cartographic revision, and GIS. One of the existing strategies for building extraction is to use a digital surface model (DSM) represented by a cloud of known points on a visible surface, and comprising features such as trees or buildings. Conventional surface modeling using stereo-matching techniques has its drawbacks, the most obvious being the effect of building height on perspective, shadows, and occlusions. The laser scanner, a recently developed technological tool, can collect accurate DSMs with high spatial frequency. This paper presents a methodology for semi-automatic modeling of buildings which combines a region-growing algorithm with line-detection methods applied over the DSM.     

An Automated System for Image-to-Vector Georeferencing

Although modern imagery usually has latitude and longitude or similar coordinates to provide true world location, much potentially useful imagery lacks this information. This includes historical imagery, as well as modern imagery that may have lost its locational information through inappropriate processing. Its provision through the process of georeferencing is still primarily a manual procedure. This paper proposes an efficient, fully- automated solution for massively asymmetric image-to-vector georeferencing whereby an image of a relatively small geographic area is automatically located relative to a substantially larger vector map base. For control points, road intersections are automatically extracted from high resolution aerial or satellite imagery using the new concepts of reference circles and central pixels. For automated control point pair identification between image and vector map, an invariant point pattern matching approach is proposed based on shape invariance for similarity transforms and invariant area ratios for affine transforms. The matching algorithm necessitates only a small subset of image points and requires no additional information beyond pixel and map coordinates. Further, it tolerates inaccurate, missing and spurious points, and provides high performance with linear scalability. A final step performs transformation verification, globalization and optimization based upon an Iterative Closest Point Greedy algorithm. Experimentation shows that images covering a few city blocks with as few as 6 to 17 extracted road intersection points can be efficiently and correctly located using the road network of Dallas County, Texas, with over 80,000 intersections.