Archival photogrammetric analysis of river–floodplain systems using Structure from Motion (SfM) methods

In this study we evaluate the extent to which accurate topographic data can be obtained by applying Structure from Motion (SfM) photogrammetric methods to archival imagery. While SfM has proven valuable in photogrammetric applications using specially acquired imagery (e.g. from unmanned aerial vehicles), it also has the potential to improve the precision of topographic data and the ease with which can be produced from historical imagery. We evaluate the application of SfM to a relatively extreme case, one of low relative relief: a braided river–floodplain system. We compared the bundle adjustments of SfM and classical photogrammetric methods, applied to eight dates. The SfM approach resulted in data quality similar to the classical approach, although the lens parameter values (e.g. focal length) recovered in the SfM process were not necessarily the same as their calibrated equivalents. Analysis showed that image texture and image overlap/configuration were critical drivers in the tie‐point generation which impacted bundle adjustment quality. Working with archival imagery also illustrated the general need for the thorough understanding and careful application of (commercial) SfM software packages. As with classical methods, the propagation of (random) error in the estimation of lens and exterior orientation parameters using SfM methods may lead to inherent systematic error in the derived point clouds. We have shown that linear errors may be accounted for by point cloud registration based on a reference dataset, which is vital for the further application in quantitative morphological analyses when using archival imagery. Copyright © 2016 John Wiley & Sons, Ltd.     

Event and model dependent rainfall adjustments to improve discharge predictions

Most conceptual rainfall–runoff models use as input spatially averaged rainfall fields which are typically associated with significant errors that affect the model outcome. In this study, it was hypothesised that a simple spatially and temporally averaged event-dependent rainfall multiplier can account for errors in the rainfall input. The potentials and limitations of this lumped multiplier approach were explored by evaluating the effects of multipliers on the accuracy and precision of the predictive distributions. Parameter sets found to be behavioural across a range of different flood events were assumed to be a good representation of the catchment dynamics and were used to identify rainfall multipliers for each of the individual events. An effect of the parameter sets on identified multipliers was found; however, it was small compared to the differences between events. Accounting for event-dependent multipliers improved the reliability of the predictions. At the cost of a small decrease in precision, the distribution of identified multipliers for past events can be used to account for possible rainfall errors when predicting future events. By using behavioural parameter sets to identify rainfall multipliers, the method offers a simple and computationally efficient way to address rainfall errors in hydrological modelling.     

一种卫星钟差精度评估方法

GNSS观测量测量的是测站与卫星间的相对时间延迟,卫星钟差求解的是相对于基准钟的相对钟差,因此卫星钟差的精度评估方法不同于其他GNSS产品。分析了卫星钟差的精度评估方法,采用消除卫星钟系统偏差的方法进行钟差精度的评估,得到的各产品的精度评定结果与各产品公布的钟差精度基本一致,证明了此方法的有效性。     

An optimized use of limited ground based topographic data for river applications

A prime requirement for hydrological applications,such as sediment budgeting or numerical modelling,is that produced Digital Terrain Models(DTMs)accurately represent the shape of landforms,especially for river reaches where data are not homogeneous.DTM error is a function of data point measurement accuracy and density and also of the field survey strategy when limited amounts of data will be acquired.This paper aims to advance the importance of the field survey strategy for the specific,but common cases,where only limited topographic data will be available.This methodology is based on the idea that any feature can be properly described by a set of cross sections and breaklines describing both main and secondary directions of the flow.Then,a longitudinal linear interpolation can be applied to the defined homogeneous zones.This morphologically oriented(MO)method that includes data acquisition strategy and interpolation,was validated using a reference DTM derived from LiDAR measurements.An estimation of the uncertainties also is suggested based on the distance of the nearest point and the local slope using a geographically weighted regression.The proposed MO method is typically applicable to Alpine river reaches characterized by multiple channels that may always be underwater and not navigable such as an alternate bar system with secondary and transverse channels.     

SS-Y型伸缩仪观测问题分析及优化方法探讨

SS-Y型伸缩仪在我国地震洞体形变监测台网中已安装使用多年。对地球固体潮观测而言,仪器观测资料精度高且长期稳定性较好,但从地震预测的观测需求来看,SS-Y型伸缩仪仍然存在很多不足,如高频信息缺失、抗干扰能力较弱、存在格值误差、自校验能力较差等。对伸缩仪存在的问题进行分析,并提出一种超宽频带短基线伸缩仪的设计思路,以期为后续新仪器的研制提供理论依据。     

Using model error in response history analysis to evaluate component calibration methods

This research is part of a larger effort to better understand and quantify the epistemic model uncertainty in dynamic response-history simulations. This paper focuses on how calibration methods influence model uncertainty. Structural models in earthquake engineering are typically built up from independently calibrated component models. During component calibration, engineers often use experimental component response under quasi-static loading to find parameters that minimize the error in structural response under dynamic loading. Since the calibration and the simulation environments are different, if a calibration method wants to provide optimal parameters for simulation, it has to focus on features of the component response that are important from the perspective of global structural behavior. Relevance describes how efficiently a calibration method can focus on such important features. A framework of virtual experiments and a methodology is proposed to evaluate the influence of calibration relevance on model error in simulations. The evaluation is demonstrated through a case study with buckling-restrained braced frames (BRBF). Two calibration methods are compared in the case study. The first, highly relevant calibration method is based on stiffness and hardening characteristics of braces; the second, less relevant calibration method is based on the axial force response of braces. The highly relevant calibration method consistently identified the preferable parameter sets. In contrast, the less relevant calibration method showed poor to mediocre performance. The framework and methodology presented here are not limited to BRBF. They have the potential to facilitate and systematize the improvement of component-model calibration methods for any structural system.     

射电天线指向改正模型中轴系误差的完全表达式

为了提高射电天线的目标跟踪精度,采用直接法推导了射电天线轴系误差对指向的影响,并给出轴系误差指向改正模型的完全表达式,明确了指向改正模型中各轴系参数的定义,传统分项以及球谐函数所推导的轴系误差项为该模型的简化形式.基于此,评估得出基本参数改正模型中,因忽略轴系误差高次谐项而引起的指向精度损失可能达到1′′量级,具体需结合轴系误差大小而定;同时明确了基本参数改正模型(如22项指向模型)中与轴系误差有关的部分高次谐项系数的物理意义.为高精度轴系误差指向改正模型的建立提供了理论依据.     

Correction Method of Antenna Pointing Error Caused by the Main Reflector Deformation

The pointing accuracy of a radio telescope is usually less than one-tenth of its antenna beam width. For large-aperture antennas at the short-centimeter band or millimeter-wave band, the pointing accuracy must be as high as several arc seconds. Therefore, for large-diameter and high-frequency reflector antennas, the pointing problem has become an important focal point to realize the antenna performance. Among many structural subsystem factors that affect the antenna pointing accuracy, there has been only less study on the factor of main reflector deformation. Based on the structural characteristics of the antenna, a reflector space coordinate system is established in this paper. And based on the space coordinates of the main reflector surface points after deformation, a non-linear least squares fitting method with 3 degrees of freedom is proposed to accurately predict the antenna pointing. Finally, the space geometric relationship is used to strictly derive the precise adjustments on the elevation and azimuth in order for correcting the antenna pointing error, and the indirect relationship between the main reflector deformation and the pointing error is constructed. This has certain guiding significance for improving the pointing accuracy of large radio antennas.     

银川地震台CTS-1数字地震仪震级校正初探

主要分析讨论了2002年1月~2005年2月银川台数字地震仪测定的震级与中国数字地震台网观测报告震级的误差,给出银川台CTS-1数字地震仪震级的校正值,以提高银川台地震速报的精度。同时初步探讨分析了银川台数字地震仪震级误差的原因。     

Evaluation of Arctic Sea-ice Cover and Thickness Simulated by MITgcm

A regional Arctic Ocean configuration of the Massachusetts Institute of Technology General Circulation Model(MITgcm)is applied to simulate the Arctic sea ice from 1991 to 2012.The simulations are evaluated by comparing them with observations from different sources.The results show that MITgcm can reproduce the interannual and seasonal variability of the sea-ice extent,but underestimates the trend in sea-ice extent,especially in September.The ice concentration and thickness distributions are comparable to those from the observations,with most deviations within the observational uncertainties and less than 0.5 m,respectively.The simulated sea-ice extents are better correlated with observations in September,with a correlation coefficient of 0.95,than in March,with a correlation coefficient of 0.83.However,the distributions of sea-ice concentration are better simulated in March,with higher pattern correlation coefficients(0.98)than in September.When the model underestimates the atmospheric influence on the sea-ice evolution in March,deviations in the sea-ice concentration arise at the ice edges and are higher than those in September.In contrast,when the model underestimates the oceanic boundaries’influence on the September sea-ice evolution,disagreements in the distribution of the sea-ice concentration and its trend are found over most marginal seas in the Arctic Ocean.The uncertainties of the model,whereby it fails to incorporate the atmospheric information in March and oceanic information in September,contribute to varying model errors with the seasons.