gLucifer: next generation visualization framework for high-performance computational geodynamics

High-performance computing provides unprecedented capabilities to produce higher resolution 4-D models in a fraction of time. Thus, the need exists for a new generation of visualization systems able to maintain parity with the enormous volume of data generated. In attempting to write this much data to disk, each computational step introduces a significant performance bottleneck, yet most existing visualization software packages inherently rely on reading data in from a dump file. Available packages make this assumption of postprocessing at quite a fundamental level and are not very well suited for plotting very large numbers of specialized particles. This necessitates the creation of a new visualization system that meets the needs of large-scale geodynamic modeling. We have developed such a system, gLucifer, using a software framework approach that allows efficient reuse of our efforts in other areas of research. gLucifer is capable of producing movies of a 4-D data set “on the fly” (simultaneously with running the parallel scientific application) without creating a performance bottleneck. By eliminating most of the human efforts involved in visualizing results through postprocessing, gLucifer reconnects the scientist to the numerical experiment as it unfolds. Data sets that were previously very difficult to even manage may be efficiently explored and interrogated without writing to disk, and because this approach is based entirely on memory distributed across as many processors as are being utilized by the scientific application, the visualization solution is scalable into terabytes of data being rendered in real time.     

Making local futures tangible—Synthesizing, downscaling, and visualizing climate change scenarios for participatory capacity building

Local in its causes and global in its impacts, climate change still poses an unresolved challenge for scientists, politicians, entrepreneurs, and citizens. Climate change research is largely global in focus, aims at enhanced understanding, and is driven by experts, all of which seem to be insufficient to anchor climate change action in regional and local contexts. We present results from a participatory scenario study conducted in collaboration with the municipality of Delta in SW British Columbia, Canada. This study applies a participatory capacity building approach for climate change action at the local level where the sources of emissions and the mechanisms of adaptation reside and where climate change is meaningful to decision-makers and stakeholders alike. The multi-scale scenario approach consists of synthesizing global climate change scenarios, downscaling them to the regional and local level, and finally visualizing alternative climate scenarios out to 2100 in 3D views of familiar, local places. We critically discuss the scenarios produced and the strengths and weaknesses of the approach applied.     

多维GIS矿产评价数据管理系统设计和实现

矿产资源评价需通过各种物探、化探、航空磁法、遥感、地质和实地调查资料综合分析以确定钻井孔位.针对多源、多时相、多尺度矿产资源勘探资料一体化管理和可视化分析,提出了一种基于分布式多维GIS模型的矿产资源评价数据管理方法.首先,分析了矿产资源预测评价数据资料特征,提出基于多维GIS模型的矿产资源评价数据管理模型;其次,提出了多源矿产资源评价数据处理策略,设计了一种全球瓦片金字塔模型的栅格和地形数据处理方法;再次,设计了分布式多维GIS矿产资源评价数据管理系统体系结构和功能模块,提出了双缓存性能优化方案;最后,开发实现了一个典型的矿产资源评价数据管理系统,实现了多达40种二维、三维数据、文档、多媒体等矿产资源评价数据一体化管理和可视化分析,可用于分布式矿产资源勘探评价的全球协同办公.     

基于ArcView GIS的沉降观测数据三维分析研究

本文在了解国内外沉降观测研究现状的基础上,从变形观测的理论出发,探求提高沉降观测操作的质量,并结合亚奥国家广场建筑物沉降观测实例,对测量所得到的沉降监测数据进行科学整理。文章从理论分析入手,结合沉降观测收集数据,然后在相关理论支持下进行监测数据的分析。在数据分析过程中,着重运用GIS软件实现沉降的三维模拟,并绘制沉降等值线,直接、美观的再现了沉降的过程。经过分析,得出亚奥国际广场建筑物沉降状况的合理性,并提出了提高沉降观测质量、科学整理数据和成果分析的相关建议。     

基于OpenGL的地形三维可视化研究

本文利用OpenGL开放图形库的200多个函数,在前人对三维可视化研究的基础上,基于实际生产中的需求,提出一种可行的“二次简化法”,实践证明,这种处理方法能够使生产出的三维地形图在兼顾高度逼真的同时,能够实际地处理空间分析操作运算,满足了生产中的需要。     

Multi-resolution clustering analysis and 3-D visualization of multitudinous synthetic earthquakes

We use modern and novel techniques to study the problems associated with detection and analysis of multitudinous seismic events, which form the background for isolated great earthquakes. This new approach involves multivariate analysis of low and large magnitude events recorded in space over a couple of centuries in time. We propose here the deployment of the clustering scheme both for extracting small local structures and large-scale trends in synthetic data obtained from four numerically simulated models with: uniform properties (U), a Parkfield-type asperity (A), fractal brittle properties (F), and multi-size-heterogeneity fault zone (M). The mutual nearest neighbor (mnn) clustering scheme allows for extraction of multi-resolutional seismic anomalies in both the spatio-temporal and multi-dimensional feature space. We demonstrate that the large earthquakes are correlated with a certain pathway of smaller events. Visualization of the anomalies by using a recently introduced visualization package Amira reveals clearly the spatio-temporal relationships between clusters of small, medium and large earthquakes, indicating significant stress relaxation across the entire fault region. We demonstrate that this mnn scheme can extract distinct clusters of the smallest events, which precede and follow a singularly large magnitude earthquake. These clusters form larger spatio-temporal structures comprising a series of large earthquakes. The link between the large and medium magnitude events is not so clearly understood. Short-ranged correlations are dominated by strong spatio-temporal anomalies, thus reflecting the global seismic properties of the entire fault zone.Electronic Supplementary Material Supplementary material is available for this article if you access the article at . A link in the frame on the left on that page takes you directly to the supplementary material.     

神威集合预报可视化实时监控系统在神威机上的设计与实现

根据神威集合数值天气预报的运行特点, 针对其运行过程中可能遇到的问题, 介绍了自主研制的可视化实时监控系统的解决方案。     

Web-based terrain and vector maps visualization for Wenchuan earthquake

This paper presents a Web-based three-dimensional Geographic Information System (3DGIS) for Wenchuan earthquake disaster assessment. With the help of information technology resources, geoscientists are in a position to learn more about the structure of the earthquake in efficient ways. Due to huge spatial datasets of Wenchuan, China and narrow network bandwidth, general-purpose applications are difficult to transmit and visualize these datasets on the network. The application aims to interactively represent and transfer large spatial objects of Wenchuan County, China, as well as for dynamically rendering them in networking environments. Level-of-detail (LOD) terrain models and vector maps are created, and the server–client architecture is presented. The application provides an effective way for powerful access and manipulation of large-scale Wenchuan datasets.     

基于cGML和Mobile SVG的手机地图可视化研究

提出了基于Mobile SVG的移动地图可视化的设计思路,研究了Mobile SVG的坐标系统和坐标转换,实现了Mobile SVG移动地图的可视化。     

Identification and prioritization of uncertainties for management of Eastern Atlantic bluefin tuna (Thunnus thynnus)

In recent decades there has been steady progress towards a risk-based management approach for fisheries. An important first step in a risk analysis framework is scoping to identify, describe and catalog the sources of uncertainty that might have an impact on a fishery. This paper introduces a methodology based on a range of tools to formalize the process of elicitation of uncertainties, from both experts and stakeholders, for the International Commission for the Conservation of Atlantic Tunas (ICCAT). ICCAT is a regional fisheries management organization responsible for the conservation of tunas and other highly migratory fish in the Atlantic Ocean and its adjacent seas. The aim of the elicitation was to identify and prioritize uncertainties for inclusion in Operating Models for Management Strategy Evaluation (MSE). The tool presented in this paper supports the qualitative prioritization of uncertainties, while also visualizing the degree of consensus among stakeholders on particular issues. Perceptions of uncertainty in fisheries often vary widely among scientists, industry and other interest groups, so tools that can facilitate inclusion and representation of different opinions are useful where decision-making depends on broad agreement and more generally, where effective management depends on commitment from stakeholders.