Assessing the Vibrational Frequencies of the Holweide Hospital in the City of Cologne (Germany) by Means of Ambient Seismic Noise Analysis and FE modelling

Ambient seismic noise measurements were conducted inside the Holweide Hospital (Cologne) for checking whether its frequencies of vibration fall into the range where soil amplification is expected. If this is the case, damage might increase in case of an earthquake due to an amplified structural response of the building. Two different techniques were used: the ratio between the horizontal and vertical components of the spectra recorded at stations located inside the building and the ratio between the corresponding components of the spectra recorded simultaneously inside the building and at a reference station placed outside. While the former method might be preferred because of less equipment involved, the latter has the advantage of producing more stable results and deleting automatically the influence of the sedimentary cover, which might obscure some eigenfrequencies of vibration of the building. An independently performed finite-element analysis of the hospital showed a good correlation between measured and calculated eigenmodes.     

Modelling and Mapping Damage to Forests from an Ice Storm Using Remote Sensing and Environmental Data

An extreme ice storm in January 1998 deposited up to 100 mm of ice and resulted in significant forest damage across eastern North America. Average crown loss of over 75% was recorded in large areas of eastern Ontario and southern Quebec. A primary question that arose following the storm was: can forest damage be effectively assessed using remote sensing and other available environmental data? This paper presents two contrasting studies to address this question. The first involves damage modelling at a local scale in an unmanaged forest using spectral and spatial information in high-resolution airborne imagery. Results of field data analyses are also given that show relations between damage and forest structure and composition as well as changes in forest structure that occurred in the years following the storm. The second study involves regional scale damage mapping in managed and unmanaged forests of eastern Ontario using medium resolution satellite imagery and other environmental data. In comparison of several image classification and data interpolation methods, the best damage map was produced using a neural network classifier and a mix of Landsat and environmental data. The methods and results presented in this paper form the basis for ongoing long-term temporal study of damage impacts on forest condition.     

光谱波段宽度对森林叶片叶绿素含量反演的影响分析

随着传感器技术的发展,高光谱数据光谱的波段宽度逐渐变窄,如何从海量的光谱数据中找到最优的光谱波段反演叶绿素含量,成为研究的难点问题。本文在测量华中农业大学狮子山6种主要树种的光谱数据和叶绿素含量的基础上,利用叶绿素指数(CI)和回归方法反演叶绿素含量,并分析了波段宽度对反演叶绿素含量结果的影响,结果发现波段宽度会影响到叶绿素反演的精度,当波段宽度为30nm时,叶绿素含量与"红边"区域(700nm-730nm)和近红外区域(770nm-800nm)叶绿素指标(CI)间的线性关系较好,决定系数可达到77.62%,均方根误差为10.6ug/cm2。     

黑体辐射定律遥感教学改革设计与实践

普朗克黑体辐射定律是遥感类课程教学的重点和难点,本文以定律分析为核心,从数值模拟大气层顶太阳光谱辐照度曲线、卫星传感器光谱响应函数卷积计算、地物行星反射率计算及地表温度反演4个方面入手,对黑体辐射定律理论教学和实践教学内容进行优化设计和教学实现。实践证明,该教学改革不仅可以使学生更容易理解和掌握黑体辐射定律揭示的基本规律,而且以此为基础,能够使学生通过实践加深对地物两大特性(反射特性和热辐射特性)的理解,提高学生对遥感类课程的兴趣。     

利用直方图匹配和低通滤波改进的SVR融合算法

针对SVR融合算法光谱失真的现象,提出了一种基于低通滤波和直方图匹配的改进SVR算法,即SVRFM算法。以IKONOS影像为实验数据,从光谱保真度和高频信息融入度两个方面将SVRFM与小波变换、SVR、Pansharp、Ehlers和Gram-Schmidt等算法的融合结果进行了定性和定量对比。结果表明,SVRFM算法的融合影像光谱信息失真小,高频信息融入度高。     

归一化光谱分解模型在城市化信息提取中的应用

以2001年7月11日LandsatETM7影像和2009年7月16日TM影像为数据源,基于V-I-S理论模型,采用归一化光谱分解模型提取了乌鲁木齐市区范围内2个时段的植被、土壤、不透水层3个连续地表参数分量。通过对不透水层不同阈值的划分,提取了2时段的乌鲁木齐市城市发展的空间信息,结果较为满意;通过空间叠加计算方式获取了8年来乌鲁木齐市城市化发展的空间信息和主要拓展方向。结果表明,乌鲁木齐城市化发展速度较快,特别是北扩趋势显著。     

基于水质类型的TM图像水体信息提取

通过对一般水体、富营养化水体和严重污染水体与山体阴影在TM各波段图像上的亮度值进行分析比较可知:一般水体在TM4图像上的亮度值小于TM3波段的,而山体阴影则相反;由于富营养化水体中的浮游植物在TM4波段具有强反射特征,严重污染水体对可见光具有强吸收作用,造成了这两类水体在TM4图像上的亮度值大于TM3波段的,因而无法通...     

基于光谱多尺度分割特征的高光谱混合像元分解

提高混合像元线性分解精度的一个关键点在于改善端元光谱矩阵的构成。本文提出一种基于光谱多尺度分割特征的混合像元分解方法。首先在分割段内离差平方和最小准则下,对高光谱影像的光谱进行多尺度分割,并以各分割段中对应像元的光谱平均值为光谱特征,最后以限制性的最小二乘方法估计出混合像元的组分。模拟与真实数据的实验结果表明,本文方法能够较大的提高遥感影像混合像元的分解精度,并且优于光谱维小波特征的分解。     

图像分类中基于核映射的光谱匹配度量方法

针对多光谱遥感数据特点利用SSV匹配技术改进高斯核函数得到新的KSSV函数,然后在由KSSV核函数映射得到的高维空间中利用SAM匹配技术代替基于欧氏距离的相似性度量。如此可以充分挖掘多光谱影像中的波谱特征信息并有效利用,提高模式识别方法应用的有效性。将此方法分别应用于非监督分类(k均值)与监督分类(最小距离、SVM)的试验表明,改进度量的分类方法可显著提高地类间的可区分度并有效降低类内的不一致性,更有效针对多光谱遥感影像中的地物类型,获得较好的精度改进。     

The Development of a Nonhydrostatic Global Spectral Model

With the development of numerical weather prediction technology,the traditional global hydrostatic models used in many countries of the world for operational weather forecasting and numerical simulations of general circulation have become more and more unfit for high-impact weather prediction.To address this,it is important to invest in the development of global nonhydrostatic models.Few existing nonhydrostatic global models use consistently the grid finite difference scheme for the primitive equations of dynamical cores,which can subsequently degrade the accuracy of the calculations.A new nonhydrostatic global spectral model,which utilizes the Eulerian spectral method,is developed here from NCAR Community Atmosphere Model 3.0(CAM3.0).Using Janjic's hydrostatic/nonhydrostatic method,a global nonhydrostatic spectral method for the primitive equations has been formulated and developed.In order to retain the integrity of the nonhydrostatic equations,the atmospheric curvature correction and eccentricity correction are considered. In this paper,the Held-Suarez idealized test and an idealized baroclinic wave test are first carried out,which shows that the nonhydrostatic global spectral model has similar climate states to the results of many other global models for long-term idealized integration,as well as better simulation ability for short-term idealized integration.Then,a real case experiment is conducted using the new dynamical core with the full physical parameterizations of subgrid-scale physical processes.The 10-day numerical integration indicates a decrease in systematic error and a better simulation of zonal wind,temperature,and 500-hPa height.