论地球数据科学与共享

地球科学大数据的到来,迫切需要通过地球数据科学系统对地学数据机理、采集处理、存储管理,特别是集成共享与挖掘分析等进行研究,以便通过大数据资源,发现和揭示数据背后隐含的地学规律和知识,促进地学科技创新。本文首先分析了地球数据科学的内涵特征,提出了地球数据科学的基础理论方法和技术体系。然后基于国家地球系统科学数据共享实践,重点研究了大数据时代下,面向地球数据科学的地学数据共享新发展。     

基于XML Schema地球系统科学数据的元数据扩展机制

概述目前国内外地学数据共享中元数据的应用,分析地球系统科学数据的学科特点:数据量大、学科复杂、元数据标准多,从而论证在地球系统科学数据共享网的开发和研究中元数据扩展的必要性,论述元数据扩展的基本方法、抽象模型和基本原则,总结地球系统科学数据共享网核心元数据的多学科扩展表达,最后,论述地球系统科学数据共享网中元数据扩展机制的实现,以及利用XML Schema文档的可扩展性,阐述基于XML Schema地球系统科学数据的元数据扩展机制,实现地球系统科学数据元数据的多学科扩展.     

地球观测数据共享的发展和趋势

地球观测数据共享是地球科学和相关学科科研活动中非常重要的基础性工作,是对地观测信息生命周期中的重要环节。受到由资源提供者、资源消费者和资源加工者组成的社会生态系统发展变化的影响,共享模式经历了无共享、项目共享、部门共享、社会共享等渐进的4个发展阶段,并呈现出区域差异和阶段差异。地球观测数据共享的概念体系包含数据开放、数据共享、数据互联等不同层次的问题,并受到信息技术等使能技术的驱动。其中开放性代表数据在网络中可被访问的状态,共享性是对于数据重复使用的授权和模式,互联性则是强调可共享数据资源在科学含义上的相互理解。而地球观测数据共享的技术体系则包含数据开放技术、数据共享技术和数据出版与引用技术。目前地球观测领域的数据共享正在经历巨大的文化、政策、技术和应用变革,下一代的地球观测数据设施集中体现了数据的共享和协作,并将呈现国际化、多学科化、标准化、设施化、大数据化和公众社会化等新的技术特征,将对相关科学活动产生重大影响。     

基于元数据的科学数据汇交研究

科学数据共享过程中如何把国家设立的科学技术研究项目的数据汇交上来,形成数据仓库,是实现科学数据共享的前提。本文根据国内科学数据的调研结果,提出了科学数据汇交系统的总体框架和科学数据汇交平台的设计,详细阐述了数据汇交过程中的工作流程和技术流程,初步设计了汇交网络体系的结构和功能。     

WDC中国地质科学数据网

地质科学数据是人类合理开发利用地球资源、保护人类赖以生存的地球环境,推进地球系统科学知识创新的重要基础数据。本文简要介绍中国地质科学院主持建设的WDC2中国地质科学数据网的有关情况,着重介绍地质数据库资源及共享服务系统的基本构架,旨在为促进地质科学数据共享建设提供参考借鉴。     

TEQC软件用于GPS控制网数据质量检测的研究

在分析影响GPS观测数据质量和GAMIT/GLOBK数据处理质量评价标准的基础七,通过TEQC数据质量检测软件和基线解算质量控制指标,研究三级GPS大地控制网数据质量的检测方法,并以三级GPS大地控制网观测数据为例对观测数据进行检测和评定.     

基于Sentinel-2A的耕地质量综合评价

本研究以Sentinel-2A数据为基础,构建基于多光谱遥感影像和地球化学数据的耕地质量指标体系和评价模型,对海伦地区耕地质量进行综合评价。在分析土壤肥力、土壤水分、土壤退化与植被指数的相关性的基础上,确定了基于Sentinel-2A的遥感评价指标,并基于营养元素与重金属含量构建地球化学指标,并将两项指标进行结合形成P-S-R框架体系。在该指标体系下,采用层次分析法构建了耕地质量综合评价模型,创新性实现了通过遥感手段结合少量地球化学数据完成对耕地质量进行评价。利用土壤样本实测点对模型进行验证,结果表明评价模型获取的耕地质量评价结果与研究区实际情况比对精度达到75%,结果表明海伦地区耕地质量整体较好。该方法相比采用传统的地球化学评价土地质量的方法更加方便和快捷,对于大范围耕地的可持续利用提供有效的技术支撑和重要的现实意义。     

三级GPS大地控制网中GPS观测数据质量检测方法研究

本文在分析影响GPS观测数据质量和GAMIT／GLOBK数据处理质量评价标准的基础上，介绍了TEQC数据质量检测软件和基线解算质量控制指标，探讨了三级GPS大地控制网数据质量的检测方法，并对实测数据进行了检测和评定。实践表明，该检测方法是有效和切实可行的。     

国土资源科学数据共享研究综述

针对当前在长期的国土资源调查、监测、评价、研究工作中所产生的大量国土资源科学数据,分析这些获取难度大、成本高,有着巨大的科学利用价值的数据资源未能充分发挥其科学价值的主要原因,阐述开展国土资源科学数据共享的重要性,并围绕制约国土资源科学数据共享的关键技术问题,综述国土资源科学数据标准化改造、共享平台功能搭建、数据标准规范建设等方面的进展和共享服务情况,提出国土资源科学数据共享今后的主要研究方向。     

OpenStreetMap路网数据的几何精度评价

针对目前关于OSM数据质量的研究现状,本文以美国地质勘查局数据为参考数据,根据OSM路网数据与参考数据的特点,完成OSM路网数据的转换及其与参考数据的匹配。同时依据匹配结果,给出OSM路网的距离、角度这两种几何精度的评价结果,并通过计算机编程,将最终的评价结果可视化,开发实现了众源数据质量评价原型系统。     

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.     

A new trapezoidal-mesh based data model for spatial operations

This paper presents a new spatial data model based on trapezoidal-mesh for implementing spatial operations within geographical information systems (GIS). Based only on the solid foundation of spatial operations, diversified application models can be established to bridge the gap between Digital Earth models and the real world with its real-world problems (‘connecting through location’). In this paper, the involved polygon features are decomposed into a series of trapezoidal-meshes. Then, geo-processing operations are employed on these meshes rather than the original polygon features, resulting in a relatively simple spatial computation. As a kind of model designed by integrating raster with vector, the model presented here has advantages over other models when carrying out spatial operations insofar as providing a solid foundation for achieving the grand goal of Digital Earth. The concept of this data model and the two extensive examples of its application in spatial operations are elaborated upon in this article. As a result, this article and the research that supports it, proves that the adoption of the trapezoidal-mesh model greatly improves the efficiency of spatial operations in GIS.     

用于空间分析的栅格中间层构建流程与方法研究

从构建能直接用于空间分析及辅助决策的栅格中间层数据入手,将其划分为地形基础因子、地形特征、专题应用栅格中间层,用层层递进的栅格中间层数据驱动空间分析全流程,并依据影响因素确定性与否,提出二值化与模糊综合评判分析方法,进而形成栅格中间层支持的空间分析解决方案,以期为地理空间辅助决策提供更加完备的数据支持,减少空间分析处理的技术难度,实现从数据到知识的转化,提高空间分析辅助决策的质量和效率。     

面向规划的城市空间数据质量检查

在空间数据质量分析的基础上,介绍了空间数据质量检查系统设计原则,各个质量指标内容及其评价方法,并对成果输出内容进行介绍.此研究内容与方法在广州空间数据检查系统中成功实现、应用,软件实际应用结果表明,论述方法正确,检验结果可靠.     

A design of three-dimensional spatial data model and its data structure in geological exploration engineering

The key to develop 3-D GISs is the study on 3-D data model and data structure. Some of the data models and data structures have been presented by scholars. Because of the complexity of 3-D spatial phenomenon, there are no perfect data structures that can describe all spatial entities. Every data structure has its own advantages and disadvantages. It is difficult to design a single data structure to meet different needs. The important subject in the 3-D data models is developing a data model that has integrated vector and raster data structures. A special 3-D spatial data model based on distributing features of spatial entities should be designed. We took the geological exploration engineering as the research background and designed an integrated data model whose data structures integrats vector and raster data by adopting object-oriented technique. Research achievements are presented in this paper.     

A design of three-dimensional spatial data model and its data structure in geological exploration engineering

The key to develop 3-D GISs is the study on 3-D data model and data structure. Some of the data models and data structures have been presented by scholars. Because of the complexity of 3-D spatial phenomenon, there are no perfect data structures that can describe all spatial entities. Every data structure has its own advantages and disadvantages. It is difficult to design a single data structure to meet different needs. The important subject in the3-D data models is developing a data model that has integrated vector and raster data structures. A special 3-D spatial data model based on distributing features of spatial entities should be designed. We took the geological exploration engineering as the research background and designed an integrated data model whose data structures integrats vector and raster data byadopting object-oriented technique. Research achievements are presented in this paper.     

A hierarchical indexing strategy for optimizing Apache Spark with HDFS to efficiently query big geospatial raster data

ABSTRACT

Earth observations and model simulations are generating big multidimensional array-based raster data. However, it is difficult to efficiently query these big raster data due to the inconsistency among the geospatial raster data model, distributed physical data storage model, and the data pipeline in distributed computing frameworks. To efficiently process big geospatial data, this paper proposes a three-layer hierarchical indexing strategy to optimize Apache Spark with Hadoop Distributed File System (HDFS) from the following aspects: (1) improve I/O efficiency by adopting the chunking data structure; (2) keep the workload balance and high data locality by building the global index (k-d tree); (3) enable Spark and HDFS to natively support geospatial raster data formats (e.g., HDF4, NetCDF4, GeoTiff) by building the local index (hash table); (4) index the in-memory data to further improve geospatial data queries; (5) develop a data repartition strategy to tune the query parallelism while keeping high data locality. The above strategies are implemented by developing the customized RDDs, and evaluated by comparing the performance with that of Spark SQL and SciSpark. The proposed indexing strategy can be applied to other distributed frameworks or cloud-based computing systems to natively support big geospatial data query with high efficiency.     

一种基于空间网格的地物要素点云提取方法

LiDAR点云的分类提取是点云数据处理中的首要步骤。为了提高复杂场景中点云数据分类提取方法的适用性,文中根据三维数学形态学思想,提出一种基于地物空间形状特征的点云提取方法。方法首先建立网格索引,划分网格空间,进行点云数据组织,然后根据地物在网格空间中的形状特征设计出四种参数可控的空间网格算子,最后结合点云反射强度信息自动提取特定地物点云。通过对复杂场景中的铁路地物要素LiDAR点云中建筑、电力杆线、铁路轨道的提取和郊区机载LiDAR点云中的地面与建筑屋顶的提取,验证提取算法的适用性,为点云分类提取功能模块的程序设计提供便捷方法。     

多尺度空间数据索引方法研究

以多尺度空间数据为研究对象,讨论其混合索引结构的建立方法。对于多尺度矢量空间数据提出基于多层次网格与R 树混合索引结构,栅格数据进行分块并建立四叉树索引结构。利用双向链表结构连接同尺度下的矢栅空间数据,实现矢栅之间的无缝转化;并用地理数据编码及双向链表结构连接不同尺度下的同一空间对象,实现多尺度空间对象的纵向无缝连接。进而实现多尺度空间数据的快速可视化及空间对象的纵向无缝查询。