基于VBA的ArcObjects二次开发在数据处理中的应用——以Shapefile的Merge和Split批处理为例

以ArcGIS为数据处理平台,结合土地变更调查中的数据处理工作,分析ArcToolBox中工具存在的不足,以Merge和Split工具为例,探讨面向任务时基于VBA的ArcObjects二次开发的基本原理与设计思路,可为实际工作中的其他数据处理提供借鉴。     

A Multi‐granularity Parallel Model for Unified Remote Sensing Image Processing WebServices

The growth of the Web has resulted in the Web‐based sharing of distributed geospatial data and computational resources. The Geospatial Processing Web (GeoPW) described here is a set of services that provide a wide array of geo‐processing utilities over the Web and make geo‐processing functionalities easily accessible to users. High‐performance remote sensing image processing is an important component of the GeoPW. The design and implementation of high‐performance image processing are, at present, an actively pursued research topic. Researchers have proposed various parallel strategies for single image processing algorithm, based on a computer science approach to parallel processing. This article proposes a multi‐granularity parallel model for various remote sensing image processing algorithms. This model has four hierarchical interfaces that are labeled the Region of Interest oriented (ROI‐oriented), Decompose/Merge, Hierarchical Task Chain and Dynamic Task interfaces or sub‐models. In addition, interfaces, definitions, parallel task scheduling and fault‐tolerance mechanisms are described in detail. Based on the model and methods, we propose an open‐source online platform named OpenRS‐Cloud. A number of parallel algorithms were uniformly and efficiently developed, thus certifying the validity of the multi‐granularity parallel model for unified remote sensing image processing web services.     

A distributed approach for calculating inundation height based on Dijkstra's algorithm

This research proposed a parallelized approach to scaling up the calculation of inundation height, the minimum sea‐level rise required to inundate a cell on a digital elevation model, which is based on Dijkstra's algorithm for shortest‐path calculations on a graph. Our approach is based on the concepts of spatial decomposition, calculate‐and‐correct, and a master/worker parallelization paradigm. The approach was tested using the U.S. Coastal Relief Model (CRM) dataset from the National Geophysical Data Center on a multicore desktop computer and various supercomputing resources through the U.S. Extreme Science and Engineering Discovery Environment (XSEDE) program. Our parallel implementation not only enables computations that were larger than previously possible, but also significantly outperforms serial implementations with respect to running time and memory footprint as the number of processing cores increases. The efficiency of the scalability seemed to be tied to tile size and flattened out at a certain number of workers.     

空间数据多服务器群集及高性能实现策略

针对当前海量空间数据网络化管理的特殊要求,分析了改善新一代地理信息系统(GIS)整体性能所需要解决的问题,剖析并引入了群集技术,充分发挥群集技术在高性能运算和高可靠性多服务器架构等方面的技术优势,优化设计了GIS群集多PC服务器体系架构,并结合空间索引分区等常规海量空间数据库管理策略,开发了一套实用化的高效空间定位、多缓冲策略等基于群集的多服务器海量空间数据管理技术。Oracle真正应用群集(RAC)数据库系统在图库管理中的应用,验证了群集空间数据多服务器管理平台的整体性能优越性。     

Observation‐Driven Geo‐Ontology Engineering

Big Data, Linked Data, Smart Dust, Digital Earth, and e‐Science are just some of the names for research trends that surfaced over the last years. While all of them address different visions and needs, they share a common theme: How do we manage massive amounts of heterogeneous data, derive knowledge out of them instead of drowning in information, and how do we make our findings reproducible and reusable by others? In a network of knowledge, topics span across scientific disciplines and the idea of domain ontologies as common agreements seems like an illusion. In this work, we argue that these trends require a radical paradigm shift in ontology engineering away from a small number of authoritative, global ontologies developed top‐down, to a high number of local ontologies that are driven by application needs and developed bottom‐up out of observation data. Similarly as the early Web was replaced by a social Web in which volunteers produce data instead of purely consuming it, the next generation of knowledge infrastructures has to enable users to become knowledge engineers themselves. Surprisingly, existing ontology engineering frameworks are not well suited for this new perspective. Hence, we propose an observation‐driven ontology engineering framework, show how its layers can be realized using specific methodologies, and relate the framework to existing work on geo‐ontologies.     

Asynchronous Geospatial Processing: An Event‐Driven Push‐Based Architecture for the OGC Web Processing Service

Geospatial processing tasks like solar potential analyses or floodplain investigations within flood scenarios are often complex and deal with large amounts of data. If such analysis operations are performed in distributed web‐based systems, technical capabilities are mostly not sufficient. Major shortcomings comprise the potentially long execution times and the vast amount of messaging overhead that arise from common poll‐based approaches. To overcome these issues, an approach for an event‐driven architecture for web‐based geospatial processing is proposed within this article. First, this article presents a thorough qualitative discussion of different available technologies for push‐based notifications. The aim of this discussion is to find the most suitable push‐based messaging technologies for application with OGC Web Processing Services (WPS). Based on this, an event‐driven architecture for asynchronous geospatial processing with the WPS is presented, building on the Web Socket Protocol as the transport protocol and the OGC Event Service as the message‐oriented middleware. The proposed architecture allows pushing notifications to clients once a task has completed. This paradigm enables the efficient execution of web‐based geospatial processing tasks as well as the integration of geographical analyses into event‐driven real‐time workflows.     

Out‐of‐Core GPU‐based Change Detection in Massive 3D Point Clouds

If sites, cities, and landscapes are captured at different points in time using technology such as LiDAR, large collections of 3D point clouds result. Their efficient storage, processing, analysis, and presentation constitute a challenging task because of limited computation, memory, and time resources. In this work, we present an approach to detect changes in massive 3D point clouds based on an out‐of‐core spatial data structure that is designed to store data acquired at different points in time and to efficiently attribute 3D points with distance information. Based on this data structure, we present and evaluate different processing schemes optimized for performing the calculation on the CPU and GPU. In addition, we present a point‐based rendering technique adapted for attributed 3D point clouds, to enable effective out‐of‐core real‐time visualization of the computation results. Our approach enables conclusions to be drawn about temporal changes in large highly accurate 3D geodata sets of a captured area at reasonable preprocessing and rendering times. We evaluate our approach with two data sets from different points in time for the urban area of a city, describe its characteristics, and report on applications.     

Collaborative Web‐GIS Design: A Case Study for Road Risk Analysis and Monitoring

This article presents a methodology for designing a WebGIS framework intended for automatically analyzing spatial data and updating statistics of interest with new information inserted daily by multiple users via a Web portal. A practical example is used on vehicle accident data for assessing risk in specific road segments. Two main blocks integrated together will be described: the collaborative block and the data‐analysis block. The former gives end‐users computer‐aided tools to view, insert, modify and manage data related to accidents and traffic monitoring sensors, whereas the latter is developed to automatically analyze the accident data coming from user's collaboration. Because different agencies can survey accident sites, a collaborative environment is necessary – and a Web‐based solution is ideal – for permitting multi‐user access and data insertion. A centralized approach to process the data in real time is described in all its components. Server‐side Structured Query Language functions optimize performance by using dedicated libraries for spatial processing and re‐structuring the attributes associated with elements which are consequently re‐classified for correct color‐scaling. The end‐product is a system that provides a seamless integration of front‐end tools for user collaboration and back‐end tools to update accident risk statistics in real time and provide them to stakeholders.     

多核环境下的GNSS数据并行处理研究

多核处理器已成为当前通用计算机体系架构的主流,相应的多核并行计算技术及其应用引起了越来越多的重视,而传统的GNSS数据处理程序都是针对单处理器体系架构编写的。本文对当前多核环境下多时段或者多测站的GNSS数据处理所涉及的计算密集型任务并行算法进行研究,分析了GNSS数据处理涉及的热点计算任务,提出基于分块理论的矩阵乘法运算、矩阵分解运算等数值计算并行方法,对比了单核和多核环境下的计算时间。通过多个算例验证多核并行设计方法的有效性,利用.NET4.0框架下的Parallel Extensions实现相关并行设计。实验结果表明,GNSS数据处理的多核并行计算能充分发挥多核体系带来的性能优势,极大提高资源利用效率和GNSS数据处理效率。     

空间大数据分析引擎的设计与实现

针对空间大数据分析需求日益增加但缺乏关键技术支撑的问题,融合GIS与大数据技术构建空间大数据分析引擎成为有效的解决方法.本文基于SuperMap iObjects for Java和Apache Spark计算框架设计并实现了空间大数据分析引擎,并将其用于计算航路拥挤情况的要素连接分析实验.研究结果表明,空间大数据分析引擎处理性能高,具备保障空间大数据分析的能力.     

Web‐based real‐time visualization of large‐scale weather radar data using 3D tiles

Weather radar data play an important role in meteorological analysis and forecasting. In particular, web‐based real‐time 3D visualization will enable and enhance various meteorological applications by avoiding the dissemination of a large amount of data over the internet. Despite that, most existing studies are either limited to 2D or small‐scale data analytics due to methodological limitations. This article proposes a new framework to enable web‐based real‐time 3D visualization of large‐scale weather radar data using 3D tiles and WebGIS technology. The 3D tiles technology is an open specification for online streaming massive heterogeneous 3D geospatial datasets, which is designed to improve rendering performance and reduce memory consumption. First, the weather radar data from multiple single‐radar sites across a large coverage area are organized into a spliced grid data (i.e., weather radar composing data, WRCD). Next, the WRCD is converted into a widely used 3D tile data structure in four steps: data preprocessing, data indexing, data transformation, and 3D tile generation. Last, to validate the feasibility of the proposed strategy, a prototype, namely Meteo3D at https://202.195.237.252:82 , is implemented to accommodate the WRCD collected from all the weather radar sites over the whole of China. The results show that near real‐time and accurate visualization for the monitoring and early warning of strong convective weather can be achieved.     

BIM及空间大数据技术支持下的铁路隧道施工数据管理

针对铁路隧道施工项目海量异构数据存储困难、信息不共享、展示不直观、数据价值利用不充分等问题,本文利用BIM及空间大数据技术,研究探讨了隧道施工项目海量异构数据的分布式存储、网络共享、三维查询、智能分析决策等技术,实现了隧道施工项目高效的信息化管理;提出了铁路隧道BIM三维模型动态建立的技术方案,设计了隧道施工管理空间大数据的云平台框架,研发了一套铁路隧道施工空间大数据管理应用云平台;通过对平台的成功开发与应用,验证了框架体系的可行性,提高了隧道施工项目管理的信息化水平。     

分布式空间数据存储对象

针对地理空间数据的地域性和日益突出的数据量快速增长特性，提出了分布式空间数据存储对象概念。介绍了基于分布式空间数据存储对象来实现一种高性能、可伸缩、跨平台共事的大规模海量空间数据存储管理机制，为分布式GIS数据存储提供了一种新的思路。     

VGDI – Advancing the Concept: Volunteered Geo‐Dynamic Information and its Benefits for Population Dynamics Modeling

The concept of Volunteered Geographic Information (VGI) has progressed from being an exotic prospect to making a profound impact on GIScience and geography in general, as initially anticipated. However, while massive and manifold data is continuously produced voluntarily and applications are built for information and knowledge extraction, the initially introduced concept of VGI lacks certain methodological perspectives in this regard which have not been fully elaborated. In this article we highlight and discuss an important gap in this concept, i.e. the lack of formal acknowledgment of temporal aspects. By coining the proposed advanced framework ‘Volunteered Geo‐Dynamic Information’ (VGDI), we attempt to lay the ground for full conceptual and applied spatio‐temporal integration. To illustrate that integrative approach of VGDI and its benefits, we describe the potential impact on the field of dynamic population distribution modeling. While traditional approaches in that domain rely on survey‐based data and statistics as well as static geographic information, the use of VGDI enables a dynamic setup. Foursquare venue and user check‐in data are presented for a test site in Lisbon, Portugal. Two core modules of spatio‐temporal population assessment are thereby addressed, namely time use profiling and target zone characterization, motivated by the potential integration in existing population dynamics frameworks such as the DynaPop model.     

基于云端一体化技术体系的云GIS系统研究

GIS系统因其与生俱来的空间属性,正面临着数据密集、计算密集、高并发、海量时空数据运算等挑战.云计算具有资源池化、弹性伸缩、按需使用等优势,可实现更高性能、更高并发的应用,从而协助解决GIS面临的问题.本文提出了基于云端一体化技术体系的GIS系统架构,包括集约化的GIS云、多样化的GIS端,以及云端互联的GIS系统三个部分.集约化的GIS云平台集成了高性能跨平台、智能集群、并行切图、并行空间分析等技术,可集约利用云计算资源,并提供高效的GIS服务.多样化的GIS端集成桌面、Web移动端技术,可构建跨多端设备的GIS应用.云端互联的一体化系统通过云端一体化、云端协同技术,实现云端之间高效互联、协同工作的GIS应用模式.云端一体化GIS系统致力于让GIS充分利用云计算的优势,应对大数据时代的数据密级、计算密集等挑战.     

Street‐level Spatial Interpolation Using Network‐based IDW and Ordinary Kriging

This study proposes network‐based spatial interpolation methods to help predict unknown spatial values along networks more accurately. It expands on two of the commonly used spatial interpolation methods, IDW (inverse distance weighting) and OK (ordinary kriging), and applies them to analyze spatial data observed on a network. The study first provides the methodological framework, and it then examines the validity of the proposed methods by cross‐validating elevations from two contrasting patterns of street network and comparing the MSEs (Mean Squared Errors) of the predicted values measured with the two proposed network‐based methods and their conventional counterparts. The study suggests that both network‐based IDW and network‐based OK are generally more accurate than their existing counterparts, with network‐based OK constantly outperforming the other methods. The network‐based methods also turn out to be more sensitive to the edge effect, and their performance improves after edge correction. Furthermore, the MSEs of standard OK and network‐based OK improve as more sample locations are used, whereas those of standard IDW and network‐based IDW remain stable regardless of the number of sample locations. The two network‐based methods use a similar set of sample locations, and their performance is inherently affected by the difference in their weight distribution among sample locations.     

Integrated compression of vehicle spatio‐temporal trajectories under the road stroke network constraint

With fast growth of all kinds of trajectory datasets, how to effectively manage the trajectory data of moving objects has received a lot of attention. This study proposes a spatio‐temporal data integrated compression method of vehicle trajectories based on stroke paths coding compression under the road stroke network constraint. The road stroke network is first constructed according to the principle of continuous coherence in Gestalt psychology, and then two types of Huffman tree—a road strokes Huffman tree and a stroke paths Huffman tree—are built, based respectively on the importance function of road strokes and vehicle visiting frequency of stroke paths. After the vehicle trajectories are map matched to the spatial paths in the road network, the Huffman codes of the road strokes and stroke paths are used to compress the trajectory spatial paths. An opening window algorithm is used to simplify the trajectory temporal data depicted on a time–distance polyline by setting the maximum allowable speed difference as the threshold. Through analysis of the relative spatio‐temporal relationship between the preceding and latter feature tracking points, the spatio‐temporal data of the feature tracking points are all converted to binary codes together, accordingly achieving integrated compression of trajectory spatio‐temporal data. A series of comparative experiments between the proposed method and representative state‐of‐the‐art methods are carried out on a real massive taxi trajectory dataset from five aspects, and the experimental results indicate that our method has the highest compression ratio. Meanwhile, this method also has favorable performance in other aspects: compression and decompression time overhead, storage space overhead, and historical dataset training time overhead.     

基于Skyline的机场三维地下管线信息系统开发

为满足机场地下管线的科学化管理,开发三维地下管线信息系统,实现管线三维量测、定位、分析等功能。系统开发采用Skyline三维软件、PostgreSQL数据库和Visual Studio 2010等开发工具和CreatCylinder、CreateModel等接口,设计地下管线GIS系统的技术框架。研究结果表明:系统具有较好的可行性和实用性,功能使用方便,能够满足实际工作需求,对相关GIS系统的建设具有参考价值。     

分布式空间数据库在海量卫星影像管理中的应用

针对现有影像存储方法在海量卫星影像存储中性能不足的问题,分析了现有卫星影像数据存储方法的特点,提出了基于分布式空间数据库管理影像元数据的改进方法。该方法采用文件系统存储影像非结构化的实体数据,影像的空间信息及元数据存储在分布式空间数据库中,实现了海量卫星影像数据的高性能存储,并开展了资源三号卫星影像数据管理试验。试验表明该方法在海量卫星影像数据查询性能方面有显著提高,适用于海量卫星影像数据存储。