SAGE测光巡天数据处理方法研究

元素丰度与星系演化(Stellar Abundance and Galactic Evolution,SAGE)是自主设计的能够准确计算恒星大气参数以及消光的新测光系统。对北天除银盘外共计约12 000 deg2的天区开展了SAGE系统测光巡天,计划获取约5亿颗恒星的高精度测光数据。单次曝光条件下100σ完备星等uSC～17. 3,vSAGE～16. 8(AB星等),这些为研究银河系提供宝贵的测光资料。介绍了巡天专用的数据处理程序的研究和开发,主要研究了针对单幅图像的快速自动化处理过程,重点介绍数据改正、天体测量校正、测光和流量定标过程,以及数据结果和数据质量检测等。     

基于GPS新型L5信号的地表雪深反演研究

利用GPS多路径反射信号测量地表雪深具有全天候和高时空分辨率的特点,因此其可作为一种代替气象站监测雪深的新手段。然而,先前大多数研究仅使用了GPS L1和L2C波段信噪比数据探测积雪深度。为验证新型的L5信号在雪深反演方面的优越性,本文阐述了GPS-R技术反演雪深的原理,利用Lomb-Scargle周期图法所处理的受积雪表层影响的信噪比数据计算了频谱振幅强度,通过获取频谱特征值与天线高度的关系求解雪深值,最后分别与L1反演结果和实测雪深数据进行了对比。试验结果表明：与现有的GPS-R测量雪深结果相比,利用新型的L5反射信号反演地表雪深的精度更佳;采用GPS-R技术探测雪深对把握测站区域内的雪深变化情况和淡水资源储量具有重要价值。     

GIS支持下的土地资源环境承载力评价——以荣成市为例

随着人类生产活动的日益加剧,土地资源环境已逐渐成为制约社会经济发展的主要因素。基于荣成市土地资源环境要素,利用层次分析法构建了区域土地资源环境承载力评价体系。对土地资源进行基础性评价,在GIS技术支持下计算各项指标分值,并得出承载状态压力指数;在基础性评价结果的基础上,对水资源、生态条件与环境质量进行修正性评价。结果显示,荣成市土地资源环境基础性评价为可载,基于水资源系统的综合承载状态为临界,基于生态条件与环境质量系统的综合承载状态为可载。     

Developing a comprehensive evaluation method for Interconnected River System Network assessment: A case study in Tangxun Lake group

Journal of Geographical Sciences - The Interconnected River System Network (IRSN) plays a crucial role in water resource allocation, water ecological restoration and water quality improvement. It...     

单锚腿系泊系统动力计算的新方法

在Hamilton型拟变分原理体系下,建立了一种时间子域以三次和五次B样条函数插值的时间子域法,并将这种新方法用于单锚腿系泊系统的动力响应分析中。算例表明,新方法比传统的动力计算方法Wilson-θ法,在计算精度上有明显的优势,表明本方法能够用于计算单锚腿系泊系统的动力响应。     

Coupling winds to ocean surface currents over the global ocean

A Wind stress–Current Coupled System (WCCS) consisting of the HYbrid Coordinate Ocean Model (HYCOM) and an improved wind stress algorithm based on Donelan et al. [Donelan, W.M., Drennan, Katsaros, K.B., 1997. The air–sea momentum flux in mixed wind sea and swell conditions. J. Phys. Oceanogr. 27, 2087–2099] is developed by using the Earth System Modeling Framework (ESMF). The WCCS is applied to the global ocean to study the interactions between the wind stress and the ocean surface currents. In this study, the ocean surface current velocity is taken into consideration in the wind stress calculation and air–sea heat flux calculation. The wind stress that contains the effect of ocean surface current velocity will be used to force the HYCOM. The results indicate that the ocean surface velocity exerts an important influence on the wind stress, which, in turn, significantly affects the global ocean surface currents, air–sea heat fluxes, and the thickness of ocean surface boundary layer. Comparison with the TOGA TAO buoy data, the sea surface temperature from the wind–current coupled simulation showed noticeable improvement over the stand-alone HYCOM simulation.     

京杭大运河保护地理信息系统建设研究

京杭大运河是独特的超大型文化遗产,其保护工作面临着复杂的形势和问题,需要新的理论方法和技术手段支持。以地理信息系统（GIS）,遥感（RS）,全球定位系统（GPS）为核心的空间信息技术在空间信息获取、处理、管理和分析上有着强大的优势。本文根据空间信息科学和文化遗产保护理论,结合京杭大运河保护实际业务需求,探讨了基于空间信息技术的京杭大运河保护地理信息系统的建设思路和建设方法,设计和开发了京杭大运河保护地理信息系统并实际应用于京杭大运河历史文化环境保护工作中,产生了一系列专题研究成果。结果表明：空间信息技术可以为大运河保护提供强有力的技术支持和可靠保障。     

GIS技术在房地产市场信息系统中的应用研究

简要介绍了当前国内房地产现状、存在的问题,以及房地产市场信息系统（Real Estate Market Information System,以下简称REMIS）当前所处的发展背景,指出房产GIS在标准和应用上存在的一些问题。对房地产管理和REMIS对GIS的需求情况进行了分析。根据需求分析作者提出了GIS技术在REMIS中的几种应用模式,并指出基于楼盘表为核心的GIS应用模式将是未来房产GIS发展的方向。针对房产GIS应用的不同模式采用的几种关键技术也做了相应描述。     

System identification for nonlinear maneuvering of large tankers using artificial neural network

This paper deals with the application of nonparametric system identification to a nonlinear maneuvering model for large tankers using artificial neural network method. The three coupled maneuvering equations in this model for large tankers contain linear and nonlinear terms and instead of attempting to determine the parameters (i.e. hydrodynamic derivatives) associated with nonlinear terms, all nonlinear terms are clubbed together to form one unknown time function per equation which are sought to be represented by the neural network coefficients. The time series used in training the network are obtained from simulated data of zigzag maneuvers and the proposed method has been applied to these data. The neural network scheme adopted in this work has one middle or hidden layer of neurons and it employs the Levenberg–Marquardt algorithm. Using the best choices for the number of hidden layer neurons, length of training data, convergence tolerance etc., the performance of the proposed neural network model has been investigated and conclusions drawn.     

Climatic regimes and the recruitment rate of anchoveta, Engraulis ringens, off Peru

The recruitment rate of Peruvian anchoveta, Engraulis ringens, was studied to test the hypothesis that long-term environmental variation (regime shifts) had a significant impact on density-dependent processes governing the anchovy recruitment during the period 1963–2004. On the basis of previous defined regimes and turning points for the Humboldt Current System, we identified two groups of years for increased recruitment of anchoveta (1963–1971 and 1986–2004), and one unfavorable period (1972–1985). A common intercept and significantly different slopes were found when the recruitment rate was plotted as a function of the spawning stock biomass during those groups of years, suggesting that density-dependent effects on recruitment were affected during different climate regimes. The favorable (unfavorable) regime was characterized by higher (lower) zooplankton volumes, and with a higher frequency of colder (warmer) waters. Dome-shaped relationships between recruitment rate, spawning stock biomass and SST, were detected with a Generalized Additive Model for the favorable regime. Thus, recruitment could be explained by non-linear effects of environmental variables. Ultimately, climatic regimes are affecting the density-dependent effects on recruitment of anchoveta and the mechanisms involved may be associated with changes in the carrying capacity of the spawning habitat of anchoveta off Peru, which in turn are related with the effects of cold and warm regimes.