基于EMD的遥感影像数据组织模型

针对目前遥感数据组织以时间为基准、同一区域不同部门遥感数据标识不统一的现状,鉴于全球剖分网格具有多层次、全球覆盖、网格单元编码全球唯一性和对传统地图图幅的继承性等特点,介绍了基于地图分幅拓展的全球剖分模型EMD,提出以EMD剖分面片为单元、采用剖分面片编码标识并管理遥感数据及其相关资源的数据组织框架.试验分析表明,基于EMD的遥感影像数据组织可行,且基于剖分面片编码的数据检索具有较高效率.     

基于全球剖分模型的空间信息编码模型初探

为解决由于不同GIS数据模型中同一空间实体的编码不惟一而导致数据共享困难及标识的静态性和无空间位置等问题,鉴于全球剖分模型的全球连续性、多层次性以及剖分面片地址码的全球惟一性,该文提出了基于全球剖分模型的全球空间信息剖分编码(GeoDNA)模型,并设计了该编码模型的系统架构,试图实现全球空间信息的全息表达。通过对遥感影像中的空间实体进行编码试验,表明全球空间信息剖分编码模型将大大增强空间信息的维护与共享能力,加快信息的查询与检索速度,在区域性的应急反应上具有很强的理论和实用价值。     

多级地理空间网格框架及其关键技术初探

为了有效管理、组织和利用海量空间数据,解决存储架构与现有空间数据结构不一致的矛盾,在融合国内外各种球面剖分模型优点基础上,设计了一种多级地理空间网格框架。该网格框架以地图分幅划分方式为基础,利用经纬度间隔对全球进行层次性剖分,形成遥感数据、测绘数据及其他空间数据的统一组织框架。通过对网格单元的地址与属性编码,实现空间数据的直接存储和索引,从而完成对空间信息的无缝拼接与多尺度管理。最后阐述了实现地理空间网格框架的关键技术,包括空时一体化技术、计算集群存储技术和空间索引技术等。     

遥感分景数据的剖分索引模型

随着空间技术和对地观测技术的飞速发展,海量遥感影像索引成为目前国内外学术界和应用部门面临的一大难题,地球剖分系统的产生为这一难题的解决开辟了新的途径。本文首先研究了遥感分景数据的特征和EMD全球剖分的特征,然后针对现有遥感影像数据索引方法的不足,提出了基于EMD剖分系统的三种索引模型:基于影像—面片映射关系的索引模型、基于EMD数据模型的索引和剖分数据标识索引模型,从三个不同的方面探讨了解决索引问题的方法和思路。并给出了利用遥感分景数据的剖分索引模型对线状对象和面状对象进行索引应用的实例。遥感分景数据的剖分索引模型的建立为遥感影像数据的高效存储和索引提供了一种有益的新思路。     

全球空间数据剖分模型分析

随着数字地球发展,全球空间信息多尺度表达和管理使得传统平面格网系统的局限性越来越明显,建立全球数据多尺度剖分模型已成为国内外学者关注的热点。该文介绍并分析全球剖分系统,根据剖分单元的形状和最终投影曲面的性质对球面剖分系统进行分类。总结出球面剖分系统具有连续性、稳定性、层次性和近似均匀性等优点,既有效避免了传统平面格网表达全球数据时存在的数据冗余问题,又克服了不规则球面剖分系统无法进行层次关联的缺陷,在管理全球、多层次和海量的空间数据时具有优势。     

基于球体退化八叉树的全球三维网格与变形特征

基于投影的度量空间变换为数字地球及数字区域建设带来了几何裂缝、投影变形等问题,解决问题的根本途径是摒弃投影.直接在球体流形空间建立统一的地球空间基础框架.该文将球面离散网格向球体内部扩展,基于球体退化八叉树提出一种全新的全球三维空间网格剖分方法--球体退化八叉树网格(SDOG).SDOG具有多层次、多分辨率特性,且网格单元面积、体积变形稳定,可对包括地球在内的任意球体进行有序的多层次三维空间剖分,可为全球空间数据集成组织与检索、多层次空间建模与可视化、地球系统科学研究等提供统一的地球空间基础框架.     

地理空间大数据存储管理的地理网络地址研究

针对地理空间数据大数据分布式网络存储管理的地理网络位置搜索问题,从地理网络地址的域名角度,基于2n一维整型数组的全球经纬度剖分格网(GeoSOT)框架提出一种具有地理涵义的空间信息存储网络空间域名地址,即Geonet域名,以统一标识地理空间数据的空间区域位置与计算机存储网络的电子方位,实现用户访问的区域范围、地理空间数据所属地域范围与空间信息存储主机之间的一致性空间关联。     

面向地理对象多尺度表达的剖分编码方法研究

现有模型对影像数据中的地理对象进行多尺度表达很困难,鉴于全球剖分模型在对地理对象表达时所具备的全球唯一性、层次性、多尺度性、编码具有地学含义等特点,提出了面向地理对象多尺度表达的剖分编码方法,目的是对地理对象赋予统一的剖分编码,使编码具有地学含义和多尺度特性.实验证明,面向地理对象多尺度表达的剖分编码方法可以满足地理对象多尺度剖分化表达的需要,为新一代GIS解决地理信息"尺度鸿沟"问题,向用户提供"连续"、"自适应"的表达尺度奠定了基础.     

戈壁分类体系与编目研究

建立统一的戈壁分类和编目体系,是进一步深入研究戈壁的理论基础,也是合理开发利用戈壁资源的前提。到目前为止,只有少量文献或著作提到戈壁或戈壁类型,关于戈壁编目的研究更鲜有报道。为了促进戈壁研究的规范化,本文在参照现有戈壁分类基础上,结合戈壁科学考察成果,根据戈壁的形成原因、地表物质组成与植被类型,分三级建立了戈壁分类体系,并对每一级每一类的戈壁特征进行了较为详细的阐述。在戈壁分类基础上,提出戈壁编目设想,以期为进一步深入开展戈壁研究奠定基础。     

基于GeoSOT编码的多元灾害数据一体化组织管理方法研究

灾害信息数据来源广、格式复杂、关联性差、存储管理难度大,亟须建立一种多元灾害数据一体化组织管理方法.该文采用目前相对成熟的GeoSOT全球剖分网格模型,提出了基于“空间面片”统一组织管理多元灾害信息数据的方法.该方法对GeoSOT模型进行了两方面改进:1)根据灾害信息数据的空间属性特点采用21级剖分方案建立“空间面片”;2)直接使用数字对“空间面片”进行编码.为解决海量、多元灾害信息数据的快速查询检索问题,设计了“两次检索”的技术方案:第一次检索使用一维剖分格网编码代替传统的二维经纬度,提高了检索速度;第二次检索使用经纬度,剔除所选范围之外数据,提高了数据检索精度.采用World Wind数字地球开发了一个C/S架构的多元灾害数据一体化管理实验系统,以HJ1A/1B多光谱数据、GLCF影像产品数据和灾情统计报表数据为例,对该方法验证的结果表明,其能够有效地组织管理多元灾害信息数据,并实现对数据的快速查询检索,满足减灾救灾数据管理的业务需求.     

Framework for probabilistic geospatial ontologies

Partial knowledge about geospatial categories is important for practical use of ontologies in the geospatial domain. Degree of overlaps between geospatial categories, especially those based on geospatial actions concepts and geospatial enitity concepts, need to be specified in ontologies. Conventional geospatial ontologies do not enable specification of such information, and this presents difficulties in ontology reasoning for practical purposes. We present a framework to encode probabilistic information in geospatial ontologies based on the BayesOWL approach. The approach enables rich inferences such as most similar concepts within and across ontologies. This paper presents two case studies of using road‐network ontologies to demonstrate the framework for probabilistic geospatial ontologies. Besides inferences within the probabilistic ontologies, we discuss inferences about most similar concepts across ontologies based on the assumption that geospatial action concepts are invariable. The results of such machine‐based mappings of most similar concepts are verified with mappings of concepts extracted from human subjects testing. The practical uses of probabilistic geospatial ontologies for concept matching and measuring naming heterogeneities between two ontologies are discussed. Based on our experiments, we propose such a framework for probabilistic geospatial ontologies as an advancement of the proposal to develop semantic reference systems.     

Building the distributed geographic SQL workflow in the Grid environment

Over recent years, massive geospatial information has been produced at a prodigious rate, and is usually geographically distributed across the Internet. Grid computing, as a recent development in the landscape of distributed computing, is deemed as a good solution for distributed geospatial data management and manipulation. Thus, the Grid computing technology can be applied to integrate various distributed resources into a ‘super-computer’ that enables efficient distributed geospatial query processing. In order to realize this vision, an effective mechanism for building the distributed geospatial query workflow in the Grid environment needs to be elaborately designed. The workflow-building technology aims to automatically transform the global geospatial query into an equivalent distributed query process in the Grid. In response to this goal, detailed steps and algorithms for building the distributed geospatial query workflow in the Grid environment are discussed in this article. Moreover, we develop corresponding software tools that enable Grid-based geospatial queries to be run against multiple data resources. Experimental results demonstrate that the proposed methodology is feasible and correct.     

地理空间元数据关联网络的构建

利用资源描述框架（RDF）设计地理空间元数据关联模型,根据地理空间元数据之间的语义关系和语义相关度的计算,以构建以元数据为节点、元数据之间的语义关系为边、语义相关度为权重的关联网络。在这一网络中,一个节点是一个地理空间元数据的资源描述图,包含属性特征（数据来源、空间特征、时间特征、内容）及其关系特征（元数据之间的语义关系、语义相关度）。实验及其分析表明,地理空间元数据关联网络可以有效地支持地理空间数据语义关联检索、推荐等应用,这与传统的基于关键词的元数据检索方式相比,具有更高的准确度。     

Reply to Comment on ‘Marine GIS: Identification of mesoscale oceanic thermal fronts’

Geographic information service (GIService) has become popular in the last decade to develop applications for addressing global challenges. Performance is one of the most important criteria to help users select distributed online GIService for developing geospatial applications including natural hazards and emergency responses. However, performance accuracy is limited by the single-location-based evaluation mechanism while service performance is dynamic in space and time between end-users and services. We propose a spatiotemporal performance evaluation mechanism to improve the accuracy. Specially, a cloud and volunteer computing mechanism is proposed to collect performance information of globally distributed GIServices. A global spatiotemporal performance model is designed to integrate spatiotemporal dynamics for better performance evaluation for users from different regions at different times. This model is tested to support GIService selection in global spatial data infrastructures (SDIs). The experiment confirms that the proposed model provides more accurate evaluations for global users and better supports geospatial resource utilizations in SDIs than previous mechanisms. The methodology can be adopted to improve the services of other regional and global distributed operational systems.     

地理信息技术应用下的无人机云端管理系统发展

日益增长的无人机飞行需求与有限的低空空域之间的矛盾愈发激烈,世界各国都在推进无人机管控政策和技术手段研究,即便在最自由的美国G类非管制空域,管理当局也在制定更为严格的无人机管控措施。无人机云端管理系统作为一种新型的数字化监管手段,其系统建设框架和技术路线得到了国内外学者和监管部门的广泛关注与研究。地理信息技术作为云端管理系统的应用技术之一,具体体现在以下几方面:利用全球导航卫星系统(GNSS)实现无人机精准空间定位;通过遥感技术(RS)获取影响无人机飞行安全的地理约束要素信息;基于地理信息系统(GIS)对低空地理空间数据进行组织管理以及构建低空虚拟地理环境等。论文结合团队在无人机低空应用上的研究进展,指出地理信息技术可以在云端管理和航路规划方面为无人机运行管理提供解决方案。     

Use of Geospatial Data and Technology for Wilderness Search and Rescue by Nonprofit Organizations

Geospatial data and tools are key in locating lost or missing persons in as short a time as possible. In this study, we used a geographic information system (GIS) to analyze four years of search and rescue (SAR) mission data from Colorado to determine the appropriate use of GIS for volunteer-based SAR organizations with limited resources and GIS expertise. GIS can provide more sophisticated analyses of geospatial data than simple mapping technologies, but our findings indicated that complex spatial analysis might not be required on all missions, because the majority of missions were completed within six to ten hours. Instead, new technologies such as tablets with mapping software and online GIS systems that provide quick and easy access to up-to-date geospatial data such as imagery offer capabilities that could improve mission planning. Here we provide a framework in which SAR missions can apply geospatial technologies to aid with missions, identify critical “hotspots,” and enhance postanalysis and training. The work here is highly applicable for nonprofit SAR groups when deciding on what GIS technologies to consider for their areas.     

Synchronising geometric representations for map mashups using relative positioning and Linked Data

Map mashups, as a common way of presenting geospatial information on the Web, are generally created by spatially overlaying thematic information on top of various base maps. This simple overlay approach often raises geometric deficiencies due to geometric uncertainties in the data. This issue is particularly apparent in a multi-scale context because the thematic data seldom have synchronised level of detail with the base map. In this study, we propose, develop, implement and evaluate a relative positioning approach based on shared geometries and relative coordinates to synchronise geometric representations for map mashups through several scales. To realise the relative positioning between datasets, we adopt a Linked Data–based technical framework in which the data are organised according to ontologies that are designed based on the GeoSPARQL vocabulary. A prototype system is developed to demonstrate the feasibility and usability of the relative positioning approach. The results show that the approach synchronises and integrates the geometries of thematic data and the base map effectively, and the thematic data are automatically tailored for multi-scale visualisation. The proposed framework can be used as a new way of modelling geospatial data on the Web, with merits in terms of both data visualisation and querying.     

Mapping fine-scale population distributions at the building level by integrating multisource geospatial big data

Fine-scale population distribution data at the building level play an essential role in numerous fields, for example urban planning and disaster prevention. The rapid technological development of remote sensing (RS) and geographical information system (GIS) in recent decades has benefited numerous population distribution mapping studies. However, most of these studies focused on global population and environmental changes; few considered fine-scale population mapping at the local scale, largely because of a lack of reliable data and models. As geospatial big data booms, Internet-collected volunteered geographic information (VGI) can now be used to solve this problem. This article establishes a novel framework to map urban population distributions at the building scale by integrating multisource geospatial big data, which is essential for the fine-scale mapping of population distributions. First, Baidu points-of-interest (POIs) and real-time Tencent user densities (RTUD) are analyzed by using a random forest algorithm to down-scale the street-level population distribution to the grid level. Then, we design an effective iterative building-population gravity model to map population distributions at the building level. Meanwhile, we introduce a densely inhabited index (DII), generated by the proposed gravity model, which can be used to estimate the degree of residential crowding. According to a comparison with official community-level census data and the results of previous population mapping methods, our method exhibits the best accuracy (Pearson R = .8615, RMSE = 663.3250, p < .0001). The produced fine-scale population map can offer a more thorough understanding of inner city population distributions, which can thus help policy makers optimize the allocation of resources.