抗差估计的多波束测深数据内插方法

针对传统多波束测深数据网格化内插方法抗差性不足的问题,该文将抗差估计理论应用于网格化内插方法中。基于不确定度指标建立了距离不确定度联合加权内插模型,在该模型的权函数中引入了等价权,同时给出了等价权设计方案及迭代初值确定原则,以增强模型的抗差性;介绍了一种节点邻域参考点合理选取方法,给出了改进内插法实现的基本步骤,最后通过实测数据对反距离加权法、联合加权法及改进方法内插水深质量进行比较。结果表明,改进方法内插结果要优于另外两种方法,可应用于多波束测深数据网格化处理中。     

Estimating attendance from cellular network data

An automatic estimate of the number of attendees to events happening in the city can provide valuable information to geographic information systems and geo-located applications. We present a methodology to estimate the number of events’ attendees from cellular network data. In this work, we used anonymized Call Detail Records (CDRs) comprising data on where and when users access the cellular network. Our approach is based on two key ideas: (1) we identify the network cells associated with the event location. (2) We verify the attendance of each user, as a measure of whether (s)he generates CDRs during the event, but not during other times. We evaluate our approach to estimate the number of attendees to a number of events ranging from football matches in stadiums to concerts and festivals in open squares. Comparing our results with the best groundtruth data available, our estimates provide a median error of less than 15% of the actual number of attendees.     

Bias estimation and correction for triangle-based surface area calculations

The calculation of surface area is meaningful for a variety of space-filling phenomena, e.g., the packing of plants or animals within an area of land. With Digital Elevation Model (DEM) data we can calculate the surface area by using a continuous surface model, such as by the Triangulated Irregular Network (TIN). However, just as the triangle-based surface area discussed in this paper, the surface area is generally biased because it is a nonlinear mapping about the DEM data which contain measurement errors. To reduce the bias in the surface area, we propose a second-order bias correction by applying nonlinear error propagation to the triangle-based surface area. This process reveals that the random errors in the DEM data result in a bias in the triangle-based surface area while the systematic errors in the DEM data can be reduced by using the height differences. The bias is theoretically given by a probability integral which can be approximated by numerical approaches including the numerical integral and the Monte Carlo method; but these approaches need a theoretical distribution assumption about the DEM measurement errors, and have a very high computational cost. In most cases, we only have variance information on the measurement errors; thus, a bias estimation based on nonlinear error propagation is proposed. Based on the second-order bias estimation proposed, the variance of the surface area can be improved immediately by removing the bias from the original variance estimation. The main results are verified by the Monte Carlo method and by the numerical integral. They show that an unbiased surface area can be obtained by removing the proposed bias estimation from the triangle-based surface area originally calculated from the DEM data.     

Dasymetric Spatiotemporal Interpolation

This research applies the principles of dasymetric mapping to spatiotemporal interpolation by extending the spatial concepts of zone and area to their temporal analogs of interval and duration, respectively. An example application of dasymetric spatiotemporal interpolation using crime event data is presented. Results indicate that dasymetric spatiotemporal interpolation significantly improves the accuracy of estimates over areal or duration weighting. In addition, even when dasymetric interpolation in either the spatial or temporal dimension is relatively weak, combining dasymetric estimation in both space and time dimensions simultaneously has the potential to amplify the accuracy of the overall dasymetric estimation.     

Application of Linear Mean-Square Estimation in Ocean Engineering

The attempt to obtain long-term observed data around some sea areas we concern is usually very hard or even impossible in practical offshore and ocean engineering situations. In this paper, by means of linear mean-square estimation method, a new way to extend short-term data to long-term ones is developed. The long-term data about concerning sea areas can be constructed via a series of long-term data obtained from neighbor oceanographic stations, through relevance analysis of different data series. It is effective to cover the insufficiency of time series prediction method’s overdependence upon the length of data series, as well as the limitation of variable numbers adopted in multiple linear regression model. The storm surge data collected from three oceanographic stations located in Shandong Peninsula are taken as examples to analyze the number-selection effect of reference oceanographic stations (adjacent to the concerning sea area) and the correlation coefficients between sea sites which are selected for reference and for engineering projects construction respectively. By comparing the N-year return-period values which are calculated from observed raw data and processed data which are extended from finite data series by means of the linear mean-square estimation method, one can draw a conclusion that this method can give considerably good estimation in practical ocean engineering, in spite of different extreme value distributions about raw and processed data.     

Investigation of gas content of organic-rich shale:A case study from Lower Permian shale in southern North China Basin,central China

Measuring gas content is an essential step in estimating the commerciality of gas reserves. In this study,eight shale core samples from the Mouye-1 well were measured using a homemade patented gas desorption apparatus to determine their gas contents. Due to the air contamination that is introduced into the desorption canister, a mathematical method was devised to correct the gas quantity and quality.Compared to the chemical compositions of desorbed gas, the chemical compositions of residual gas are somewhat different. In residual gas, carbon dioxide and nitrogen record a slight increase, and propane is first observed. This phenomenon may be related to the exposure time during the transportation of shale samples from the drilling site to the laboratory, as well as the differences in the mass, size and adsorptivity of different gas molecules. In addition to a series of conventional methods, including the USBM direct method and the Amoco Curve Fit(ACF) method, which were used here for lost gas content estimation, a Modified Curve Fit(MCF) method, based on the 'bidisperse' diffusion model, was established to estimate lost gas content. By fitting the ACF and MCF models to gas desorption data, we determined that the MCF method could reasonably describe the gas desorption data over the entire time period, whereas the ACF method failed. The failure of the ACF method to describe the gas desorption process may be related to its restrictive assumption of a single pore size within shale samples. In comparison to the indirect method, this study demonstrates that none of the three methods studied in this investigation(USBM, ACF and MCF) could individually estimate the lost gas contents of all shale samples and that the proportion of free gas relative to total gas has a significant effect on the estimation accuracy of the selected method. When the ratio of free gas to total gas is lower than 45%, the USBM method is the best for estimating the lost gas content, whereas when the ratio ranges from 45% to 75% or is more than 75%, the ACF and MCF methods, are the best options respectively.     

融雪洪水跳跃变异对其参数估计不确定性影响分析

利用Pettitt非参数检验法和Mann-Kendall非参数趋势检验法,分析年最大洪峰流量序列的非一致性,确定序列的变异形式,采用“分解-合成”理论对其进行一致性修正,得到过去、现状两种条件下年最大洪峰流量序列,根据贝叶斯理论对序列一致性修正前后参数不确定性进行估计,并对其预报区间优良性进行评价。研究结果表明：年最大洪峰流量序列变异点发生在1993年,序列整体上升趋势不显著,在1957-1993年子序列呈显著下降趋势,而1994-2006年子序列变化趋势不显著,跳跃变异为序列主要变异形式;给出了实测、还原及还现序列参数后验分布估计值及95%置信区间,将其结合优化适线法进行P-Ⅲ型频率分析,得到修正前后设计频率年最大洪峰流量预报区间估计值;还原、还现序列与实测序列相比,预报区间覆盖率均提高24%,平均带宽分别减少39.59%、23.17%,平均偏移幅度分别减少28.45%、11.39%。通过对非一致性年最大洪峰流量序列还原/还现计算,可减小参数估计不确定性对其计算产生的影响,从而提高预报区间的可靠性。     

开敞式潮滩-潮沟系统发育演变动力机制——Ⅲ.海平面上升影响

为研究海平面上升对潮滩-潮沟系统的影响,以江苏中部粉砂淤泥质海岸为原型,建立变态物理模型,模拟研究在不同海平面潮汐过程作用下的潮沟发育和演变过程,分析了潮滩淹没历时、排水密度、潮沟断面形态等特征参数变化规律。研究表明:潮沟在发育初期伸长速率高于拓宽速率,最终趋于动态平衡;海平面上升后,潮滩淹没历时增加,露滩时间缩短,归槽水对潮沟底床的塑造作用减弱;平均归槽水流长度和Horton排水长度均随海平面上升呈现出减小趋势,潮沟的排水能力增强;潮沟断面宽深比服从对数正态分布,随着海平面上升,潮沟断面面积和宽深比均呈现出增大趋势,宽深比分布范围变广。     

Satellite estimates and subpixel variability of rainfall in a semi-arid grassland

卫星估雨精度的不确定性受到当地降雨类型和像元内降雨非均匀性影响,而结合这两个关键因素开展半干旱草原卫星估雨的研究有限.2009年夏,我们在中国锡林郭勒半干旱草原用多部微雨雷达和雨量计构建了9 km卫星像元降雨观测网,观测了像元内降雨非均匀性(空间变异系数CV),并评估了卫星估雨精度.结果表明:(1)CV值受像元内平均降雨量,降雨类型,降雨云面积及移向等影响,如高Cv值的降雨过程大多为平均降雨量小,对流性降雨过程,降雨云边缘像元CV值较高;(2)TRMM 3B42V7卫星估雨产品适用性较好,CMORPH和PERSIANN次之,但TRMM 3B42V7易在半干旱草原湖泊处高估降雨.     

花岗岩风化料弃土快速堆填过程中不排水抗剪强度评估

沿海沿江城市地下开挖产生的工程渣土含泥量大、含水率高且较松散,主要运往渣土场进行堆填处置。由于产量巨大而处置场地有限,许多渣土场在运营过程中存在堆填速度快、缺乏排水设施、超高超库容堆填等问题,容易引发堆填体失稳事故。目前对于非饱和工程渣土堆体在快速堆填过程中的失稳机制认识尚不清晰,尤其是对这一过程中的高饱和度工程渣土强度增长规律缺乏足够的认识。以深圳红坳渣土场填料——花岗岩风化料(CDG)填土为研究对象,对不同初始饱和度土样进行三轴不排水不排气等向压缩和剪切试验,结果表明:非饱和CDG填土不排水抗剪强度随围压增大呈非线性增长,增长速率与试样初始饱和度密切相关;当土样压缩后的饱和度超过0.7,不排水强度随围压的增长速率显著降低。基于有效固结应力法的原理,结合Hilf孔压公式和修正剑桥模型,提出了一种工程渣土不排水抗剪强度估算方法,并通过与试验结果对比验证了该方法对初始饱和度高于0.6的CDG填土的适用性。利用该方法确定的不排水强度cu与正应力σn的关系可应用于高饱和度工程渣土快速堆填中的稳定性分析。