The Influence of Transient Flow Distortion on Turbulence in Stable Weak-Wind Conditions

Transport by very weak turbulence near the surface, particularly with strong stratification, often violates existing similarity theory due partly to transient distortion of the wind profile by nonstationary mesoscale motions. This problem is examined with 4 months of flux data at seven levels on a 30-m tower. Difficulties with calculation of fluxes and shear with weak winds and weak turbulence are examined. The distortion of the wind profile assumes a wide variety of forms, but sometimes occurs with a transient wind maximum in the lowest 10 m. Though the vertical mixing of momentum is weak for weak-wind nonstationary conditions, it is often more efficient than predicted by existing similarity theory. In fact for weak-wind stable conditions, the flux-gradient relationship depends more on the curvature of the wind profile than the value of the stability parameter. This statistical study suggests a new direction for future work, but does not unravel the physics of the complex and varied structure for stratified weak-wind conditions.     

形势场相似计算方案的比较研究

结合天气分析方法,对常用的形势场相似算法效果进行了对比分析,结果表明:"相关系数"是较好的"形"相似判据;对经向和纬向分别计算相似度可以发掘出更多有预报参考价值的信息;另外,对相似计算方案的边界条件及执行效率等问题也作了探讨.     

Local Similarity in the Stable Boundary Layer and Mixing-Length Approaches: Consistency of Concepts

In stably stratified flows vertical movement of eddies is limited by the fact that kinetic energy is converted into potential energy, leading to a buoyancy displacement scale z _B . Our new mixing-length concept for turbulent transport in the stable boundary layer follows a rigid-wall analogy, in the sense that we assume that the buoyancy length scale is similar to neutral length scaling. This implies that the buoyancy length scale is: ℓ _B  = κ _B z _B , with κ _B ≈ κ, the von Karman constant. With this concept it is shown that the physical relevance of the local scaling parameter z/Λ naturally appears, and that the α coefficient of the log-linear similarity functions is equal to c/κ ², where c is a constant close to unity. The predicted value α ≈ 1/κ ² = 6.25 lies within the range found in observational studies. Finally, it is shown that the traditionally used inverse linear interpolation between the mixing length in the neutral and buoyancy limits is inconsistent with the classical log-linear stability functions. As an alternative, a log-linear consistent interpolation method is proposed.     

基于理想分形规则扩展的地图曲线模拟方法研究

针对地图目标中许多线状要素具有典型统计分形特征的性质,探讨了在理想分形规则基础上通过增加随机因子,从而根据分维数反过来模拟构建地图曲线的方法.     

基于语义匹配和QoS的Web服务混合选择方法

提出了一种Web服务语义匹配方法,在此基础上分析了基于语义匹配和基于QoS(服务质量)的服务选择策略,以及面向独立服务和组合服务的服务选择方法,并给出了结合语义匹配和QoS指标值的Web服务混合选择策略及算法。实例分析结果表明,该混合选择策略能针对不同的服务需求作相应的处理,增加了服务选择的正确性,提高了服务组合效率。     

基于本体的异构空间数据的集成研究

在综合国内外地理信息学术界有关本体理论、方法和应用研究的基础上,改进了基于本体的空间数据集成框架,并进行了试验说明。     

融合可变形卷积与条件随机场的遥感影像语义分割方法

当前,深度卷积神经网络在遥感影像语义分割领域取得了长足的发展.标准的卷积神经网络由于卷积核的几何形状是固定的,导致对几何变换的模拟能力受到限制.本文引入一种可变形卷积来增强卷积网络对空间变换的适应能力.由于神经网络架构中使用了池化层操作,这会导致在输出层未能充分地对局部对象进行准确的分割.为了克服这种特性,本文将神经网络输出层的粗糙预测分割结果通过全连接的条件随机场来进行处理,以此来提高对影像细节的分割能力.本文方法易于采用标准的反向传播算法进行端到端的方式训练.ISPRS数据集上的测试试验结果表明本文方法可以有效地克服遥感影像中分割对象的复杂结构对分割结果的影响,并在该数据集上获得了当前最好的语义分割结果.     

基于语义的倾斜影像单体建模技术研究

针对应用倾斜航空影像进行自动化建模所创建的建筑物建模存在诸如模型细节缺失,难以获取语义信息的问题,该文提出了一种采用基于语义的建模方式构建建筑物模型的方法;首先对密集图像匹配(DIM)点云进行建筑物类提取,实现场景中建筑和其它地物的分离;然后进行基于点云分割和建筑物验证的建筑物单体标注,以保证对单体建筑物的有效标记;最后利用倾斜航空影像和DIM点云的建筑物各组件的语义识别和提取算法,实现以单体建筑物为建模对象的模型重建;同时,设计适用于建筑物重建的语义建模框架,对单体语义模型进行自动化纹理映射,构建出语义化的建筑物模型。该文提出的建模关键技术方法将有助于减少城市建模成本,提高建模效率,为智慧城市基础数据的建设提供关键技术储备,并发挥相应的的社会和经济效益。