遥感影像三维可视化研究

利用DEM高程资料实现遥感影像的三维显示可大大提高遥感监测产品的使用价值，而商用软件成本高操作繁琐普及困难。利用计算机图形学知识和Delphi编程语言，开发了一套遥感影像三维可视化软件。对在开发过程中遇到的有关DEM数据的裁剪与拼接、图像配准、地表模拟、透视变换、消隐处理、光照和阴影效果以及颜色变换等问题的解决方案和实现方法作了简要的介绍。     

GPS水汽遥感中的大气干延迟局地订正模型研究

在GPS遥感水汽过程中,大气干延迟模型的精度直接影响水汽遥感的精度。根据广东清远站1995～2001年的气象探空资料,计算了GPS水汽测量中的实际大气干延迟。在此资料基础上,利用地面气象要素建立了大气干延迟的年和分月局地订正模型。分析结果表明,年模型的精度优于目前广泛使用的普适模型;月模型与年模型相比,效果不是很明显,建立局地分月订正模型意义不大;在对高度角的敏感程度上,局地模型略大些;当高度角小于75时,大气干延迟弯曲路径与直线路径之差ΔS随天顶角增大而迅速增大。     

Spatially weighted supervised classification for remote sensing

A simple approach for incorporating a spatial weighting into a supervised classifier for remote sensing applications is presented. The classifier modifies the feature-space distance-based metric with a spatial weighting. This is facilitated by the use of a non-parametric (k-nearest neighbour, k-NN) classifier in which the spatial location of each pixel in the training data set is known and available for analysis. A remotely sensed image was simulated using a combined Boolean and geostatistical unconditional simulation approach. This simulated image comprised four wavebands and represented three classes: Managed Grassland, Woodland and Rough Grassland. This image was then used to evaluate the spatially weighted classifier. The latter resulted in modest increase in the accuracy of classification over the original k-NN approach. Two spatial distance metrics were evaluated: the non-centred covariance and a simple inverse distance weighting. The inverse distance weighting resulted in the greatest increase in accuracy in this case.     

后遥感应用技术研究与地质实践——以东胜—神木地区铀资源勘查为例

介绍了后遥感应用技术提出的背景及技术构成,阐述了该技术的研究内容及取得的地质成果。实践表明,在地质勘查领域,后遥感应用技术比单一遥感技术具有更大的实用价值和更好的应用效果。     

微波焙烧炉在分析测试中的应用研究

本文详细论述了微波焙烧炉代替马弗炉应用于样品焙烧、熔融、活性炭灰化工作中的实际效果。结果表明：其应用不但可行，而且与马弗炉相比，微波焙烧炉具有更加优越的经济性与环保效果。     

Application of Remote Sensing in Flood Management with Special Reference to Monsoon Asia: A Review

The conventional means to record hydrological parameters of aflood often fail to record an extreme event. Remote sensingtechnology along with geographic information system (GIS)has become the key tool for flood monitoring in recent years.Development in this field has evolved from optical to radarremote sensing, which has provided all weather capabilitycompared to the optical sensors for the purpose of flood mapping.The central focus in this field revolves around delineation of floodzones and preparation of flood hazard maps for the vulnerable areas.In this exercise flood depth is considered crucial for flood hazardmapping and a digital elevation model (DEM) is considered to bethe most effective means to estimate flood depth from remotelysensed or hydrological data. In a flat terrain accuracy of floodestimation depends primarily on the resolution of the DEM. Riverflooding in the developing countries of monsoon Asia is very acutebecause of their heavy dependence on agriculture but any floodestimation or hazard mapping attempt in this region is handicappedby poor availability of high resolution DEMs. This paper presents areview of application of remote sensing and GIS in flood managementwith particular focus on the developing countries of Asia.     

基于PRS的遥感图像地物信息提取模型

点源理论(PRS)是一种面向应用需求的集中信息处理方式。不同尺度、不同分辨率的点都是一定的综合信息场,是客观世界的真实反映。本文在数字图像处理过程中引入点源理论,探讨针对地物空间信息应用服务的遥感信息分析和处理模型,讨论基于点源的图像构造、知识构造及地物模型建造过程,给出基于点源的遥感图像地物提取流程。     

概率神经网络与BP网络模型在遥感图像分类中的对比研究

通过分析概率神经网络(以下称PNN)的基本结构及其训练算法,建立了卫星图像分类的概率神经网络模型,并通过实例对比分析了概率神经网络与BP网络分类模型的分类效果。实验表明,PNN图像分类方法在分类精度上优于误差反向传播神经网络模型,且分类时间相当,是一种有效的图像分类方法。     

基于光谱信息的遥感图像空间域自适应滤波

遥感图像往往由于内外因素的干扰含有各种噪声 ,为提高图像质量人们对其进行滤波。常规的滤波方式完全基于图像空间域 ,在消除异常点使图像平滑的同时使边界变得不清楚从而使图像模糊 ;或者正相反 ,在边缘信息得到增强时也放大了图像噪声而使图像变得粗糙。该文的自适应滤波方法充分利用多光谱和高光谱遥感图像的光谱维信息 ,滤波时不仅要使均匀的地块得到平滑 ,而且要使地块间的边缘、局部的异常点、线仍然得到保存、在光滑的同时尽量保持原有的数值特征     

Estimation of ocean primary productivity and its spatio-temporal variation mechanism for East China Sea based on VGPM model

According to calculation results of ocean chlorophyll concentration based on SeaWiFS data by SeaBAM model and synchronous ship-measured data, this research set up an improved model for CaseⅠand CaseⅡwater bodies respectively. The monthly chlorophyll distribution in the East China Sea in 1998 was obtained from this improved model on calculation results of SeaBAM. The euphotic depth distribution in 1998 in the East China Sea is calculated by using remote sensing data of K490 from SeaWiFS according to the relation between the euphotic depth and the oceanic diffuse attenuation coefficient. With data of ocean chlorophyll concentration, euphotic depth, ocean surface photosynthetic available radiation (PAR), daily photoperiod and optimal rate of daily carbon fixation within a water column, the monthly and annual primary productivity spatio-temporal distributions in the East China Sea in 1998 were obtained based on VGPM model. Based on analysis of those distributions, the conclusion can be drawn that there is a clear bimodality character of primary productivity in the monthly distribution in the East China Sea. In detail, the monthly distribution of primary productivity stays the lowest level in winter and rises rapidly to the peak in spring. It gets down a little in summer, and gets up a little in autumn. The daily average of primary productivity in the whole East China Sea is 560.03 mg/m2/d, which is far higher than the average of subtropical ocean areas. The annual average of primary productivity is 236.95 g/m2/a. The research on the seasonal variety mechanism of primary productivity shows that several factors that affect the spatio-temporal distribution may include the chlorophyll concentration distribution, temperature condition, the Yangtze River diluted water variety, the euphotic depth, ocean current variety, etc. But the main influencing factors may be different in each local sea area.