福建港口体系结构研究

阐述了福建港湾自然条件和港口开发现状,采用赫希曼-赫芬达尔指数分析近20年来港口体系空间结构的动态演变规律,结果表明,福建港口体系空间结构演变总趋势呈分散化。这说明了港口间的竞争大于合作,职能结构趋同,因而形成合理分工与协作的福建港口群是当务之急。鉴于此,运用模糊聚类、货种区位商等分析技术,对其体系内的港口等级层次、职能结构的基本特征进行探讨,并在此基础上提出了各港口职能分工的发展方向。     

Supervised neural network recognition of habitat zones of rice invertebrates

This study aimed to evaluate effectiveness and performance of several supervised neural network models and make pattern recognition on invertebrate habitat zones. Probabilistic, general regression, and linear neural networks, and discriminant analysis were used to recognize both known and unknown invertebrate habitat zones. The results showed that neural network models were better than traditional discriminant analysis in the recognition of known habitat zones. There was not distinctive variation in recognition from different neural network models. Sensitivity analysis indicated that the learning rate of the neural network would influence recognized results. An unknown invertebrate species from Lepidoptera was recognized to be soil-dweller (dryland) by both neural network models and discriminant analysis. In sensitivity analysis it was additionally recognized to be the type of plant canopy (terrestrial). Overall the species was estimated to be a soil-dweller (dryland) or live on plant canopy (terrestrial). It was concluded that neural network models can perform better than conventional statistic models in pattern recognition, but a comprehensive comparison among various models is necessary in order to achieve a high reliable recognition and prediction. Furthermore, sensitivity analysis can lead to an in-depth grasp on the mechanism in the recognition and is thus needed.     

Inferred ground motions on Guadeloupe during the 2004 Les Saintes earthquake

Accurate estimates of the ground motions that occurred during damaging earthquakes are a vital part of many aspects of earthquake engineering, such as the study of the size and cause of the uncertainties within earthquake risk assessments. This article compares a number of methods to estimate the ground shaking that occurred on Guadeloupe (French Antilles) during the 21st November 2004 (M _w 6.3) Les Saintes earthquake, with the aim of providing more accurate shaking estimates for the investigation of the sources of uncertainties within loss evaluations, based on damage data from this event. The various techniques make differing use of the available ground-motion recordings of this earthquake and by consequence the estimates obtained by the different approaches are associated with differing uncertainties. Ground motions on the French Antilles are affected by strong local site effects, which have been extensively investigated in previous studies. In this article, use is made of these studies in order to improve the shaking estimates. It is shown that the simple methods neglecting the spatial correlation of earthquake shaking lead to uncertainties similar to those predicted by empirical ground-motion models and that these are uniform across the whole of Guadeloupe. In contrast, methods (such as the ShakeMap approach) that take account of the spatial correlation in motions demonstrate that shaking within roughly 10 km of a recording station (covering a significant portion of the investigated area) can be defined with reasonable accuracy but that motions at more distant points are not well constrained.     

我国资源卫星资料应用对空间分辨率的需求

在简介了我国3种对地遥感卫星的基础上,归纳出我国主要应用领域对遥感图像空间分辨率的需求状况。     

福建省及其沿海和台湾海峡频度统计与分析

本文采用空间扫描方法 ,按选区和时段做震级—频度统计 ,计算年平均地震数。通过比较与分析 ,得出三点初步结论     

Developing a bivariate spatial association measure: An integration of Pearson's r and Moran's I

 This research is concerned with developing a bivariate spatial association measure or spatial correlation coefficient, which is intended to capture spatial association among observations in terms of their point-to-point relationships across two spatial patterns. The need for parameterization of the bivariate spatial dependence is precipitated by the realization that aspatial bivariate association measures, such as Pearson's correlation coefficient, do not recognize spatial distributional aspects of data sets. This study devises an L statistic by integrating Pearson's r as an aspatial bivariate association measure and Moran's I as a univariate spatial association measure. The concept of a spatial smoothing scalar (SSS) plays a pivotal role in this task. Received: 07 November 2000 / Accepted: 02 August 2001     

The development of an intervening opportunities model with spatial dominance effects

In this paper an intervening opportunities model with spatial dominance is developed. The usual assumption in spatial theory is that decision makers are influenced not just by the size of a destination or distance but by these two factors in combination, that is, spatial dominance. Decision-makers will have more knowledge about, and clearly perceive destinations that exert the greatest amount of spatial dominance on their origins, just as they would primate cities. Thus destinations are ranked in terms of the spatial dominance calculated for each destination. Empirical verification of the model utilizes state-to-state migration flow data for the US. Calibration results compare favourably with the traditional intervening opportunities model and the production constrained gravity model. Received: 7 October 1999/Accepted: 15 June 2000     

Solution and econometric estimation of spatial dynamic models in continuous space and continuous time

 This paper presents and demonstrates a general approach to solving spatial dynamic models in continuous space and continuous time that characterize the behaviour of intertemporally and interspatially optimizing agents and estimating from discrete data the parameters of such models. The approach involves the use of a projection method to solve the models and a quasi-Newton algorithm to update quasi-FIML parameter estimates. Received: 26 July 2000 / Accepted: 31 January 2001     

20世纪80年代中国地区大气气溶胶光学厚度的平均状况分析

利用中国北京等 41个甲种日射站 1 979～ 1 990年太阳直接辐射日总量和日照时数等资料 ,配合同期 TOMS version - 7臭氧观测资料 ,反演了 41个站逐年、逐月 0 .75μm大气气溶胶的平均光学厚度值 (Aerosol Optical Depth,AOD) ,据此分析了 1 2 a来中国大气气溶胶的变化和时空平均分布特征。结果表明 :中国大气气溶胶光学厚度 AOD的多年平均分布是以四川盆地为中心向四周减少 ,南疆盆地和长江中游武汉附近为另两个大值中心 ;长江中下游大部分地区、山东半岛以及广东沿海等 ,AOD值亦较大 ;而东北大部、西北大部、云南和福建沿海等地 AOD较小。AOD各月平均分布有所不同。中国绝大部分地区春季 AOD值最大 ,最小值则各地不同。 1 979～ 1 990年 ,青藏高原、四川盆地西部、贵州北部、长江中下游大部分地区、山东半岛和南疆盆地西部等 ,AOD呈增长趋势。而东北地区、西北地区大部、云贵高原和广西西部以及华东沿海等地 AOD呈减小势态。中国地区 AOD的季节变化曲线大体可分为单峰、一峰一谷、两峰一谷和多峰等 4种类型     

A Simple Temporal and Spatial Analysis of Flow in Complex Terrain in the Context of Wind Energy Modelling

A simple temporal and spatial analysisis done on wind speed and direction data from a number ofmeteorological towers separated by distances between roughly 1 and 100 kilometres. The analysis is done in the context of expected model error in wind energy calculations. The study first uses single point statistics to show the evolution of mean values with time. It is shown that strong seasonal signals are present and that stable means are achieved only after averaging periods of a year or more. The study then uses discrete Fourier transforms to show that significant amounts of spectral energy reside in modes with periods of a few days to less than a day. Frequency dependent cross correlation values are then derived and used to show how correlation between towers diminishes with increasing frequency. The mechanism responsible for this diminished correlation is shown through the comparison of cross-correlation phase as a function of frequency and its relationship to distance between towers. Error in wind energy estimates are shown to be strongly related to correlation and therefore distance over which the prediction is made. In summary, much of the inaccuracy in modelling flow in the context of wind energy calculations is due to a lack of scale separation between the deterministic part of the flow, which is well modelled, and that part of the flow that is stochastic at the length and time scales modelled.