基于SMOS卫星数据的海表面盐度模型

海表面盐度是研究海洋对全球气候影响以及大洋环流的重要参量之一,而卫星遥感技术是获取海表面盐度数据的最有效方法.目前,L波段的SMOS和Aquarius/SAC-D遥感卫星正在用于探测海表面盐度,并根据卫星观测数据和物理机制反演出海表面盐度的产品.但在某些近陆地区域,由于淡水流入及陆地射频(RFI)等因素影响,卫星反演盐度的产品精度较低.文中利用“东方红2号”科学考察船的实测数据、SMOS卫星数据,首次针对中国南海海域提出了用贝叶斯网络模型计算海表面盐度,并用验证数据集(实测Argo盐度)对模型进行适应性评估.经过计算,模型误差和验证误差分别为0.47 psu和0.45 psu,而相应的SMOS Level 2产品的精度分别为1.90 psu和1.82 psu.此模型为海表面盐度的计算提供了一个新方法.     

Nonparametric Estimation of Undrained Shear Strength for Normally Consolidated Clays

For decades, various well-known empirical correlations have been established and commonly used to estimate the undrained shear strength of normally consolidated clays in geotechnical practice. However, there are still many contradictory cases regarding the validity of these correlations, so their applicability and reliability are questionable. In this study, an extensive geotechnical database for normally consolidated clays has been compiled. Next, a Bayesian nonparametric method is exploited to identify the most critical soil index properties in inferring the undrained shear strength and a new predictive model is proposed. Finally, the performance of the proposed predictive model is assessed and compared with two well-known correlations using an independent testing database. It confirms that the proposed model not only possesses high predictability, but also provides superior performance over other existing empirical correlations.     

Probabilistic calibration of a coupled hydro-mechanical slope stability model with integration of multiple observations

Multiple types of responses, such as displacements, ground water level, pore water pressures, water contents, etc., are usually measured in comprehensive monitoring programmes for rainfall-induced landslide prevention. In this study, a probabilistic calibration method for coupled hydro-mechanical modelling of slope stability is presented with integration of multiple types of measurements. A numerical example of a soil slope under rainfall infiltration is illustrated to compare the effects of single and multiple types of responses on parameter estimation and model calibration. The results show that the soil parameters can be estimated with less uncertainty and total uncertainty bounds are narrower with multiple types of responses than with a single type of response. Model calibration based on multiple types of responses can compromise different responses and hence the means and standard deviations of model error are the smallest. A feasible correlation coefficient between soil modulus and permeability can be obtained from model calibration with multiple types of responses and single type of response as long as the responses include displacement data.     

Effect of loading duration on uncertainty in creep analysis of clay

Some studies suggest that creep parameters should be determined using a greater quantity of creep test data to provide more reliable prediction regarding the deformation of soft soils. This study aims to investigate the effect of loading duration on model updating. One‐dimensional consolidation data of intact Vanttila clay under different loading durations collected from the literature is used for demonstration. The Bayesian probabilistic method is used to identify all unknown parameters based on the consolidation data during the entire consolidation process, and their uncertainty can be quantified through the obtained posterior probability density functions. Additionally, the optimal models are also determined from among 9 model candidates. The analyses indicate that the optimal models can describe the creep behavior of intact soft soils under different loading durations, and the adopted method can evaluate the effect of loading duration on uncertainty in the creep analysis. The uncertainty of a specific model and its model parameters decreases as more creep data are involved in the updating process, and the updated models that use more creep data can better capture the deformation behavior of an intact sample. The proposed method can provide quantified uncertainty in the process of model updating and assist engineers to decide whether the creep test data are sufficient for the creep analysis.     

VGI and crowdsourced data credibility analysis using spam email detection techniques

Volunteered geographic information (VGI) can be considered a subset of crowdsourced data (CSD) and its popularity has recently increased in a number of application areas. Disaster management is one of its key application areas in which the benefits of VGI and CSD are potentially very high. However, quality issues such as credibility, reliability and relevance are limiting many of the advantages of utilising CSD. Credibility issues arise as CSD come from a variety of heterogeneous sources including both professionals and untrained citizens. VGI and CSD are also highly unstructured and the quality and metadata are often undocumented. In the 2011 Australian floods, the general public and disaster management administrators used the Ushahidi Crowd-mapping platform to extensively communicate flood-related information including hazards, evacuations, emergency services, road closures and property damage. This study assessed the credibility of the Australian Broadcasting Corporation’s Ushahidi CrowdMap dataset using a Naïve Bayesian network approach based on models commonly used in spam email detection systems. The results of the study reveal that the spam email detection approach is potentially useful for CSD credibility detection with an accuracy of over 90% using a forced classification methodology.     

Pattern,style and timing of British–Irish Ice Sheet advance and retreat over the last 45 000 years: evidence from NW Scotland and the adjacent continental shelf

Predicting the future response of ice sheets to climate warming and rising global sea level is important but difficult. This is especially so when fast-flowing glaciers or ice streams, buffered by ice shelves, are grounded on beds below sea level. What happens when these ice shelves are removed? And how do the ice stream and the surrounding ice sheet respond to the abruptly altered boundary conditions? To address these questions and others we present new geological, geomorphological, geophysical and geochronological data from the ice-stream-dominated NW sector of the last British–Irish Ice Sheet (BIIS). The study area covers around 45 000 km² of NW Scotland and the surrounding continental shelf. Alongside seabed geomorphological mapping and Quaternary sediment analysis, we use a suite of over 100 new absolute ages (including cosmogenic-nuclide exposure ages, optically stimulated luminescence ages and radiocarbon dates) collected from onshore and offshore, to build a sector-wide ice-sheet reconstruction combining all available evidence with Bayesian chronosequence modelling. Using this information we present a detailed assessment of ice-sheet advance/retreat history, and the glaciological connections between different areas of the NW BIIS sector, at different times during the last glacial cycle. The results show a highly dynamic, partly marine, partly terrestrial, ice-sheet sector undergoing large size variations in response to sub-millennial-scale climatic (Dansgaard–Oeschger) cycles over the last 45 000 years. Superimposed on these trends we identify internally driven instabilities, operating at higher frequency, conditioned by local topographic factors, tidewater dynamics and glaciological feedbacks during deglaciation. Specifically, our new evidence indicates extensive marine-terminating ice-sheet glaciation of the NW BIIS sector during Greenland Stadials 12 to 9 – prior to the main ‘Late Weichselian’ ice-sheet glaciation. After a period of restricted glaciation, in Greenland Interstadials 8 to 6, we find good evidence for rapid renewed ice-sheet build-up in NW Scotland, with the Minch ice-stream terminus reaching the continental shelf edge in Greenland Stadial 5, perhaps only briefly. Deglaciation of the NW sector took place in numerous stages. Several grounding-zone wedges and moraines on the mid- and inner continental shelf attest to significant stabilizations of the ice-sheet grounding line, or ice margin, during overall retreat in Greenland Stadials 3 and 2, and to the development of ice shelves. NW Lewis was the first substantial present-day land area to deglaciate, in the first half of Greenland Stadial 3 at a time of globally reduced sea-level c. 26 kabp , followed by Cape Wrath at c. 24 kabp. The topographic confinement of the Minch straits probably promoted ice-shelf development in early Greenland Stadial 2, providing the ice stream with additional support and buffering it somewhat from external drivers. However, c. 20–19 kabp , as the grounding-line migrated into shoreward deepening water, coinciding with a marked change in marine geology and bed strength, the ice stream became unstable. We find that, once underway, grounding-line retreat proceeded in an uninterrupted fashion with the rapid loss of fronting ice shelves – first in the west, then the east troughs – before eventual glacier stabilization at fjord mouths in NW Scotland by ~17 kabp. Around the same time, ~19–17 kabp , ice-sheet lobes readvanced into the East Minch – possibly a glaciological response to the marine-instability-triggered loss of adjacent ice stream (and/or ice shelf) support in the Minch trough. An independent ice cap on Lewis also experienced margin oscillations during mid-Greenland Stadial 2, with an ice-accumulation centre in West Lewis existing into the latter part of Heinrich Stadial 1. Final ice-sheet deglaciation of NW mainland Scotland was punctuated by at least one other coherent readvance at c. 15.5 kabp , before significant ice-mass losses thereafter. At the glacial termination, c. 14.5 kabp , glaciers fed outwash sediment to now-abandoned coastal deltas in NW mainland Scotland around the time of global Meltwater Pulse 1A. Overall, this work on the BIIS NW sector reconstructs a highly dynamic ice-sheet oscillating in extent and volume for much of the last 45 000 years. Periods of expansive ice-sheet glaciation dominated by ice-streaming were interspersed with periods of much more restricted ice-cap or tidewater/fjordic glaciation. Finally, this work indicates that the role of ice streams in ice-sheet evolution is complex but mechanistically important throughout the lifetime of an ice sheet – with ice streams contributing to the regulation of ice-sheet health but also to the acceleration of ice-sheet demise via marine ice-sheet instabilities.     

长白山景区旅游安全风险动态评价研究

以长白山景区旅游安全为研究对象,以鱼骨图、动态贝叶斯、GIS技术等为基本研究方法,从研究区自然环境、社会环境及责任人为3个方面出发,筛选景区致险因子,构建景区旅游安全风险危险性评价指标体系,利用动态贝叶斯方法综合构建景区旅游安全风险动态评价模型;并以实测数据及景区统计数据为依据,划分景区旅游安全风险评价的4个动态时段,综合实现景区旅游安全风险动态风险评价。研究结果表明：① 中等以上风险区域呈条带状分布;② 高风险区域与主要景点重合;③ 长白山景区安全风险发生高概率的时段发生在第三个时段（12:00~14:00）;较高概率发生分别在第二个时段（10:00~12:00）与第四个时段（14:00~16:00）;中等概率发生较高的时段在第四个时段（14:00~16:00）;较低概率发生在第一个时段（8:00~10:00）。     

海洋环境因子对澳洲鲐亲体补充量关系的影响——基于贝叶斯模型平均法的研究

澳洲鲐（Scomber australasicus）是西北太平洋重要的中上层经济鱼类,生命周期相对较短,资源量受补充量影响明显,了解澳洲鲐太平洋群系补充量状况对掌握其资源量及确保其可持续利用具有重要的意义。本文利用产卵场1（30°~32°N,130°~132°E）海表面温度（sea surface temperature,SST1）、产卵场2（34°~35°N,138°~141°E）海表面温度（SST2）、索饵场（35°~45°N,140°~160°E）海表面温度（SST3）、潮位差（tidal range,TR）、太平洋年代际涛动（Pacific decadal oscillation,PDO）和亲体量（spawning stock biomass,SSB）6个影响因子任意组合与补充量构建多个模型,运用贝叶斯模型平均法（Bayesian model averaging,BMA）分析各个环境因子对资源补充量的解释能力,并预测其补充量的变化。结果表明,SSB对补充量具有最长期且稳定的解释能力,其次是SST3,PDO、TR、SST2、SST1也对补充量模型具有一定的解释能力。SST3是环境因子中影响最大的因子,可能是由于补充群体在索饵场内生活时间较长,索饵场温度对仔鱼或鱼卵的生长存活有较大的影响。研究认为,基于BMA的组合预报综合考虑了各个模型的优势,优于单一模型,可用于澳洲鲐资源补充量的预测。     

一种海洋混合层深度的智能识别方法研究

文章提出了一种识别混合层深度的人工智能方法。该方法在温度(密度)与压强(或深度)间建立线性模型, 并且将其系数和方差做成一组表征廓线特征的统计量。初始时为模型设定一个主观的先验分布, 在一个自海表向下移动的窗口内通过贝叶斯链式法则和最小描述长度原理学习新数据, 得到系数均值的最大后验概率估计。用F-检验识别系数发生突变的位置, 以此确定混合层的存在性及其深度。通过2017年2月太平洋海域的地转海洋学实时观测阵(Array for Real-time Geostrophic Oceanography, ARGO)数据进行测试, 并且以质量因子(Quality Index, QI)值作为判断识别混合层深度结果准确性的依据, 发现该方法相比于梯度法、阈值法、混合法、相对变化法、最大角度法和最优线性插值法在识别结果上具备更大的QI值。表明该方法能够准确识别混合层深度。     

Indoor localization for pedestrians with real-time capability using multi-sensor smartphones

ABSTRACT

The localization of persons or objects usually refers to a position determined in a spatial reference system. Outdoors, this is usually accomplished with Global Navigation Satellite Systems (GNSS). However, the automatic positioning of people in GNSS-free environments, especially inside of buildings (indoors) poses a huge challenge. Indoors, satellite signals are attenuated, shielded or reflected by building components (e.g. walls or ceilings). For selected applications, the automatic indoor positioning is possible based on different technologies (e.g. WiFi, RFID, or UWB). However, a standard solution is still not available. Many indoor positioning systems are only suitable for specific applications or are deployed under certain conditions, e.g. additional infrastructures or sensor technologies. Smartphones, as popular cost-effective multi-sensor systems, is a promising indoor localization platform for the mass-market and is increasingly coming into focus. Today’s devices are equipped with a variety of sensors that can be used for indoor positioning. In this contribution, an approach to smartphone-based pedestrian indoor localization is presented. The novelty of this approach refers to a holistic, real-time pedestrian localization inside of buildings based on multi-sensor smartphones and easy-to-install local positioning systems. For this purpose, the barometric altitude is estimated in order to derive the floor on which the user is located. The 2D position is determined subsequently using the principle of pedestrian dead reckoning based on user's movements extracted from the smartphone sensors. In order to minimize the strong error accumulation in the localization caused by various sensor errors, additional information is integrated into the position estimation. The building model is used to identify permissible (e.g. rooms, passageways) and impermissible (e.g. walls) building areas for the pedestrian. Several technologies contributing to higher precision and robustness are also included. For the fusion of different linear and non-linear data, an advanced algorithm based on the Sequential Monte Carlo method is presented.