局部型地形因子并行计算方法研究

 随着分析区域的扩展及需求精度的提高,数据-计算密集型地形分析亟需通过并行化来满足用户的时间响应需求。局部型地形因子是以一定半径的分析窗口(通常为3×3)计算且具有单元计算结果独立性的地形信息,是数字地形分析的基本参数。本文在分析局部型地形因子串行算法特征的基础上,以坡度算法为样本,对局部型地形因子的并行计算方法进行了深入研究。从数据并行的角度,对并行计算环境下的数据划分粒度、方式及结果融合策略进行了分析,构建了局部型地形因子的并行计算方法。利用SRTM陆地表面地形DEM数据,设计了坡度并行计算的实验以验证其方法的正确性和实用性。实验结果表明,本文提出的并行计算方法顾及了任务、数据及计算环境,可快速对局部型地形因子串行算法进行并行化改造,提高算法的执行效率,具有较好的并行性能。     

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基于扇形子镜的12m光学红外望远镜拼接共相误差仿真分析

为满足国内对应用大型通用光学望远镜在光学红外波段进行天文观测的需求, 中国计划建设一架12 m大口径光学红外望远镜(12-meter large aperture optical-infrared telescope, LOT). LOT对于中国天文界具有极其重要的意义, 将会在近红外波段实现共相. LOT的主镜将采用子镜拼接的方案, 由72块扇形子镜拼接而成, 并且中央部分有一块直径4.5m的圆形镜. 分析了采用扇形子镜拼接方案下LOT的共相误差, 提供了详细的共相误差理论推导过程, 并对包括3种子镜面外误差在内的误差源进行深入的单独模拟和综合模拟. 在共相波长为1μm的条件下, 当服从正态分布的倾斜误差的均方根值小于0.016^\prime\prime或服从正态分布的活塞误差的均方根值小于42.5nm时, LOT的斯特列尔比大于0.8. 仿真结果对于采用共相拼接镜面主动光学的主镜在LOT中的应用具有重要意义.     

基于海量海底地形数据的存储和可视化研究

针对海量海底地形数据的存储和可视化的技术难点,提出一种基于细节层次模型的处理技术。使用这种技术,可以对海底地形模型进行有效的管理。通过实验证明,使用细节层次模型技术可以对海底地形模型进行高效绘制。     

基于贝叶斯正则化BP神经网络的DEM趋势面逼近

趋势面从宏观上揭示了研究对象的特性,在各领域发挥着重要作用。BP神经网络可以对复杂系统进行无限逼近,进而进行预测。建立了基于贝叶斯正则化BP神经网络的数字高程模型趋势面,与二次多项式建立的数字高程模型趋势面进行比较分析,证明了该方法的可行性和有效性。     

月面形貌的3维可视化算法

基于大范围地形可视化算法研究的基础上,对平面geometry clipmaps算法进行改进,利用GPU的顶点着色器实现平面地形向球面地形的投影变换,并综合利用球面视域裁剪、球面视点控制等技术,使geometry clipmaps算法适用于球面海量地形数据的3维可视化;收集处理月球全球影像和形貌高程数据,对算法进行验证,实现月球表面形貌的实时动态3维可视化.试验表明:绘制算法可不受数据量大小的限制、绘制效率高、效果逼真,但存在两极变形较大的缺点.

Abstract：

Based on the study of visualization arithmetic of large area terrain, plane geometry clipmaps algorithm is improved. Projection transformation from plane landform to sphere landform was realized by using GPU vertex shader. In that improved algorithm, methods such as sphere vision field culling and sphere viewpoint control are used.That makes geometry clipmops algorithm more effective in 3D visualization of massive sphere terrain data. The whole moon image and DEM data are collected and disposed, which are used to verify the capability of that algorithm, realizing dynamic and real time 3D visualization of moon surface. The experiments show that the graphic algorithm isn't limited by data quantity, which is of high efficiency and reality simulation, but the two-pole distortion is serious.     

Regional hydrologic mapping of flows in stream networks

River low flow (LF) is an important hydrological characteristic used in management of the quantity and quality of water resources. A common way to transpose at-station low flow quantiles to ungaged locations involves development of regional multivariate regression models. In site selection studies of water control facilities, need arises to automate the mapping of LF characteristics onto the stream network in a continuous manner. This would allow estimation of LF at any desired ungaged location. A mapping algorithm is introduced that determines the value of regression model's independent variables (input components) over the drainage area of each stream pixel and calculates the flow (output). The mapping algorithm relies mainly on the digital elevation model (DEM) and its derivatives, such as flow direction and flow accumulation. Furthermore, the contribution of each independent variable of the regional model to the total flow may be plotted to represent the flow profiles along the streams. A case study involving LF mapping in rivers of Gilan province, Iran, where LF quantiles are required for issuing water withdrawal permits as well as maintaining water quality standards, is also described in the paper. Overall, the maps and profiles of flow statistics in the region of interest provide convenient visualization and assessment tools for water resource and environmental engineers. The transposition algorithm may also be applied in regional mapping of other flow characteristics such as flood or average flows.     

基于ArcGIS的洪水淹没分析模拟及可视化

基于数字高程模型(DEM)格网模型,通过改进迭代种子蔓延算法,实现给定水深情况下洪水淹没区的讣算模型,讨论洪水淹没演进过程可视化实现的关键技术,并使用ArcEngine开发包进行二次开发,以二维和二三维两种可视化方式,动态而形象地模拟在指定洪水水位下的洪水淹没演进过程.试验证明,所提出的实现方法切实有效,便于推广应用,为快速、准确及科学地进行洪灾评估洪水风险图的制作提供良好的基础,对洪涝灾害进行评估和预测分析具有重要意义.     

Accuracy assessment of digital elevation models by means of robust statistical methods

Measures for the accuracy assessment of Digital Elevation Models (DEMs) are discussed and characteristics of DEMs derived from laser scanning and automated photogrammetry are presented. Such DEMs are very dense and relatively accurate in open terrain. Built-up and wooded areas, however, need automated filtering and classification in order to generate terrain (bare earth) data when Digital Terrain Models (DTMs) have to be produced. Automated processing of the raw data is not always successful. Systematic errors and many outliers at both methods (laser scanning and digital photogrammetry) may therefore be present in the data sets. We discuss requirements for the reference data with respect to accuracy and propose robust statistical methods as accuracy measures. Their use is illustrated by application at four practical examples. It is concluded that measures such as median, normalized median absolute deviation, and sample quantiles should be used in the accuracy assessment of such DEMs. Furthermore, the question is discussed how large a sample size is needed in order to obtain sufficiently precise estimates of the new accuracy measures and relevant formulae are presented.     

面向应用的CBERS-02星高分辨率相机成像数值模拟技术框架

技术框架研究的目标是准确仿真卫星高分辨率相机成像过程中辐射和几何质量的下降情况,从应用方的角度建立评价高分辨率卫星相机在国土资源领域的应用潜力和技术框架,并以CBERS-02B星HR相机在轨成像模拟为例进行了原理验证,同时对今后以国土资源应用评价为目标的高分辨率相机在轨成像模拟改进方案提出了建议。