共查询到19条相似文献，搜索用时 161 毫秒
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地理空间元数据关联网络的构建 总被引：1，自引：1，他引：0
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。 相似文献
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空间数据立方体的多维数据组织及存储 总被引：1，自引：1，他引：0
邹逸江 《地理与地理信息科学》2006,22(5):26-30
定义空间数据立方体地理空间维、专题维和时间维分别包含的数据种类和内容;设计它们的维和维层次数据结构;表述地理空间维、专题维和时间维在概念层次和物理层次上构成空间数据立方体的方法;确定地理空间维、专题维和时间维数据的多维数组组织方法,以及多维数据的数据文件和虚拟内存存储策略;表达多维数组中记录间的关联运算和多维数组的压缩方法。 相似文献
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为解决多源空间数据语义集成问题,在已有研究成果基础上,提出了基于地理本体的空间数据集成方法。该方法采用局部本体向标准本体集成的策略,在构建具有公共内涵属性模板的地理本体前提下,通过地理概念语义关系集合运算构建局部本体概念与标准本体概念间的语义映射关系,实现地理本体集成,并以这种语义映射关系及概念与对象类的关联关系为媒介,通过空间数据语义细化和空间对象融合 、分割等过程完成空间数据集成。在此基础上,设计开发了基于地理本体的空间数据集成原型系统,并以某土地利用数据为例进行了实证研究,结果表明:基于地理本体的空间数据集成方法能有效集成具有不同语义的空间数据集。 相似文献
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移动GIS中GML数据压缩技术研究 总被引：2，自引：1，他引：1
目前利用GML实现多源异构移动GIS空间数据资源整合时,存在数据压缩的"瓶颈"问题。在分析移动计算环境中GML数据压缩特性(语义同构、时空拓扑特性保持以及自适应网络流量动态调整压缩结构)的基础上,利用语义编码构造整体空间,并通过语义空间聚类与小波变换分析,构建移动GIS中GML数据压缩模型。实验表明:该压缩模型在压缩比、直接读取压缩数据以及在无线网络上传输压缩数据3方面均具有较好的性能,对移动GIS数据共享集成的理论与技术研究具有一定的参考价值。 相似文献
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针对城市建设用地数据的多源异构、多维、复杂度高等特点,探讨基于空间数据仓库理论挖掘城市建设用地潜在的空间信息,提出了面向城市建设用地利用的多维数据模型,并基于该模型构建了以城市建设用地利用为主题的空间数据仓库,实现空间数据挖掘过程.以北京市中心城区的建设用地扩展为例,研究了城市建设用地的空间格局及其演变特征,为城市建设用地管理提供决策依据,同时也为城市建设用地数据的集成、分析和高层决策支持提供了方法论. 相似文献
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航空情报资料是空中交通地理活动所必需或所产生的航空地理数据,在信息化管理过程中面临着多源异构数据的集中管理、统一维护和分布使用等需求。GML作为开放的空间数据模型标准,为航空地理数据的交换和共享提供了要素编码方法和数据交换规范。针对航空信息化系统建设中对规范的航空地理数据的应用需求,在研究航空地理数据特点的基础上,通过分析航空地理数据与GML模型之间的映射关系,以航线管理系统中基础航空情报数据库的建设为例,基于GML规范设计了航空地理数据模型,阐明了数据处理流程,为建立标准化的航空信息数据仓库进行了有益的尝试。 相似文献
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GIS对空间对象及其关系表达能力的增强以及多源数据集成应用的需要,不仅扩大 了城市空间数据的内涵,而且推动了城市空间数据集成研究.城市空间数据涉及多个学科,主要来源于航空遥感与摄影测量、勘探量测、内插推算和社会统计,可分 为地上、地表、地下3个空间层次类型.城市空间数据具有离散非连续、构造约束、零散分 布、信息隐含和体特征等特殊性,并存在多语义、多尺度和实体拓扑特征.城市空间数据具有灰白二象性,地下空间数据可以灰、白相互转化. 相似文献
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多级地理空间网格框架及其关键技术初探 总被引：1，自引：0，他引：1
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。 相似文献
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《地理与地理信息科学》2016,(1)
针对现有地理分析模型同多源复杂地学数据之间耦合困难、模型运算数据处理过程复杂等问题,构建了以模型需求模板匹配为基础的多源地理数据自动处理与推送方法。利用元数据对多源地理数据进行统一描述,并从模型的数据需求和任务需求两个角度生成模型需求模板,最后通过基于XML的元数据与模型需求模板的匹配求得数据操作模板。在数据操作模板中应用算子库作为转换工具,实现了数据库数据到模型需求数据的转换,完成模型运算数据的自动推送。基于江苏沿海滩涂数据库的分析案例表明,该文提出的模型模板匹配方法可对模型运行数据进行有效解析,并通过数据操作流的构建实现数据的自动推送。该研究可为服务型GIS的发展及地理模型的集成提供理论参考与方法借鉴。 相似文献
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Maythm Al-Bakri 《International journal of geographical information science》2013,27(8):1437-1456
One difficulty in integrating geospatial data sets from different sources is variation in feature classification and semantic content of the data. One step towards achieving beneficial semantic interoperability is to assess the semantic similarity among objects that are categorised within data sets. This article focuses on measuring semantic and structural similarities between categories of formal data, such as Ordnance Survey (OS) cartographic data, and volunteered geographic information (VGI), such as that sourced from OpenStreetMap (OSM), with the intention of assessing possible integration. The model involves ‘tokenisation’ to search for common roots of words, and the feature classifications have been modelled as an XML schema labelled rooted tree for hierarchical analysis. The semantic similarity was measured using the WordNet::Similarity package, while the structural similarities between sub-trees of the source and target schemas have also been considered. Along with dictionary and structural matching, the data type of the category itself is a comparison variable. The overall similarity is based on a weighted combination of these three measures. The results reveal that the use of a generic similarity matching system leads to poor agreement between the semantics of OS and OSM data sets. It is concluded that a more rigorous peer-to-peer assessment of VGI data, increasing numbers and transparency of contributors, the initiation of more programs of quality testing and the development of more directed ontologies can improve spatial data integration. 相似文献
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Enrico Steiger Bernd Resch Alexander Zipf 《International journal of geographical information science》2016,30(9):1694-1716
ABSTRACTThe investigation of human activity patterns from location-based social networks like Twitter is an established approach of how to infer relationships and latent information that characterize urban structures. Researchers from various disciplines have performed geospatial analysis on social media data despite the data’s high dimensionality, complexity and heterogeneity. However, user-generated datasets are of multi-scale nature, which results in limited applicability of commonly known geospatial analysis methods. Therefore in this paper, we propose a geographic, hierarchical self-organizing map (Geo-H-SOM) to analyze geospatial, temporal and semantic characteristics of georeferenced tweets. The results of our method, which we validate in a case study, demonstrate the ability to explore, abstract and cluster high-dimensional geospatial and semantic information from crowdsourced data. 相似文献
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J.-P. de Almeida J.G. Morley I.J. Dowman 《International journal of geographical information science》2013,27(8):1514-1529
Interpretation and analysis of urban topology are particularly challenging tasks given the complex spatial pattern of the urban elements, and hence their automation is especially needed. In terms of the urban scene meaning, the starting point in this study is unstructured geospatial data, i.e. no prior knowledge of the geospatial entities is assumed. Translating these data into more meaningful homogeneous regions can be achieved by detecting geographic features within the initial random collection of geospatial objects, and then by grouping them according to their spatial arrangement. The techniques applied to achieve this are those of graph theory applied to urban topology analysis within GIS environment. This article focuses primarily on the implementation and algorithmic design of a methodology to define and make urban topology explicit. Conceptually, such procedure analyses and interprets geospatial object arrangements in terms of the extension of the standard notion of the topological relation of adjacency to that of containment: the so-called ‘containment-first search’. LiDAR data were used as an example scenario for development and test purposes. 相似文献
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Yongyao Jiang Yun Li Kai Liu Edward M. Armstrong Thomas Huang 《International journal of geographical information science》2017,31(11):2310-2328
It is challenging to find relevant data for research and development purposes in the geospatial big data era. One long-standing problem in data discovery is locating, assimilating and utilizing the semantic context for a given query. Most research in the geospatial domain has approached this problem in one of two ways: building a domain-specific ontology manually or discovering automatically, semantic relationships using metadata and machine learning techniques. The former relies on rich expert knowledge but is static, costly and labor intensive, whereas the second is automatic and prone to noise. An emerging trend in information science takes advantage of large-scale user search histories, which are dynamic but subject to user- and crawler-generated noise. Leveraging the benefits of these three approaches and avoiding their weaknesses, a novel methodology is proposed to (1) discover vocabulary-based semantic relationships from user search histories and clickstreams, (2) refine the similarity calculation methods from existing ontologies and (3) integrate the results of ontology, metadata, user search history and clickstream analysis to better determine their semantic relationships. An accuracy assessment by domain experts for the similarity values indicates an 83% overall accuracy for the top 10 related terms over randomly selected sample queries. This research functions as an example for building vocabulary-based semantic relationships for different geographical domains to improve various aspects of data discovery, including the accuracy of the vocabulary relationships of commonly used search terms. 相似文献
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Xiaoping Liu Xingjian Liu He Jin Jinpei Ou Limin Jiao 《International journal of geographical information science》2018,32(4):738-756
To-date few research has successfully integrated big data from multiple sources to characterize urban mixed-use buildings. In this paper, we introduce a probabilistic model to integrate multi-source and geospatial big data (social network data, taxi trajectories, Points of Interest and remote sensing images) to characterize urban mixed-use buildings. The usefulness of our model is demonstrated with a case study of the Tianhe District in megacity Guangzhou, China. The model predicted building functions at 85% accuracy based on ground truth data from field surveys. We further explored the spatial patterns of the identified building functions. Most mixed-use buildings are located along major streets. Our proposed model can identify mixed-use buildings in a city; information is useful for planning evaluation and urban policymaking. 相似文献
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Michael J. Widener Neal C. Crago Jared Aldstadt 《International journal of geographical information science》2013,27(9):1707-1723
As geospatial researchers' access to high-performance computing clusters continues to increase alongside the availability of high-resolution spatial data, it is imperative that techniques are devised to exploit these clusters' ability to quickly process and analyze large amounts of information. This research concentrates on the parallel computation of A Multidirectional Optimal Ecotope-Based Algorithm (AMOEBA). AMOEBA is used to derive spatial weight matrices for spatial autoregressive models and as a method for identifying irregularly shaped spatial clusters. While improvements have been made to the original ‘exhaustive’ algorithm, the resulting ‘constructive’ algorithm can still take a significant amount of time to complete with large datasets. This article outlines a parallel implementation of AMOEBA (the P-AMOEBA) written in Java utilizing the message passing library MPJ Express. In order to account for differing types of spatial grid data, two decomposition methods are developed and tested. The benefits of using the new parallel algorithm are demonstrated on an example dataset. Results show that different decompositions of spatial data affect the computational load balance across multiple processors and that the parallel version of AMOEBA achieves substantially faster runtimes than those reported in related publications. 相似文献
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Javier Lacasta F. Javier Lopez-Pellicer Borja Espejo-García Javier Nogueras-Iso F. Javier Zarazaga-Soria 《International journal of geographical information science》2017,31(8):1583-1605
Geospatial data catalogs enable users to discover and access geographical information. Prevailing solutions are document oriented and fragment the spatial continuum of the geospatial data into independent and disconnected resources described through metadata. Due to this, the complete answer for a query may be scattered across multiple resources, making its discovery and access more difficult. This paper proposes an improved information retrieval process for geospatial data catalogs that aggregates the search results by identifying the implicit spatial/thematic relations between the metadata records of the resources. These aggregations are constructed in such a way that they match better the user query than each resource individually. 相似文献