分层递阶雨水情信息系统的应用研究

针对现有雨水情系统存在稳定性、可靠性和智能性方面的问题,基于Saridis提出的智能控制理论,设计了分层递阶雨水情信息系统。该系统在现有两级系统的基础上,增加了专门处理雨水情信息的嵌入式设备,搭建了遥测终端与雨水情应用平台的联系桥梁,使遥测终端和雨水情应用平台分工、功能更加明确,新系统提高了原有系统的稳定性、可靠性,可根据任务执行情况的反馈信息,并及时更新决策方案,因此,智能化程度更高。     

雨洪资源利用进展与利用模式探索

对雨洪及雨洪资源利用的概念进行了界定,明确了雨洪资源开发利用的对象。在明确雨洪资源概念的基础上,概括了近20年来国内外在雨洪资源利用方面的研究和进展,并对国外在此利用技术和管理方面所取得的经验进行了总结。接下来用较多的篇幅对雨洪资源利用工程和非工程的措施进行了的介绍,在对每种利用方式加以剖析之后,分别引用了相应利用方式中比较典型的实例。最后对这些利用方式在未来的发展趋势做了初步的展望。     

绿色建筑雨水资源的利用

绿色建筑是可持续发展的产物,在节水方面,其倡导使用非传统水源和水资源的循环利用。发展绿色建筑有利于缓解水资源短缺和城市用水量不断增加的矛盾。绿色建筑的水系统及雨水资源利用技术,将绿色建筑及雨水利用结合起来,对生态和可持续发展有重要意义。     

Using k-nn and discriminant analyses to classify rain forest types in a Landsat TM image over northern Costa Rica

Conservation and land use planning in humid tropical lowland forests urgently need accurate remote sensing techniques to distinguish among floristically different forest types. We investigated the degree to which floristically and structurally defined Costa Rican lowland rain forest types can be accurately discriminated by a non-parametric k nearest neighbors (k-nn) classifier or linear discriminant analysis. Pixel values of Landsat Thematic Mapper (TM) image and Shuttle Radar Topography Mission (SRTM) elevation model extracted from segments or from 5 × 5 pixel windows were employed in the classifications. 104 field plots were classified into three floristic and one structural type of forest (regrowth forest). Three floristically defined forest types were formed through clustering the old-growth forest plots (n = 52) by their species specific importance values. An error assessment of the image classification was conducted via cross-validation and error matrices, and overall percent accuracy and Kappa scores were used as measures of accuracy. Image classification of the four forest types did not adequately distinguish two old-growth forest classes, so they were merged into a single forest class. The resulting three forest classes were most accurately classified by the k-nn classifier using segmented image data (overall accuracy 91%). The second best method, with respect to accuracy, was the k-nn with 5 × 5 pixel windows data (89% accuracy), followed by the canonical discriminant analysis using the 5 × 5 pixel window data (86%) and the segment data (82%). We conclude the k-nn classifier can accurately distinguish floristically and structurally different rain forest types. The classification accuracies were higher for the k-nn classifier than for the canonical discriminant analysis, but the differences in Kappa scores were not statistically significant. The segmentation did not increase classification accuracy in this study.     

基于粒子系统和Vega的实时雨雪模拟

在分析粒子系统实现原理的基础上,基于Vega提出了一种在大型场景漫游系统中实时模拟雨、雪的方法.基本思想是基于Vega特效模块粒子属性的设置,采用一种始终面向视点的多边形来表示雨、雪粒子模型.试验结果表明,该方法交互性强,能够有效地再现三维场景中的降雨、降雪景象,在实时交互漫游的前提下表现出较强的真实感.     

基于雨雾分离处理和多尺度网络的图像去雨方法

雨带来的雨条纹和雨雾会降低户外拍摄图像的质量,为了去除雨雾对图像的影响,提出了一种基于雨雾分离处理和多尺度卷积神经网络的图像去雨方法。首先利用导向滤波将雨线和图像细节信息提取到高频层,雨雾和背景信息则分离到低频层;然后构建多尺度卷积神经网络来去除高频层中的雨线,网络中融入多个稠密连接模块以提升特征提取的准确性;其次构建多层特征融合的轻量级去雾网络来去除低频层中的雨雾,采用参数一体化结构避免了估计多个大气散射模型参数导致的次优解;最后再结合处理后的高低频结果还原出清晰图像。在多个合成的雨雾数据集以及真实自然场景图像上进行测试,定性和定量结果表明,提出的方法在去除雨雾影响的同时较好地保留了色彩信息,和近年的算法相比,图像结构相似性约提升了0.02~0.08,图像峰值信噪比约提升了0.2~3.5 dB。     

基于GPU粒子系统的大规模场景高效雨雪实时模拟

粒子系统实现的雨雪效果能有效增强三维场景的真实感,传统基于中央处理器（CPU）运算模拟的粒子系统占用了大量CPU运算时间,难以达到实时模拟的要求。为此提出了一种基于图形处理器的（GPU）运算的粒子系统来模拟的雨雪场景。该方法通过在GPU中重复使用消亡粒子在视点坐标系内生成新粒子,并在几何着色器中将粒子的点坐标转换为矩形坐标,将CPU从复杂庞大的几何运算中解放出来,从而大幅增加了场景绘制的微粒数,使雨雪场景模拟的实时性和逼真度得到增强。     

谈园林布局的艺术手法

中国园林布局的艺术手法有着丰富的主题思想和含蓄的意境,本文主要从园林布局的艺术手法中的主题多样、欲扬先抑、曲折迂回、尺度得当、余意不尽、远借邻借、隔而不塞来谈及园林布局的艺术手法。     

Ka频段卫星通信上行链路自适应功率控制

为提高Ka频段（30GHz／20GHz）卫星通信系统上行链路功率控制的可靠性,提出一种上行链路自适应功率控制算法。该方法基于自回归滑动平均模型,能由测量到的下行链路降雨衰减值预测出上行链路的降雨衰减值,从而提高功率控制精度。仿真结果表明,该方法对降雨衰减具有较好的补偿效果。     

Redefining the Water Poverty Index

Abstract

The Water Poverty Index (WPI) of arid and semiarid climatic zones is redefined by introducing the contribution of rainfed agriculture into WPI calculations and by making the WPI equation account for diversities in climatic conditions within arid and semiarid zones and for recycled household water used in irrigation.