Enabling point pattern analysis on spatial big data using cloud computing: optimizing and accelerating Ripley’s K function

Performing point pattern analysis using Ripley’s K function on point events of large size is computationally intensive as it involves massive point-wise comparisons, time-consuming edge effect correction weights calculation, and a large number of simulations. This article presented two strategies to optimize the algorithm for point pattern analysis using Ripley’s K function and utilized cloud computing to further accelerate the optimized algorithm. The first optimization sorted the points on their x and y coordinates and thus narrowed the scope of searching for neighboring points down to a rectangular area around each point in estimating K function. Using the actual study area in computing edge effect correction weights is essential to estimate an unbiased K function, but is very computationally intensive if the study area is of complex shape. The second optimization reused the previously computed weights to avoid repeating expensive weights calculation. The optimized algorithm was then parallelized using Open Multi-Processing (OpenMP) and hybrid Message Passing Interface (MPI)/OpenMP on the cloud computing platform. Performance testing showed that the optimizations effectively accelerated point pattern analysis using K function by a factor of 8 using both the sequential version and the OpenMP-parallel version of the optimized algorithm. While the OpenMP-based parallelization achieved good scalability with respect to the number of CPU cores utilized and the problem size, the hybrid MPI/OpenMP-based parallelization significantly shortened the time for estimating K function and performing simulations by utilizing computing resources on multiple computing nodes. Computational challenge imposed by point pattern analysis tasks on point events of large size involving a large number of simulations can be addressed by utilizing elastic, distributed cloud resources.     

Free and open source software for geospatial applications (FOSS4G) to support Future Earth

ABSTRACT

The development, integration, and distribution of the information and spatial data infrastructure (i.e. Digital Earth; DE) necessary to support the vision and goals of Future Earth (FE) will occur in a distributed fashion, in very diverse technological, institutional, socio-cultural, and economic contexts around the world. This complex context and ambitious goals require bringing to bear not only the best minds, but also the best science and technologies available. Free and Open Source Software for Geospatial Applications (FOSS4G) offers mature, capable and reliable software to contribute to the creation of this infrastructure. In this paper we point to a selected set of some of the most mature and reliable FOSS4G solutions that can be used to develop the functionality required as part of DE and FE. We provide examples of large-scale, sophisticated, mission-critical applications of each software to illustrate their power and capabilities in systems where they perform roles or functionality similar to the ones they could perform as part of DE and FE. We provide information and resources to assist the readers in carrying out their own assessments to select the best FOSS4G solutions for their particular contexts and system development needs.     

语义约束的RVT模型到CityGML模型的转换方法

建筑信息模型(BIM)与地理信息系统(GIS)集成,不仅使得精细化的三维模型得到极大重用,同时两者的数据集成和共享可实现从几何到物理和功能特性的多尺度综合表达,已经成为新一代数字城市三维建模的关键途径之一。本文选取典型的BIM模型数据格式(RVT),提出语义约束的RVT模型到City GML模型的转换方法,以BIM模型丰富的语义信息为约束实现几何简化及转换,同时实现了几何部件与语义信息的一一映射及语义输出,并以建筑模型、暖通、桥梁模型为例进行了验证。     

网格GIS中地理空间数据访问与集成技术研究

将网格技术应用于地理信息领域,构建实现地理信息资源共享与协同工作的网格地理信息系统,是目前地理信息行业研究的热点之一。OGC制定的网络服务规范作为得到广泛支持的地理空间数据互操作规范。与网格技术的相关规范存在许多不兼容之处,使得OGC服务在网格体系下难于集成和管理。文章研究了OGC数据服务WMS,WFS和wCS的相关规范和OGSA—DAI网格中间件技术,提出将OGC数据服务扩展为OGSA—DAI的数据资源的方案,将WMS,WFS和WCS封装为符合WSRF的网格资源,实现分布式异构地理空间数据在OGSA—DAI框架下的访问、集成与管理。此方案提供了一种将OGC服务集成到网格环境中的方法,比较容易实现,对相关研发工作的开展具有很好的借鉴作用。     

河南省地名数据库的构建方法研究

河南省地名数据库是国家地名数据库的重要组成部分。介绍了河南省地名数据库建立的背景,按照国家标准要求建立了分布式的省、地市、县三级数据库,并以此为出发点,系统论述了河南省地名数据的分类方式与组织方式,描述了河南省地名数据库的逻辑构成与物理构成;论述了地名数据库建库的基本技术,包括基于元数据的建库方案与基于SuperMap的空间数据库技术。河南省地名数据库的建立充分考虑了城市地名服务的特点与要求,在民政服务信息化方面做了有益的尝试。     

地学空间数据模型的研究

以美国、加拿大、澳大利亚等国家地质调查局建立的地学空间数据库为基础，阐述了建立地学空间数据模型的重要意义。归纳了地学空间数据模型的设计原则，认为图层与属性表的实体关系、图层及属性表多少为佳是着重要解决的问题。通过对地学空间数据模型概念设计的深入研究，可以使地学空间数据模型设计人员正确地理解地学专家领域的问题，而逻辑设计则是地学空间数据模型的核心。地学逻辑数据模型研究的主要任务有图层的划分、属性表定义及关联、空间图形数据图层与属性数据的关联等。     

Web环境下地理空间数据的开放式表达体系研究

对Web环境下的适合分布式异构地理空间数据表达的地理空间数据模型进行了研究 ,在此基础上提出了虚拟地图、实体地图以及可视化地图的概念 ,并分别基于XML、GML以及SVG创建了开放式地理空间数据的三层表达体系 ,该体系的建立为开放式WebGIS的数据互操作奠定了基础。     

LBS中位置及其语义的研究

阐述了两种LBS位置表示方法，引入了语义位置的概念，对现有的语义位置概念作了修正。强调了位置属性也是语义位置的重要组成部分。通过对位置概念内涵和外延的分析，讨论了位置属性所包括的内容；运用层次建模，实现了位置之间关系的描述。为了能够规范化地描述语义位置，运用本体技术，对位置所包含的语义信息进行了描述，建立了能够被计算机识别和处理的OWI。位置本体模型。通过对语义位置的本体建模，实现了位置信息的知识化描述，为实现个性化服务奠定了基础。     

面向三维空间信息应用的网格框架体系及应用研究

针对三维空间信息应用领域的具体内容和特点，提出了一种适合三维空间信息应用的网格框架体系。围绕该体系讨论了三维空间信息的具体应用及涉及的关键技术，给出了三维空间信息应用网格的系统原型（GridVRMap）。