GPS RTK技术及其在管线勘控中的应用

针对GPS RTK技术应用中的工作条件、数据链传输、误差特性及质量控制等问题,结合管线勘控测量的作业特点,提出了提高RTK作业精度若干方法.     

冬小麦夏玉米土壤水分预报及优化灌溉模型

利用土壤水分平衡方程，结合河南省冬小麦和夏玉米的生长规律和1994～2000年冬小麦、夏玉米田实测土壤湿度资料，建立了河南省冬小麦、夏玉米土壤水分预报及优化灌溉的计算机模型。用1998～1999年郑州市麦田实测土壤湿度资料验证该模型模拟结果，未来10、20、30天土壤湿度相对误差分别为-7．3％～7．7％、-8．3％～6．8％、-7．6％～7．7％，表明利用该模型，可以较为准确地预报未来1个月的土壤水分变化，并可根据小麦、玉米不同发育期特点，给出以最高产量和最佳经济效益为目标的灌溉建议。     

基于DSM阴影仿真和高度场光线跟踪的影像阴影检测

介绍了一个建筑物阴影检测的模型。首先利用摄影测量学原理来计算阴影坐标。即用数字表面模型(digitalsurfacemodel,缩写为DSM)和太阳高度和方位来计算建筑物阴影的空间坐标,并由相机模型计算出每个阴影单元对应的扫描行和相机空间坐标。由高度场光线跟踪判断阴影的可见性,对可见阴影计算出它在投影图像上的坐标。然后在这个结果的基础上再对图像进行阴影的细分割。     

基于地表定量参数的沙漠化遥感监测方法

利用野外沙漠化调查的定位数据和ETM+ 遥感数据，在实验分析的基础上，探讨了沙漠化程度与地表参数之间的定量关系，即沙漠化与植被指数（NDVI）、地表辐射温度（LST）之间的关系，提出了综合反映沙漠化土地生物物理特征的遥感监测指数——沙漠化遥感监测差值指数（DDI），为沙漠化遥感监测提供有效的定量化方法。     

Outlier detection algorithms and their performance in GOCE gravity field processing

The satellite missions CHAMP, GRACE, and GOCE mark the beginning of a new era in gravity field determination and modeling. They provide unique models of the global stationary gravity field and its variation in time. Due to inevitable measurement errors, sophisticated pre-processing steps have to be applied before further use of the satellite measurements. In the framework of the GOCE mission, this includes outlier detection, absolute calibration and validation of the SGG (satellite gravity gradiometry) measurements, and removal of temporal effects. In general, outliers are defined as observations that appear to be inconsistent with the remainder of the data set. One goal is to evaluate the effect of additive, innovative and bulk outliers on the estimates of the spherical harmonic coefficients. It can be shown that even a small number of undetected outliers (<0.2 of all data points) can have an adverse effect on the coefficient estimates. Consequently, concepts for the identification and removal of outliers have to be developed. Novel outlier detection algorithms are derived and statistical methods are presented that may be used for this purpose. The methods aim at high outlier identification rates as well as small failure rates. A combined algorithm, based on wavelets and a statistical method, shows best performance with an identification rate of about 99%. To further reduce the influence of undetected outliers, an outlier detection algorithm is implemented inside the gravity field solver (the Quick-Look Gravity Field Analysis tool was used). This results in spherical harmonic coefficient estimates that are of similar quality to those obtained without outliers in the input data.     

Development of a remotely sensed,historical land-cover change database for rural Chihuahua,Mexico

The purpose of this article is to describe the development of a remotely sensed, historical land-cover change database for the northwestern quarter of Chihuahua, Mexico, The database consists of multi-temporal land-cover classifications and change detection images. The database is developed to facilitate future investigations that examine urban–rural linkages as possible drivers of rural land-use and land-cover changes. To develop the needed land-cover change database, this study uses the North American Landsat Characterization (NALC) MSS triplicates because of their temporal depth and spatial breadth. Challenges exist, however, to effective classification and change detection using the NALC triplicates, including illumination differences across multiple scenes and periods caused by topographic and solar variations and the lack of ground reference data for historic periods. Therefore, creation of the database is a four step process. First, extensive pre-processing is performed to enhance comparability of multi-date images. Pre-processing includes topographic correction, mosaic creation and multi-date radiance normalization. Second, ancillary sources of land-cover data are combined with visual interpretations of enhanced images to define reference pixels used to classify the images using the maximum likelihood algorithm. Third, classification accuracy is assessed. Fourth, post-classification change detection is performed. Results indicate significant image improvements after pre-processing that permit very good overall classification (86.26% classified correctly) and change detection. To conclude, findings are presented that indicate significant changes to arid grasslands/shrublands and forest resources in mountainous regions.     

Particle size dependent response of aerosol counters

During an international workshop at the Institute for Experimental Physics of the University of Vienna, Austria, which was coordinated within the Committee on Nucleation and Atmospheric Aerosols (IAMAS-IUGG), 10 instruments for aerosol number concentration measurement were studied, covering a wide range of methods based on various different measuring principles. In order to investigate the detection limits of the instruments considered with respect to particle size, simultaneous number concentration measurements were performed for monodispersed aerosols with particle sizes ranging from 1.5 to 50 nm diameter and various compositions.The instruments considered show quite different response characteristics, apparently related to the different vapors used in the various counters to enlarge the particles to an optically detectable size. A strong dependence of the 50% cutoff diameter on the particle composition in correlation with the type of vapor used in the specific instrument was found. An enhanced detection efficiency for ultrafine hygroscopic sodium chloride aerosols was observed with water operated systems, an analogous trend was found for n-butanol operated systems with nonhygroscopic silver and tungsten oxide particles.     

Structural damage detection using the optimal weights of the approximating artificial neural networks

This work presents a novel neural network‐based approach to detect structural damage. The proposed approach comprises two steps. The first step, system identification, involves using neural system identification networks (NSINs) to identify the undamaged and damaged states of a structural system. The partial derivatives of the outputs with respect to the inputs of the NSIN, which identifies the system in a certain undamaged or damaged state, have a negligible variation with different system errors. This loosely defined unique property enables these partial derivatives to quantitatively indicate system damage from the model parameters. The second step, structural damage detection, involves using the neural damage detection network (NDDN) to detect the location and extent of the structural damage. The input to the NDDN is taken as the aforementioned partial derivatives of NSIN, and the output of the NDDN identifies the damage level for each member in the structure. Moreover, SDOF and MDOF examples are presented to demonstrate the feasibility of using the proposed method for damage detection of linear structures. Copyright © 2001 John Wiley & Sons, Ltd.     

A response‐based decoupling criterion for multiply‐supported secondary systems

It is often infeasible to carry out coupled analyses of multiply‐supported secondary systems for earthquake excitations. ‘Approximate’ decoupled analyses are then resorted to, unless the response errors due to those are significantly high. This study proposes a decoupling criterion to identify such cases where these errors are likely to be larger than an acceptable level. The proposed criterion is based on the errors in the primary system response due to decoupling and has been obtained by assuming (i) the input excitation to be an ideal white noise process, (ii) cross‐modal correlation to be negligible, and (iii) the combined system to be classically damped. It uses the modal properties of the undamped combined system, and therefore, a perturbation approach has been formulated to determine the combined system properties in case of light to moderately heavy secondary systems. A numerical study has been carried out to illustrate the accuracy achieved with the proposed perturbation formulation. The proposed decoupling criterion has been validated with the help of two example primary‐secondary systems and four example excitation processes. Copyright © 2002 John Wiley & Sons, Ltd.     

EFG法在土体固结中的应用

EFGM作为一种新的数值计算方法，具有只需节点信息而无段单元的特性，故在解固结方程方面有很大的优势。在计算分析中，此法容易构造固结方程的EFGM刚度矩阵和处理不同边界条件。对单面排水等条件的计算结果表明，EFGM在解决固结变形问题上，精度较高，处理边界准确。