空间信息多级网格及其功能

从思考地理空间数据在网格计算环境下的表示方法出发,提出了一种空间信息表示新方法——空间信息多级网格SIMG(SpatialInformationMulti-Grid)。介绍了空间信息多级网格的概念和核心思想,重点阐述了SIMG的三大功能,并展望了SIMG的应用前景。     

High-performance three-horizon composition algorithm for large-scale terrains

This work presents a high-performance algorithm to compute the horizon in very large high-resolution DEMs. We used Stewart's algorithm as the core of our implementation and considered that the horizon has three components: the ground, near, and far horizons. To eliminate the edge-effect, we introduced a multi-resolution halo method. Moreover, we used a new data partition approach, to substantially increase the parallelism in the algorithm. In addition, several optimizations have been applied to considerably reduce the number of arithmetical operations in the core of the algorithm. The experimental results have demonstrated that by applying the above-described contributions, the proposed algorithm is more than twice faster than Stewart's algorithm while maintaining the same accuracy.     

A general-purpose parallel raster processing programming library test application using a geographic cellular automata model

A general-purpose parallel raster processing programming library (pRPL) was developed and applied to speed up a commonly used cellular automaton model with known tractability limitations. The library is suitable for use by geographic information scientists with basic programming skills, but who lack knowledge and experience of parallel computing and programming. pRPL is a general-purpose programming library that provides generic support for raster processing, including local-scope, neighborhood-scope, regional-scope, and global-scope algorithms as long as they are parallelizable. The library also supports multilayer algorithms. Besides the standard data domain decomposition methods, pRPL provides a spatially adaptive quad-tree-based decomposition to produce more evenly distributed workloads among processors. Data parallelism and task parallelism are supported, with both static and dynamic load-balancing. By grouping processors, pRPL also supports data–task hybrid parallelism, i.e., data parallelism within a processor group and task parallelism among processor groups. pSLEUTH, a parallel version of a well-known cellular automata model for simulating urban land-use change (SLEUTH), was developed to demonstrate full utilization of the advanced features of pRPL. Experiments with real-world data sets were conducted and the performance of pSLEUTH measured. We conclude not only that pRPL greatly reduces the development complexity of implementing a parallel raster-processing algorithm, it also greatly reduces the computing time of computationally intensive raster-processing algorithms, as demonstrated with pSLEUTH.     

Massively parallel spatial point pattern analysis: Ripley’s K function accelerated using graphics processing units

This study presents a massively parallel spatial computing approach that uses general-purpose graphics processing units (GPUs) to accelerate Ripley’s K function for univariate spatial point pattern analysis. Ripley’s K function is a representative spatial point pattern analysis approach that allows for quantitatively evaluating the spatial dispersion characteristics of point patterns. However, considerable computation is often required when analyzing large spatial data using Ripley’s K function. In this study, we developed a massively parallel approach of Ripley’s K function for accelerating spatial point pattern analysis. GPUs serve as a massively parallel platform that is built on many-core architecture for speeding up Ripley’s K function. Variable-grained domain decomposition and thread-level synchronization based on shared memory are parallel strategies designed to exploit concurrency in the spatial algorithm of Ripley’s K function for efficient parallelization. Experimental results demonstrate that substantial acceleration is obtained for Ripley’s K function parallelized within GPU environments.     

施甸盆地三维地震动研究

本文利用三维施甸盆地模型以及川滇地区的地壳速度结构,采用谱元法和并行计算技术,考虑地形的影响,模拟了盆地外围中等设定地震作用下施甸盆地地震波的传播,分析了面波的产生和传播,研究了该盆地不同位置剖面地震动的差异和原因.研究表明,小型盆地在中等地震的作用下盆地内部地震动空间差异很大,盆地中较深的小型凹陷更容易汇聚面波,形成更强的振动,位于覆盖层厚度剧烈变化区域的地震动强度也会很大,甚至大于覆盖层厚的区域.较基岩地震动,盆地内地震动持续时间明显增加,地震动的放大作用明显,这也是盆地震害严重的主要原因之一.     

On generalised and specialised spatial information grids: are geo-services ready?

Abstract

After the set-up of a spatial data infrastructure (SDI) and a national information infrastructure (NII) in many countries, the provision of geo-services became one of the most important and attractive tasks. With the integration of global positioning system (GPS), geographic information system (GIS) and remote sensing (RS), we can, in principle, answer any geo-spatial related question: when and where what object has which changes? An intelligent geo-service agent could provide end-users with the most necessary information in the shortest time and at the lowest cost. Unfortunately there is still a long way to go to achieve such goals. The central component in such geo-services is the integration of the spatial information system with a computing grid via wire- and wireless communication networks. This paper will mainly discuss the grid technology and its integration with spatial information technology, expounding potential problems and possible resolutions. A novel categorising of information grids in the context of geo-spatial information is proposed: generalised and specialised spatial information grids.     

当代云计算发展研究现状

地理信息技术和地理信息产业作为信息产业的重要组成部分,一直与其同步发展或紧随其后。目前,第三次信息化浪潮和未来技术的代表云计算正在迅速兴起,全球各大IT公司竞相进入云计算领域,抢占制高点;我国也高度重视这一战略性新兴产业,呈现出科研先行,政府推动,企业参与,风起"云"涌的态势。全球学术界和企业界密切协作,有力推动了云计算技术的发展。测绘地理信息界需要了解国际国内云计算研究发展现状。     

3D GIS支持下盐腔围岩三维计算模型的生成

目前盐腔围岩蠕变模拟中计算网格生成多是理想化的,并没有充分利用真实探测数据。针对这些问题,提出了一种新的三维计算模型生成方法。借助HalfEdge数据结构,基于研究区域边界、DEM（digital element model,数字高程模型）和钻井数据,构建了研究区域地层三维模型;基于声纳测腔数据构建了盐腔三维模型,并对其进行了拓扑检查与修正;将地层三维模型与盐腔三维模型进行三维空间布尔运算,获取盐腔围岩三维模型;通过对该模型进行三维空间网格离散,得到盐腔围岩四面体网格单元,即数值模拟计算模型。通过该方法构建的三维计算模型,可以为后期盐腔围岩蠕变数值模拟过程提供有效的计算网格,进而可以为盐腔的建造,尤其是安全合理地利用盐腔提供科学依据和技术支持。     

基于集群的影像并行OPTA算法研究

并行计算是提高海量遥感影像细化处理速度的有效途径.基于对OPTA细化算法的分析,深入研究OPTA细化并行算法中数据划分和数据通信优化等关键问题,提出一种适合集群并行处理的通信优化并行算法,实验证明该算法具有良好的加速比,适合集群计算环境下海量遥感影像的细化处理.     

利用流水线技术的遥感影像并行处理

针对现有的OpenMP和直接的线程并行法难以对遥感影像处理链进行加速的问题,引入流水线概念对复杂的功能链进行并行加速,提出了基于流水线技术的遥感影像并行处理方法。影像处理实验验证了流水线在遥感影像多级连续处理方面的优势。