TM图像中道路目标识别方法的研究

提出了一种新的TM图像中道路目标的识别方法。算法充分利用了TM图像的特点,在底层处理中运用方向可调滤波器(SteerableFilter)的方法提取出潜在的道路目标;在中层处理中使用链码表示目标并提取其特征参数;最后在高层处理中进行道路识别和一些后处理,整个算法可以进行自动的识别。实验证明该算法对于TM图像中的道路识别是很有效的。     

机载LiDAR点云数据中电力线的提取方法研究

提出了一种基于机载LiDAR点云数据的电力线提取方法。首先在进行LiDAR数据滤波的基础上,分离地面点与非地面点;然后针对非地面点采取一种基于角度的滤波方法,分离非地面点中的植被点与电力线点,对电力线点,采用二维Hough变换进一步分离各条电力线点;最后使用双曲余弦函数模型,对单条电力线进行曲线拟合。实验结果表明,该方法能够从LiDAR点云数据中较完整地提取出电力线点,电力线点提取正确率达96.2%,并能够对电力线走廊进行三维重建。     

以数值产品为基础的省级分县温度预报方法

将国家气象中心Ｔ６３,Ｔ１０６和欧洲中心数值模式中温度预报场,湿度预报场,ｕ,ｖ分量预报分别插值到１０８个测站上,以此作为预报因子,运用ＰＰＭ,ＭＯＳ,ＫＦ（卡尔曼滤波法）等方法分别建立最低,最高气温预报方程,用以上预报方法所是的预报结果作为预报因子,进行二次滤波集成和全集成预报,并建立了“数值产品省级分县温度预报系统”的１９９７年６月～１１月将该预报系统投入业务运行,取得了良好的预报效果。     

1980-2011年阿勒泰市光热资源变化对春小麦发育期的影响

利用阿勒泰基准站1980-2011年观测资料,分析了阿勒泰市春小麦发育期和光热资源变化,及各发育期日期与≥0℃积温、日照时数的相关性研究。结果表明：全发育期天数的变化是呈减少趋势的,分蘖、乳熟期、全发育期天数均通过了（P＜0.01）显著性检验;全发育期的≥0℃积温和日照时数是呈线性减少趋势变化的,拔节、乳熟、成熟期的≥0℃积温与年份的相关系数通过了信度0.01的显著性检验;出苗、拔节、乳熟、成熟期和全发育期的日照时数与年份的相关系数通过了（P<0.01）的显著性检验。成熟期日期受成熟期间的日照时数的正相关影响(P＜0.05）,分蘖、乳熟期的日期受发育期间的≥0℃积温和日照时数的正相关影响（P＜0.01）。造成这些差异的主要原因可能是各年的气候条件不同,其次是各年份的栽培条件、田间管理( 如灌溉、施肥、病虫害防治)等非气象因子的不同所致,各年作物的生长及发育都是气象因子和非气象因子共同作用的结果。     

GRAPES全球三维变分同化系统--基本设计方案与理想试验

中国气象局数值预报研究中心开发了一个全球和区域统一框架的格点三维变分资料同化系统(GRAPES3D-Var).作者给出全球版本的方案设计,采用单点观测试验检验方案设计的合理性和正确性.全球方案选择流函数、速度势、非平衡高度和相对湿度作为分析求解的控制变量,用线性平衡方程作为质量场和风场的动力约束,通过预调方法解决背景误差协方差矩阵阶数过大和难以求逆的问题,其中垂直变换和物理变换以及观测算子设计等方面与区域方案相同,但预调的水平变换采用球谐函数谱滤波表示背景误差协方差的水平相关模型,避免了递归滤波在高纬和极区因相关尺度过大无法实施的问题.另外,设计了一个使极区插值和差分计算完全闭合的网格以及相应的算法,解决了极点分析问题.单点观测理想试验结果表明,GRAPES 3D-Var系统能够合理给出全球任何地区的分析.     

全球、中国及云南近百年气温变化的层次结构和突变特征

用文献［１］建立的自适应多分辨数据波滤器进行了全球、中国及云南近百年气温变化的层次结构和突变特征分析。结果表明：（１）全球近百年来的气温变化对于较大时间尺度的演化来说主要特征是变暖,并为３个层次：即１９１９年以前的偏冷期;１９２０－１９７８年偏暖期和１９７９年以后的更暖期。对应于这种较大时间尺度的层次演变,全球的气温变化表现出十分明显的突变特征,两上最明显增暖的突变点分别发生在１９２０年和１９７９     

常规资料获取中尺度信息的一种简便方案

基于Ｂａｒｎｅｓ滤波原理，利用低通滤场的连续性特征，设计了一种从观测资料中提取中尺度气象信息的简便方案。利用该方案，可独立地获得观测站网和规则网格点上的中尺度气象信息，为基层气象台站进行中分析提供了方便。该方案与过去方案相比，具有计算量小，速度快，程序设计简单，计算精度高等优点，尤其适合基层台站使用。     

Data assimilation in groundwater modelling: ensemble Kalman filter versus ensemble smoothers

Groundwater modelling calls for an effective and robust data integrating method to fill the gap between the model and observation data. The ensemble Kalman filter (EnKF), a real‐time data assimilation method, has been increasingly applied in multiple disciplines such as petroleum engineering and hydrogeology. In this approach, a groundwater model is updated sequentially with measured data such as hydraulic head and concentration. As an alternative to the EnKF, the ensemble smoother (ES) has been proposed for updating groundwater models using all the data together, with much less computational cost. To further improve the performance of the ES, an iterative ES has been proposed for continuously updating the model by assimilating measurements together. In this work, we compare the performance of the EnKF, the ES, and the iterative ES using a synthetic example in groundwater modelling. Hydraulic head data modelled on the basis of the reference conductivity field are used to inversely estimate conductivities at unsampled locations. Results are evaluated in terms of the characterization of conductivity and groundwater flow predictions. It is concluded that (a) the iterative ES works better than the standard ES because of its continuous updating and (b) the iterative ES could achieve results comparable with those of the EnKF, with less computational cost. These findings show that the iterative ES should be paid much more attention for data assimilation in groundwater modelling.     

Shape detection of multiple subsurface cavities by particle filtering with elastic wave propagation

A numerical technique for detecting the number and shape of subsurface cavities is presented, applying the particle filter and the parametric level set method to elastic wave propagation under the ground. When subsurface cavities exist, the elastic wave propagating in the ground is reflected at the boundary faces of the cavities. Observing the velocity of the reflection wave at the surface of a ground that includes multiple cavities and parameterizing the shape of the cavities by the parametric level function, both the number and the shape of the cavities can be identified by the particle filter. Numerical experimentation for detecting multiple cavities is conducted with synthetic observation data. The results show that the proposed technique enables the number of cavities to be identified by the number of peaks in the posterior probabilistic distribution function and solves geometric inverse problems by estimating the shape of the cavities through the parameter identification of the level set function.     

Sediment particle selectivity and its response to overland flow hydraulics within grass strips

Particle selectivity plays an important role in clarifying sediment transport processes in vegetative filter strips (VFS). 10-m long grass strips at slopes of 5° and 15° were subjected to a series of sediment-laden inflows experiments with different particle sizes to investigate the sediment transport and its response to overland flow hydraulics. The inflow sediments came from local soil, river-bed sand, and mixed, with median particle size d₅₀ of 39.9, 207.9 and 77.4 μm, respectively. Three independent repeated experiments were carried for each treatment. The results show that when the sediment trapping lasted for a certain length of time, the re-entrainment of some small-sized particles was greater than the deposition; that is, net loss occurred, which was not erosion of the original soil. Net loss of particles is mainly determined by the particle diameter. The coarser the inflow sediment particles and/or the steeper the slope, the coarser the particles can be net lost. Deposited sediment causes the VFS bed surface to become smooth and hydraulic resistance decrease exponentially. Unit stream power P is more suitable than shear stress τ of overland flow to be used to describe the process of sediment particle transport in VFS. The relationship between P and d₅₀ of outflow sediment is very consistent with the form of power function with a constant term. These results are helpful to understand the physical process of sediment transport on vegetation hillslopes.