空间逐步寻优数据挖掘在遥感影像分类中的应用

在遥感地学分析模型中,由于遥感信息模糊和不确定性的特点,其特征空间中的特征分布并不完全符合特定的高斯密度分布,而是分布形状各异,相互交错,用传统模型是很难获得特征的最优分布解的,而空间逐步寻优数据挖掘方法(SOMM)是在演化寻优理论的基础上,融合知识的参数化分布函数,来逐步分离特征空间,逐步降解的获得特征树状的层次结构。结合实例,用SOMM方法对遥感影像进行分类计算,并与传统的最大似然分类方法的分类结果进行了比较。     

UWB室内距离交会定位算法的研究与性能分析

在众多室内定位技术中,超宽带(ultra-wideband,UWB)技术以其极大的带宽、高时间分辨率、高速数据传输等特点而备受关注,目前,UWB超宽带定位技术已广泛应用于展厅、仓库、超市、图书馆、矿井等环境中。针对基于超宽带室内距离交会定位原理的最小二乘算法及几何算法两种算法的性能进行了实验与评估,不仅比较了平面定位精度,而且对比了两种算法的执行时间。实验结果显示,在平面定位中,最小二乘算法具有更好的内、外符合精度,可以更为准确的估计移动目标的位置信息;但几何算法在执行时间和计算效率方面有着显著的优势。     

祁连山东北缘最大风速气候特征

依托祁连山东北缘5个基本站和35个区域站观测资料,通过回归重建1971-2013年最大风速数据库,运用mann-kendall检验、EOF经验正交函数、耿贝尔分布分析了研究区域最大风速特征。结果表明:最大风速在明显减小,民勤尤为明显(0.1879 m·s-1·a-1),在最大风速分布上形成3个极值中心:一是以红沙岗为代表的北部荒漠地区(22.75 m·s-1),二是以红山窑为代表的西部荒滩地区(21.76 m·s-1),三是以乌鞘岭为代表的祁连山地(21.54 m·s-1)。以红沙岗、红山窑、丰乐、乌鞘岭为代表站,分析发现前三者最大风速递减率分别为-0.173、-0.104、-0.103,特征显著,但乌鞘岭基本围绕在平均值附近波动。年最大风速多出现在2~6月,尤其以4~5月份为高发期,占到全年的34.8%~56.8%,EOF第一特征向量进一步揭示了北部沙漠地区和祁连山地的典型风险特征。以南湖—红崖山—昌宁为界的北部沙漠地带在未来10 a、20 a、30 a、50 a间最大风速分别为29.18、30.20、30.82、31.63 m·s-1,为典型的风灾危险区域。本文用区域站资料为最大风速危险区划提出了一些分析结论,可作为项目设计、民生安全、经济发展的参考依据,一定程度上填补了研究空白。     

Role of Ozone Deposition in the Occurrence of the Spring Maximum

Abstract

A hypothesis has been formulated on the basis of experimental data presented in this article. According to the hypothesis, occurrence of the spring surface ozone maximum at mid-latitudes results from a delay in snow-cover melt. The data were collected at ozone stations in Minsk (Belarus) and Preila (Lithuania). Because the measurements of surface ozone concentration are quite different, despite the close proximity of the stations, a conclusion can be drawn about the significant influence of meteorological parameters on measurements. In addition to a rather subjective and poorly defined parameter—time of snow melt—the difference between the average March temperature and a climatological mean may be treated as a criterion for the presence or absence of the spring ozone maximum.     

一种基于众数赋值的高光谱图像地物分类方法

提出了一种融合监督分类与非监督分类结果的高光谱遥感影像分类新方法——众数赋值分类法。采用ISODATA非监督分类方法对高光谱遥感影像进行分类,并对非监督分类结果的图斑进行标记,同时用最大似然法(ML)和支持向量机(SVM)法进行监督分类,然后以监督分类结果对非监督分类后各斑块进行类别赋值。方法是:统计每个非监督分类斑块中由监督分类所获得的各类别像元数及所占比例,将非监督分类斑块的类别赋予所占比例最高的监督分类结果的类别,最终获得高光谱图像分类结果。研究表明:(1)非监督分类类别数量大于10时,其与ML分类结果融合的总体分类精度和Kappa系数均较监督分类法的分类结果好;(2)ML和20个类别的ISODATA分类结果融合的总体精度最高,为87.35%,比单独ML的总体精度高约2个百分点;(3)SVM和10个类别的ISODATA分类结果融合的总体精度提高最大,较SVM的总体精度提高近3个百分点;(4)随着非监督分类类别数量的增多,分类结果的总体精度呈现由低到高再到低的变化过程。     

Estimation of ecological high flow

Floods can destroy fish habitat. During a flood a fish has to seek shelters (refuges) to survive. It is necessary to know the maximum discharge that the fish can sustain against the strong current. Ecological and hydraulic engineers can simulate the flow condition of high flow for designing the refuge when restoring and enhancing the rivers are needed. Based on the average ratio of the mean and maximum velocities invariant with time, discharge and water level, this paper tries to introduce the concept of ecological high flow. The mean‐maximum velocity ratio can be used to estimate the mean velocity of the river. If the maximum velocity of the cross section is replaced by the maximum sustained swimming speeds of fish, the mean velocity of ecological high flow can be calculated with the constant ratio. The cross‐sectional area can be estimated by the gage height. Then the ecological high flow can be estimated as the product of mean velocity of ecological high flow multiplied by the cross‐sectional area. The available data of the upstream of the Dacha River where is the habitat of the Formosan landlocked salmon were used to illustrate the estimation of the ecological high flow. Any restoration project at Sonmou that try to improve the stream habitat can use the ecological high flow to design the hydraulic structure at suitable location to offer refuges for the Formosan landlocked salmon that is an endangered species in Taiwan Copyright © 2005 John Wiley & Sons, Ltd.     

Frequency analysis for predicting 1% annual maximum water levels along Florida coast,US

In the Coastal Flood Insurance Study by the Federal Emergency Management Agency (FEMA, 2005), 1% annual maximum coastal water levels are used in coastal flood hazard mitigation and engineering design in coastal areas of USA. In this study, a frequency analysis method has been developed to provide more accurate predictions of 1% annual maximum water levels for the Florida coast waters. Using 82 and 94 years of annual maximum water level data at Pensacola and Fernandina, performances of traditional frequency analysis methods, including advanced method of Generalized Extreme Value distribution method, have been evaluated. Comparison with observations of annual maximum water levels with 83 and 95 years of return periods indicate that traditional methods are unable to provide satisfactory predictions of 1% annual maximum water levels to account for hurricane‐induced extreme water levels. Based on the characteristics of annual maximum water level distribution of Pensacola and Fernandina stations, a new probability distribution method has been developed in this study. Comparison with observations indicates that the method presented in this study significantly improves the accuracy of predictions of 1% annual maximum water levels. For Fernandina station, predictions of extreme water level match well with the general trend of observations. With a correlation coefficient of 0·98, the error for the maximum observed extreme water level of 3·11 m (National Geodetic Vertical Datum) with 95 years of return period is 0·92%. For Pensacola station, the prediction error for the maximum observed extreme water level with a return period of 83 years is 5·5%, with a correlation value of 0·98. The frequency analysis has also been reasonably compared to the more costly Monte Carlo simulation method. Copyright © 2008 John Wiley & Sons, Ltd.     

The influences of the Southern and North Atlantic Oscillations on climatic surface variables in Turkey

In this study, Turkish climatic variables (precipitation, stream flow and maximum and minimum temperatures) were first analysed in association with both the Southern Oscillation (SO) and the North Atlantic Oscillation (NAO). The relationships between Turkish maximum and minimum monthly temperatures and the extreme phases of the SO (El Niño and La Niña events) were examined. The results of this analysis showed that relationships between Turkish monthly maximum temperatures and El Niño and La Niña contain some complexity still to be identified, because both events produce a signal indicating a correspondence with cold anomalies in the aggregate composites. A relationship between turkish minimum temperatures and El Niño was detected in western Anatolia, whereas there was no significant and consistent signal associated with La Niña. Moreover a series of cross‐correlation analyses was carried out to demonstrate the teleconnections between the climatic variables and both the NAO and SO. The NAO during winter was found to influence precipitation and stream‐flow patterns. In contrast temperature patterns appeared to be less sensitive to the NAO. Furthermore, lag‐correlation results indicated a prediction potential for both precipitation and stream‐flow variables in connection with the NAO. Simultaneous and time‐lag correlations between the climatic variables and the SO index, in general, indicated weaker relationships in comparison with those for the NAO. These analyses also showed that the influences of the SO on Turkish temperature data are negligible. The outcomes were presented in conjunction with an explanation regarding physical mechanisms behind the implied teleconnections. Copyright © 2004 John Wiley & Sons, Ltd.     

Changes in flow conveyance and implication for flood protection,Sava River,Zagreb

A low‐lying part of the Croatian capital, Zagreb, is exposed to flood risk from the Sava River. The biggest flood to data, with catastrophic consequences, occurred on 26 November 1964. To protect Zagreb from the Sava River floods, a flood control system was built and set in operation at the end of 1978. The Sava River's flood response changed over time as a result of this constructed system, as well as other anthropogenic and natural influences. The series of maximum annual Sava River stages and discharges measured at the Zagreb gauging station from 1926 to 2004 were analysed. Hydrological methods were used in order to assess Zagreb safety from the Sava River floods in the new conditions. This paper detects changes in high water occurrence in the Sava River near Zagreb. Long‐term stages and linear trends in discharges were examined. A simple technique for the conversion of stages to actual river channel morphology conditions was used. The technique presented in this paper enabled the recalculation of flood probabilities. It is stressed that for a complete understanding of floods, an examination should include the study of parameters of both maximum stages and maximum discharges. Copyright © 2007 John Wiley & Sons, Ltd.     

Annual streamflow modelling with asymmetric distribution function

Classical autoregressive models (AR) have been used for forecasting streamflow data in spite of restrictive assumptions, such as the normality assumption for innovations. The main reason for making this assumption is the difficulties faced in finding model parameters for non‐normal distribution functions. However, the modified maximum likelihood (MML) procedure used for estimating autoregressive model parameters assumes a non‐normally distributed residual series. The aim in this study is to compare the performance of the AR(1) model with asymmetric innovations with that of the classical autoregressive model for hydrological annual data. The models considered are applied to annual streamflow data obtained from two streamflow gauging stations in K?z?l?rmak Basin, Turkey. Copyright © 2008 John Wiley & Sons, Ltd.