祁连山中段青海云杉林土壤肥力质量评价研究

以祁连山排露沟流域青海云杉林为研究对象,研究了海拔梯度上土壤肥力因子的分布特征及变化规律,并运用主成分分析法对青海云杉林土壤肥力状况进行了评价。结果表明：（1）研究区土壤呈碱性,pH值均大于8.0;高海拔地区（3 300 m）含水量达到过饱和状态,各土层含水量均大于100%;随海拔升高,全氮含量呈增大趋势,全钾含量呈减小趋势,而全磷含量呈先减小后增大趋势;不同海拔梯度速效磷含量差异不显著（P>0.05）,海拔3 300 m处速效钾含量显著高于其他海拔段（P<0.05）。（2） 不同海拔梯度下土壤有机质、全氮、全磷、全钾、速效磷和速效钾含量都有明显的“表聚效应”,其中3 300 m处0~10 cm土层有机质含量高达325.93 g·kg^-1,是本海拔段其他土层的1.6~1.8倍,是同土层其他海拔段的1.3~2.0倍。（3） 土壤肥力因子间关系密切,土壤含水量与有机质、全氮呈极显著正相关关系,与土壤容重、pH和全钾呈极显著负相关关系,土壤养分含量之间存在不同程度的显著正相关关系。（4） 不同海拔梯度土壤肥力质量为：3 300 m>3 200 m>3 100 m>3 000 m>2 900 m。     

施肥对新垦绿洲风沙土肥力及碳积累的影响

利用2005年安排在临泽边缘绿洲沙地农田的长期施肥定位试验,研究不同用量有机肥、化肥、有机肥和化肥配施对绿洲沙地土壤肥力及有机碳积累的影响。试验包括高量有机肥单施(M3),氮磷化肥单施(NP3),低、中、高量氮磷钾化肥单施(NPK1,NPK2,NPK3),及低、中、高量氮磷钾化肥配施高、中、低量有机肥9个处理(NPK1M3,NPK2M2,NPK3M1),测定分析10年后不同施肥处理耕层(0~20 cm)土壤物理化学性状特征及有机碳动态。结果表明:施有机肥及有机无机配施处理较单施化肥处理容重下降0.13 g·cm^-3,田间持水量提高6.7%,单施有机肥、有机无机配施较单施化肥,土壤有机碳(SOC)和全氮含量分别提高64.8%、36.3%和64.9%、49.5%。高量施用氮磷化肥和氮磷钾化肥处理全磷含量最高,有机肥及有机无机配施较单施化肥有效氮含量显著增加,有机无机配施及高量施用磷肥土壤有效磷积累明显,高量施用有机肥能显著提升有效钾含量。连续施肥处理10年后,SOC含量提高了1.68~2.84倍,土壤全氮、全磷、碱解氮及有效磷均有一定程度的提高,但单施化肥及有机肥与氮磷化肥配施有效钾含量下降。SOC的积累速率单施化肥、有机无机配施、单施有机肥处理分别为0.27、0.59,0.87 g·kg^-1·a^-1。增施有机肥、适量减少化肥投入、氮磷钾化肥的平衡施用是绿洲沙地农田土壤肥力持续提升的施肥管理对策。     

基于动态极坐标参数化的遥感影像匹配方法

图像匹配作为三维重建至关重要的环节,其精度直接影响了平差优化、正射校正等模块的精度。对于城镇、农场等特征密集型区域,特征距离小,相似性强,易于匹配图像;而针对草地、沙漠等特征不明显区域,特征距离大,如果使用特征点匹配的方法,严格阈值下难以获得足够数量的匹配对,放宽阈值又将引入较多误匹配对,这也是导致稀疏点云不够均匀的原因之一。在此场景下,本文提出了基于动态极坐标参数化的无人机正视影像匹配算法,首先对图像做极坐标参数变化,采用动态策略解决极轴方向采样不均匀的问题,使用最小二乘法对得到的极坐标影像对做位移方向上的匹配,匹配后得到的旋转量和平移量,将该结果和SIFT算法的结果做比较。本文设计了2组实验,即参数已知的解算实验和参数未知的解算实验,且每组实验进行3次。在同等配置的计算机上,对两张7360像素×5400像素,32位的影像,本文方法的位姿解算时间相比SIFT的时间减少约57%,二者求得的位姿差通常小于1%。结论表明二者的结果在精度上表现相当,在时间上明显优于SIFT算法,具有实际的应用价值。     

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冀鲁豫地区重力场变化与封丘ML4.8地震关系的探讨

利用冀鲁豫测网的流动重力5期观测成果,探讨了重力场变化与封丘地震的关系。研究发现：冀鲁豫交界地区的重力点值在封丘地震前后出现了下降-上升-下降的变化过程,较好地对应了封丘ML4.8地震孕育 发震 震后调整的过程。该重力变化可能是封丘地震的异常反映。     

基于条件平差的卫星双向时间传递链路性能优化方法

卫星双向时间传递(Two-Way Satellite Time and Frequency Transfer, TWSTFT)是目前精度最高的时间传递方法之一,同时也是参与国际原子时计算的守时实验室之间比较原子时尺度的一种主要方法.提高TWSTFT链路的短期稳定度,降低周日效应对链路时间传递结果的影响,对优化TAI (International Atomic Time)的性能具有现实意义.提出了一种基于条件平差的TWSTFT链路性能优化方法,先依据TWSTFT链路测量噪声水平与谱分析结果建立TWSTFT链路性能优化网络(简称优化网络),再根据优化网络中各链路测量噪声分析结果设置权系数阵,建立条件平差模型.选取亚太地区的中国计量科学研究院(National Institute of Metrology, NIM)-中国科学院国家授时中心(National Time Service Center, NTSC)卫星双向时间传递链路作为待优化链路,以NTSC、NIM以及德国联邦物理技术研究所(Physikalisch-Technische Bundesanstalt,PTB)之间的TWSTFT链路组成优化网络,对优化网络的组网方法和条件平差模型进行实验验证.结果表明,平差后待优化链路短期稳定度得到了改善,同时其受周日效应的影响降低了约24.6%.使用该方法,能够有效提高待优化链路的时间传递性能.     

附有限制条件的间接平差秩亏时解法初探

在附有限制条件的间接平差的应用中,若所列观测方程中实际用到的未知参数的个数少于所选参数的总数u时,就会出现法方程系数阵秩亏的问题。为了解决此问题,在理论公式推导的基础上,给出了一种新的解决方法,并结合算例进行了验证。     

A strip adjustment procedure to mitigate the impact of inaccurate mounting parameters in parallel lidar strips

Lidar (laser scanning) technology has been proven as a prominent technique for the acquisition of high-density and accurate topographic information. Because of systematic errors in the lidar measurements (drifts in the position and orientation information and biases in the mirror angles and ranges) and/or in the parameters relating the system components (mounting parameters), adjacent lidar strips may exhibit discrepancies. Although position and orientation drifts can have a more significant impact, these errors and their impact do not come as a surprise if the quality of the GPS/INS integration process is carefully examined. Therefore, the mounting errors are singled out in this work. The ideal solution for improving the compatibility of neighbouring strips in the presence of errors in the mounting parameters is the implementation of a rigorous calibration procedure. However, such a calibration requires the original observations, which may not be usually available. In this paper, a strip adjustment procedure to improve the compatibility between parallel lidar strips with moderate flight dynamics (for example, acquired by a fixed-wing aircraft) over an area with moderately varying elevation is proposed. The proposed method is similar to the photogrammetric block adjustment of independent models. Instead of point features, planar patches and linear features, which are represented by sets of non-conjugate points, are used for the strip adjustment. The feasibility and the performance of the proposed procedure together with its impact on subsequent activities are illustrated using experimental results from real data.     

Estimation of parameters in a split functional model of geodetic observations (<Emphasis Type="Italic">M</Emphasis><Subscript>split</Subscript> estimation)

The paper presents a method of estimating parameters in two competitive functional models. The models considered here are concerned with the same observation set and are based on the assumption that an observation may result from a realization of either of two different random variables. These variables differ from one another at least in the main characteristic (for example, outliers can be realizations of one variable). A quantity that describes the opportunity of identifying a single observation with one random variable is assumed to be known. That quantity, called the elementary split potential, is strictly referred to the amount of information that an observation can provide about two competitive assumptions concerning the observation distribution. Parameter assessments that maximize the global elementary split potential (concerning all observations), are called M _split estimators. A generalization of M _split estimation presented in the paper refers to the theoretical foundation of M-estimation. An erratum to this article can be found at     

Singular value decomposition and cluster analysis as regression diagnostics tools for geodetic applications

It is well known that high-leverage observations significantly affect the estimation of parameters. In geodetic literature, mainly redundancy numbers are used for the detection of single high-leverage observations or of single redundant observations. In this paper a further objective method for the detection of groups of important and less important (and thus redundant) observations is developed. In addition, the parameters which are predominantly affected by these groups of observations are identified. This method thus complements other diagnostics tools, such as, e.g., multiple row diagnostics methods as described in statistical literature (see, e.g., Belsley et al. in Regression diagnostics: identifying influential data and sources of collinearity. Wiley, New York, 1980). The method proposed in this paper is based on geometric aspects of adjustment theory and uses the singular value decomposition of the design matrix of an adjustment problem together with cluster analysis methods for regression diagnostics. It can be applied to any geodetic adjustment problem and can be used for the detection of (groups of) observations that significantly affect the estimated parameters or that are of negligible impact. One of the advantages of the proposed method is the improvement of the reliability of observation plans and thus the reduction of the impact of individual observations (and outliers) on the estimated parameters. This is of particular importance for the very long baseline interferometry technique which serves as an application example of the regression diagnostics tool.