Underwater Navigation Based on Real-Time Simultaneous Sound Speed Profile Correction

Precise sound speed profile (SSP) information is critical when using sonar for underwater terrain navigation. Nevertheless, acquiring SSP information in real-time is difficult, especially in underwater navigation environment. To account for this problem, this paper presents an underwater navigation method that applies real-time SSP correction to the terrain measurements. The method uses a probe to measure the surface sound speed simultaneously. Meanwhile, redundancy of topographic measurement data is exploited to derive the equivalent SSP information. The acquired equivalent SSP is updated continuously with particle filter algorithm. The terrain measurements can be corrected in real-time with the equivalent SSP to improve the performance of underwater terrain navigation. By removing the impact of inaccurate SSP from the terrain measurements, the proposed method can achieve precise and robust underwater navigation result without using an underway-profiling instrument. Simulated results confirm the good performance of the proposed method.     

Land-surface segmentation as a method to create strata for spatial sampling and its potential for digital soil mapping

Sampling efforts are constrained by limited availability of resources. Therefore, methods to reduce the number of samples, while still achieving reasonable accuracy are needed. Land-surface segmentation (LSS) has proven a powerful technique to partition digital elevation models (DEMs) and their derivatives into relatively homogeneous areas, which can be further employed as support in soil sampling. Though topography is one of the main soil forming factors, a robust assessment of the potential of this technique to digital soil mapping (DSM) is still missing. In this study, we aimed at evaluating the potential of LSS in stratifying a landscape into relatively homogeneous areas, which can be used as strata for guiding the selection of sampling points in DSM. The experiments were carried out in two study areas where soil samples were available. Land-surface derivatives were derived from DEMs and segmented with a tool based on the multiresolution segmentation algorithm, into objects considered as homogeneous soil-landscape divisions. Thus, one sample was randomly selected within each segment from the existing sample data, based on which predictions of soil classes/sub-orders and properties, i.e. soil texture and A-horizon thickness, were made. Results were compared with predictions based on simple random sampling (SRS) and conditioned Latin hypercube (cLHS). The segmentation-based sampling (SBS) scheme performed better than SRS and cLHS schemes in predicting the A-horizon thickness, soil texture fractions and soil classes, showing a high potential of LSS in stratifying a landscape for the purposes of DSM. The novelty of this study is in the way strata are constructed, rather than in the sampling design itself. Further research is needed to demonstrate the value of a SBS design for practical use. The analyses presented here further highlight the importance of considering locally adaptive techniques in optimization of sampling schemes and predictions of soil properties.     

Evaluating the impact of visualization of wildfire hazard upon decision-making under uncertainty

The paper investigates whether the methods chosen for representing uncertain geographic information aid or impair decision-making in the context of wildfire hazard. Through a series of three human subject experiments, utilizing 180 subjects and employing increasingly difficult tasks, this research evaluates the effect of five different visualizations and a text-based representation on decision-making under uncertainty. Our quantitative experiments focus specifically on the task of decision-making under uncertainty, rather than the task of reading levels of uncertainty from the map. To guard against the potential for generosity and risk seeking in decision-making under uncertainty, the experimental design uses performance-based incentives. The experiments showed that the choice of representation makes little difference to performance in cases where subjects are allowed the time and focus to consider their decisions. However, with the increasing difficulty of time pressure, subjects performed best using a spectral color hue-based representation, rather than more carefully designed cartographic representations. Text-based and simplified boundary encodings were among the worst performers. The results have implications for the performance of decision-making under uncertainty using static maps, especially in the stressful environments surrounding an emergency.     

Interactive discovery of sequential patterns in time series of wind data

Wind speed and direction vary over space and time due to the interactions between different pressures and temperature gradients within the atmospheric layers. Near the earth’s surface, these interactions are modulated by topography and artificial structures. Hence, characterizing wind behaviour over large areas and long periods is a complex but essential task for various energy-related applications. In this study, we present a novel approach to discover wind patterns by integrating sequential pattern mining and interactive visualization techniques. The approach relies on the use of the Linear time Closed pattern Miner sequence algorithm in conjunction with a time sliding window that allows the discovery of all sequential patterns present in the data. These patterns are then visualized using integrated 2D and 3D coordinated multiple views and visually explored to gain insight into the characteristics of the wind from a spatial, temporal and attribute (type of wind pattern) point of view. This proposed approach is used to analyse 10 years of hourly wind speed and direction data for 29 weather stations in the Netherlands. The results show that there are 15 main sequential patterns in the data. The spatial task shows that weather stations located in the same region do not necessarily experience similar wind pattern. For within the selected time interval, similar wind patterns can be observed in different stations and in the same station at different times of occurrence. The attribute task discovered that the repetitive occurrences of chosen pattern indicate as regular wind behaviour at different weather stations that persisted continuously over time. The results of these tasks show that the proposed interactive discovery facilitates the understanding of wind dynamics in space and time.     

Map-Based Web Tools Supporting Climate Change Adaptation

This article discusses the state of the art in geovisualization supporting climate change adaptation. We reviewed twenty selected map-based Web tools, classified by their content and functionality, and assessed them by visual representations, interactive functions, information type, target audience, and how vulnerability and adaptation to climate change are addressed. Our study concludes that the tools (1) can be classified as data viewers with basic functionality and data explorers offering more sophisticated interactive functions; (2) mostly feature moderate or high richness of data content; and (3) predominantly target expert users.     

AS350B3型直升机在中高山航空物探测量中的优势

中高山地区作业的航空地球物理勘探飞行器需要有高原适航性。通过对比空中国王350ER在起降条件、最大升限、最大续航能力及高原机动能力等特点,提出了在中高山地区的低高度、大比例尺的航空地球物理勘探飞行器的选型原则及飞行方法。通过甘肃某测区的实际测量飞行验证了该原则和方法的可行性。分析结果显示,AS350B3型直升机在中高山地区作业时表现出的实际飞行性能满足在该类型区域低高度、大比例尺的航空地球物理勘探的要求。     

3D打印技术在矿床学中的应用研究——以内蒙古乌力吉敖包萤石矿Ⅲ号矿体为例

3D打印(3D printing)是一种以三维模型为样本的快速成形技术,它通过逐层打印或粉末熔铸的方式来构造需要的立体图形。本文从3D打印技术的原理及其发展现状入手,重点列举内蒙古乌力吉敖包萤石矿,利用3D打印机打印具有现实可观性的地质体实体,探讨3D打印技术作为新兴的科技手段应用于矿床学教学与研究的应用价值和发展前景。研究发现,3D打印技术在矿体三维可视化中的应用符合地质图件立体化和3D打印技术多领域化的趋势,未来3D打印技术在地质领域的应用也有助于开拓矿床学教学和研究的新方式与新思路。     

A virtual globe-based time-critical adaptive visualization method for 3D city models

3D city models, which are important items of content on the virtual globe, are characterized by complicated structures and large amounts of data. These factors make the visualization of 3D city models highly dependent upon the performance of computer hardware. Thus, achieving the efficient rendering of 3D city models using different hardware performance levels represents one of the key problems currently facing researchers. This paper proposes a time-critical adaptive visualization method that first estimates the possible rendering time for each model according to the data structure of the model in addition to the CPU/GPU performance of the computer. It then dynamically adjusts the rendering level for each model based on the results of an estimation of the rendering time to ensure that the final scene can be completed within a given time. To verify the effectiveness and flexibility of this method, it is applied using different computers. The results show that the adaptive visualization method presented in this paper not only can adapt to computers with different levels of performances but also demonstrates an obvious improvement in the time estimation precision, visual effects, and optimization speed relative to existing adaptive visualization methods.     

定量研究雅安地形坡向坡度对降水分布的影响

利用四川省雅安市30 m分辨率基础高程数据,提取栅格的坡向和坡度参数,将雅安307个区域自动站在2017年汛期(6—9月)共50次的降水天气个例,分为16次大尺度降水和34次中小尺度降水,使用对应时次的欧洲中心细网格0.25°×0.25°再分析风场资料,根据不同的站点地形高度将风场合成平均风场,和各站点地形的坡向和坡度计算出其动力抬升作用,同时使用当天日照和天文太阳辐射值来计算地形的热力抬升作用,与对应降水过程的降水分布进行多元线性回归,根据回归的标准系数的大小确定各自变量对降水分布的影响,得出以下结论:(1)中小尺度降水中,地形的热力抬升作用对降水分布的影响作用最大,其次是海拔高度,地形的动力抬升作用在三者中对降水分布的影响最小;(2)在大尺度降水中刚好相反,地形的动力抬升对降水的分布影响作用最大,海拔次之,热力抬升作用在三者中影响作用最小;(3)日降水量最大值的站点海拔高度基本位于1 000 m左右,与抬升凝结高度对应较好;(4)从长期的统计来看,地形的动力作用和地表的植被情况对降水分布的影响最大。在实际预报工作用,根据不同的降水类型,关注不同的动力和热力作用对于判断降水分布大值区的位置有较好的参考作用。     

延庆-张家口地区复杂地形冬季山谷风特征分析

基于2016年12月—2017年2月和2017年12月—2018年2月两年冬季的近地面自动气象站逐时观测数据以及张家口探空数据分析延庆-张家口一带（包括张家口崇礼、赤城、海坨、小五台山区,延怀、怀涿、洋河、蔚县盆地以及北京延庆、昌平、怀柔部分平原地区）复杂地形的风场精细化时、空分布特征,揭示不同复杂地形下局地风场的时、空变化规律,加深对复杂地形动力、热力作用对近地面风场影响的认识,为冬季山区风场预报以及复杂地形数值模式改进提供参考。结果表明:晴朗小风天风持续性作为矢量平均风速和标量平均风速的比值,可以作为研究风场变化规律的重要参数。根据风持续性的日变化特征,可以将研究区域内所有站点分为10种类型,分别代表不同局地地形特征的影响,风持续与风向变化的相关也很强。研究区域主要有3种类型的地形风:斜坡风、峡谷风以及较大尺度的山区平原风。不同地形特征下的风场、风持续性存在明显不同的日变化特征,山风和谷风相互转化的时间也不同,山区最早,盆地次之,平原区最晚;山风时段持续时间较谷风时段长,风速小;晴朗小风天实测风反映了实际风场的特征,而排除环境背景风场,弱化地形动力作用后整个冬季的局地风作为理论山谷风,更能反映热力作用下的山谷风特征。