A Methodological Framework for Researching the Usability of the Space-Time Cube

Abstract

In recent years, an increased interest in the use of the Space-Time Cube (STC) to visualize movement data can be witnessed. However, little is known about whether the cube is truly efficient and effective to satisfactorily display complex movement datasets. The limited usability research that has been done did not lead to details on how the STC content should be designed and whether the cartographic design influences the exploration process. The conceptual framework that is proposed in this paper offers an approach to the evaluation of the STC content with special attention for design aspects and the environment in which the STC has to function. Systematic usability studies have to identify the strengths and weaknesses of the STC under different conditions. Therefore, the framework contains phased studies in which real-world data of four use cases of different complexity are used.     

Bringing GEOSS Services into Practice: A Capacity Building Resource on Spatial Data Infrastructures (SDI)

Data discoverability, accessibility, and integration are frequent barriers for scientists and a major obstacle for favorable results on environmental research. To tackle this issue, the Group on Earth Observations (GEO) is leading the development of the Global Earth Observation System of Systems (GEOSS), a voluntary effort that connects Earth Observation resources world‐wide, acting as a gateway between producers and users of environmental data. GEO recognizes the importance of capacity building and education to reach large adoption, acceptance and commitment on data sharing principles to increase the capacity to access and use Earth Observations data. This article presents “Bringing GEOSS services into practice” (BGSIP), an integrated set of teaching material and software to facilitate the publication and use of environmental data through standardized discovery, view, download, and processing services, further facilitating the registration of data into GEOSS. So far, 520 participants in 10 countries have been trained using this material, leading to numerous Spatial Data Infrastructure implementations and 1,000 tutorial downloads. This workshop lowers the entry barriers for both data providers and users, facilitates the development of technical skills, and empowers people.     

Rapid,high-resolution detection of environmental change over continental scales from satellite data – the Earth Observation Data Cube

The effort and cost required to convert satellite Earth Observation (EO) data into meaningful geophysical variables has prevented the systematic analysis of all available observations. To overcome these problems, we utilise an integrated High Performance Computing and Data environment to rapidly process, restructure and analyse the Australian Landsat data archive. In this approach, the EO data are assigned to a common grid framework that spans the full geospatial and temporal extent of the observations – the EO Data Cube. This approach is pixel-based and incorporates geometric and spectral calibration and quality assurance of each Earth surface reflectance measurement. We demonstrate the utility of the approach with rapid time-series mapping of surface water across the entire Australian continent using 27 years of continuous, 25?m resolution observations. Our preliminary analysis of the Landsat archive shows how the EO Data Cube can effectively liberate high-resolution EO data from their complex sensor-specific data structures and revolutionise our ability to measure environmental change.     

Integrating Environmental Models with GIS: An Object-oriented Approach Utilising a Hierarchical Data Format (HDF) Data Repository

Conceptual, as well as operational, aspects need to be taken into account when developing an integrated modelling framework. A set of achievable requirements has been identified which are used to realise a solution that is applied to the modelling of ephemeral flood channels. The solution described provides: (1) a common data repository within which all model run details, scientific data sets and output results reside; (2) the ability to interactively visualise and select suitable data sets from the data repository to configure the model; (3) an interface for mediating the flow of information between model and other applications; and (4) the possibility to allow model functionality and associated data to be made available to the wider scientific community. This is achieved using an object-oriented approach within the Research System Inc. Interactive Data Language (IDL) and the adoption of National Center for Supercomputer Application's HDF as a common file format for modelling scenarios. The paper outlines the development of a class library, EM_HDF, for mediating and facilitating data exchange between the model and its HDF data repository. The developed system is designed to be applicable to a wide range of modelling applications beyond the fluvial model described.     

Multidimensional and quantitative interlinking approach for Linked Geospatial Data

ABSTRACT

Linked Data is known as one of the best solutions for multisource and heterogeneous web data integration and discovery in this era of Big Data. However, data interlinking, which is the most valuable contribution of Linked Data, remains incomplete and inaccurate. This study proposes a multidimensional and quantitative interlinking approach for Linked Data in the geospatial domain. According to the characteristics and roles of geospatial data in data discovery, eight elementary data characteristics are adopted as data interlinking types. These elementary characteristics are further combined to form compound and overall data interlinking types. Each data interlinking type possesses one specific predicate to indicate the actual relationship of Linked Data and uses data similarity to represent the correlation degree quantitatively. Therefore, geospatial data interlinking can be expressed by a directed edge associated with a relation predicate and a similarity value. The approach transforms existing simple and qualitative geospatial data interlinking into complete and quantitative interlinking and promotes the establishment of high-quality and trusted Linked Geospatial Data. The approach is applied to build data intra-links in the Chinese National Earth System Scientific Data Sharing Network (NSTI-GEO) and data -links in NSTI-GEO with the Chinese Meteorological Data Network and National Population and Health Scientific Data Sharing Platform.     

基于双效机制的时空数据模型研究

地理特征对象是时空数据组织的基本单元,而事件是导致时空数据发生变化的根本原因。在分析、借鉴前人的时空数据管理方法的基础上,通过分析事件驱动的特征对象数据存储与管理机制,提出了一种基于特征和事件双效机制的TG IS时空数据模型。同时结合土地利用的时空数据特点,设计了基于该模型的时空数据的快速索引机制和时空数据库。实际运行表明基于该模型的TG IS系统设计方案能高效、快速、全面地实现时空数据的存储、管理和分析。     

Oracle数据库空间数据插件技术初探

从基本概念，数据模型，应用功能等方面介绍了空间数据插件技术。     

数据挖掘和知识发现的技术方法

数据挖掘是指从数据库中提取出隐含的、先前不知道的有用知识的过程。本文从数据挖掘和知识发现的概念出发 ,总结了数据挖掘常采用的技术方法 ,并从数据挖掘采用的技术方法的角度对数据挖掘进行分类 ,指出每种技术适合挖掘出哪些知识 ,比较每种技术的优缺点 ,同时还对几个数据挖掘的应用进行了阐述。     

Big Data and cloud computing: innovation opportunities and challenges

ABSTRACT

Big Data has emerged in the past few years as a new paradigm providing abundant data and opportunities to improve and/or enable research and decision-support applications with unprecedented value for digital earth applications including business, sciences and engineering. At the same time, Big Data presents challenges for digital earth to store, transport, process, mine and serve the data. Cloud computing provides fundamental support to address the challenges with shared computing resources including computing, storage, networking and analytical software; the application of these resources has fostered impressive Big Data advancements. This paper surveys the two frontiers – Big Data and cloud computing – and reviews the advantages and consequences of utilizing cloud computing to tackling Big Data in the digital earth and relevant science domains. From the aspects of a general introduction, sources, challenges, technology status and research opportunities, the following observations are offered: (i) cloud computing and Big Data enable science discoveries and application developments; (ii) cloud computing provides major solutions for Big Data; (iii) Big Data, spatiotemporal thinking and various application domains drive the advancement of cloud computing and relevant technologies with new requirements; (iv) intrinsic spatiotemporal principles of Big Data and geospatial sciences provide the source for finding technical and theoretical solutions to optimize cloud computing and processing Big Data; (v) open availability of Big Data and processing capability pose social challenges of geospatial significance and (vi) a weave of innovations is transforming Big Data into geospatial research, engineering and business values. This review introduces future innovations and a research agenda for cloud computing supporting the transformation of the volume, velocity, variety and veracity into values of Big Data for local to global digital earth science and applications.     

Deeply integrating Linked Data with Geographic Information Systems

The realization that knowledge often forms a densely interconnected graph has fueled the development of graph databases, Web‐scale knowledge graphs and query languages for them, novel visualization and query paradigms, as well as new machine learning methods tailored to graphs as data structures. One such example is the densely connected and global Linked Data cloud that contains billions of statements about numerous domains, including life science and geography. While Linked Data has found its way into everyday applications such as search engines and question answering systems, there is a growing disconnect between the classical ways in which Geographic Information Systems (GIS) are still used today and the open‐ended, exploratory approaches used to retrieve and consume data from knowledge graphs such as Linked Data. In this work, we conceptualize and prototypically implement a Linked Data connector framework as a set of toolboxes for Esri's ArcGIS to close this gap and enable the retrieval, integration, and analysis of Linked Data from within GIS. We discuss how to connect to Linked Data endpoints, how to use ontologies to probe data and derive appropriate GIS representations on the fly, how to make use of reasoning, how to derive data that are ready for spatial analysis out of RDF triples, and, most importantly, how to utilize the link structure of Linked Data to enable analysis. The proposed Linked Data connector framework can also be regarded as the first step toward a guided geographic question answering system over geographic knowledge graphs.     

服务于PDA的矢量数据分块存储数据结构的研究

数据结构、数据模型是GIS领域中一个比较重要的研究方向，目前GIS中较成熟的数据结构均是针对个人PC机或工作站硬件环境，并不适合以掌上电脑为平台的移动GIS系统。针对以掌上电脑为代表的智能移动终端，提出了一种矢量数据分块数据结构模型。该数据结构适用于以PDA智能终端为硬件平台的移动GIS系统，是实现矢量图形数据存储与快速显示的技术关键。     

VGI数据与地形图数据的自动融合研究

随着科学技术的不断发展,志愿者地理信息（volunteered geographic information,VGI）已经成为地理空间数据中最为重要的来源之一。为了充分利用志愿者地理信息,需要进行VGI与传统地形图数据的匹配与融合。开发了一种全新的数据自动匹配与融合算法,其目的是将ATKIS道路网数据（由德国联邦测绘局所采集的官方数据）与AOSD数据（由大量志愿者携带定位仪器进行户外徒步或骑行所获取的轨迹数据）匹配并融合起来,从而丰富传统地理信息数据的内容,并实现数据的增值。考虑到ATKIS数据与AOSD数据在空间表达上的差异很大,所开发的算法包括了道路要素的智能化分割、道路要素匹配、道路网数据融合以及融合后道路网内部要素间的匹配运算与数据集成等4个过程。大量实地数据的测试结果表明,该算法具有匹配成功率高、准确率高、运算速度快等优点。     

基于机载LiDAR数据的等高线制作流程研究

LiDAR数据获取快、精度高,具有传统摄影测量方法和常规测量技术无法比拟的优越性,为等高线的获取提供了新的思路,在测绘行业越来越受到关注。本文通过生产实践,解决了平原地区生成等高线的瓶颈,提出了一个基于机载LiDAR数据制作等高线的标准化流程,并重点介绍了相关的细节处理。     

一种适应图像特征的数据加密方法

数据加密是信息科学中一个重要问题 ,它对于知识产权的保护、防止机密数据外流及情报的安全传递都有很重要的现实意义。文中提出一种利用图像携带加密数据的技术 ,将需要加密的数据隐藏到一幅图像文件中 ,而对宿主文件的效果影响甚微 ,并采用两种数据筛方法 ,即利用图像特征数据筛保持携密图像的带密位仍具有原始图像的特征 ,利用随机数筛消除加密数据的特征 ,从而有效地防止这类图像被识别与解密 ,为私有信息的存储与传递提供安全保障。     

A Lightweight Approach for the Sensor Observation Service to Share Environmental Data across Europe

The importance of near real‐time access to environmental data has increased steadily over the last few years. In this article, the focus is on the European Environment Agency (EEA), which receives environmental data from a large number of providers. The heterogeneous data formats and data transfer mechanisms make the data collection and integration a difficult task for the EEA. An approach is needed for facilitating the interoperable exchange of environmental data on a large scale. A core element of this approach is the Sensor WebEnablement (SWE) technology of the Open Geospatial Consortium (OGC) which allows the standardized, interoperable, vendor and domain independent exchange of sensor data. The main contribution of this article is a lightweight profile for the OGC Sensor Observation Service that ensures the necessary interoperability for seamlessly integrating the environmental data provided by the EEA's member states and thus forms the foundation for the developed data exchange mechanisms. This is complemented by information about the resulting Sensor Web architecture and the integration into the EEA's existing IT infrastructure. In summary, this article describes a practical scenario in which SWE technology enables the exchange of near real‐time environmental data on a large scale.     

空间数据仓库的技术与实践

空间数据仓库（Ｓｐａｔｉａｌ Ｄａｔａ Ｗａｒｅｈｏｕｓｅ）是ＧＩＳ技术和数据仓库技术相结合的产物,它大大扩展了ＧＩＳ的应用功能,为逐渐兴起的全球变化和区域持续发展研究以及复杂的商业地理分析提供强有力的支持。该文主要从空间数据仓库的起源、特征、体系结构、关键技术与应用等方面来探讨空间数据仓库这一全新的ＧＩＳ应用。     

A New Method to Correct Pushbroom Hyperspectral Data Using Linear Features and Ground Control Points

Data acquired using aerial pushbroom scanners often contain aircraft motion errors—especially aircraft roll error. This article describes a new algorithm to correct roll errors using both ground control points and linear features digitized on a reference map and the uncorrected image. The algorithm is different from previous methods used to correct aerial pushbroom data because it does not solely rely on a single or multiple straight lines. Rather, it is able to integrate both points and lines together to correct the error. With an associated loss of precision, it can also use points or lines separately. The method is tested on a hyperspectral dataset acquired in the Range Creek, Utah area during June 2009. It was found that the approach is an effective way to remove aircraft roll errors and prepare the image for additional georegistration. A program with a graphical user interface has been written using the algorithm and is available on the project's website.     

新型基础测绘数据生产与应用一体化实践

测绘发展经历了模拟测绘、数字化测绘和信息化测绘发展阶段,随着物联网、大数据、移动互联网等空间技术和信息技术的不断进步,测绘技术也逐渐由靠人工内、外业采集的传统测绘,发展到今天的使用卫星导航定位、无人机、物联网、大数据等先进技术手段的智能化测绘.本文从呼和浩特市智慧空间地理信息数据库的建设与应用入手,探索智慧城市建设中新型基础测绘数据生产与成果应用一体化的管理实践.     

基于空间方向相似性的面状矢量空间数据匹配算法

数据一致性匹配处理技术是空间数据融合中的关键技术。采用方向关系矩阵模型进行空间方向关系描述,讨论了一般情况下的空间方向相似性计算,提出了基于空间方向相似性的矢量数据匹配算法流程。最后,以面状目标为研究对象,以某地局部地区居民地数据为例,对基于空间方向相似性的矢量数据匹配算法进行了试验与分析。