Multidimensional indexing tools for the virtual observatory

The last decade has seen a dramatic change in the way astronomy is carried out. The dawn of the the new microelectronic devices, like CCDs has dramatically extended the amount of observed data. Large, in some cases all sky surveys emerged in almost all the wavelength ranges of the observable spectrum of electromagnetic waves. This large amount of data has to be organized, published electronically and a new style of data retrieval is essential to exploit all the hidden information in the multiwavelength data. Many statistical algorithms required for these tasks run reasonably fast when using small sets of in‐memory data, but take noticeable performance hits when operating on large databases that do not fit into memory. We utilize new software technologies to develop and evaluate fast multidimensional indexing schemes that inherently follow the underlying, highly non‐uniform distribution of the data: they are layered uniform indices, hierarchical binary space partitioning, and sampled flat Voronoi tessellation of the data. These techniques can dramatically speed up operations such as finding similar objects by example, classifying objects or comparing extensive simulation sets with observations. (© 2007 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Random forest algorithm for classification of multiwavelength data

We introduced a decision tree method called Random Forests for multiwavelength data classification. The data were adopted from different databases, including the Sloan Digital Sky Survey (SDSS) Data Release five, USNO, FIRST and ROSAT.We then studied the discrimination of quasars from stars and the classification of quasars,stars and galaxies with the sample from optical and radio bands and with that from optical and X-ray bands. Moreover, feature selection and feature weighting based on Random Forests were investigated. The performances based on different input patterns were compared. The experimental results show that the random forest method is an effective method for astronomical object classification and can be applied to other classification problems faced in astronomy. In addition, Random Forests will show its superiorities due to its own merits, e.g. classification, feature selection, feature weighting as well as outlier detection.     

省级国土资源数据中心数据库命名规则研究

在对省级国土资源数据的多业务、多时相,多领域,海量性等特征分析的基础上,依据国家的相关标准与规范,对省级国土资源数据中心数据库分类体系进行了研究,将信息分类编码方法应用于国土资源数据中心数据库的分类编码工作,制订了适用于省级国土资源数据中心的数据库命名编码规则.     

The global climate monitor system: from climate data-handling to knowledge dissemination

This paper summarizes our work on building a data model and a geovisualization tool that provides access to global climate data: the Global Climate Monitor Web Viewer. Linked to this viewer, a complete set of climate-environmental indicators capable of displaying climate patterns on a global scale that is accessible to any potential user (scientists and laypeople) will be built and published using the same online application. The data currently available correspond to the CRU TS3.21 version of the Climate Research Unit (University of East Anglia) database – a product that provides data at a spatial resolution of half of a degree in latitude and longitude, spanning January 1901 to December 2012, on a monthly basis. Since January 2013, the datasets feeding the system have been the GHCN-CAMS temperature dataset and the Global Precipitation Climatology Centre (GPCC) First Guess precipitation dataset. Climatologists, hydrologists, planners and non-experts users such as media workers, policymakers, non-profit organizations, teachers or students, can access useful climatological information through the Global Climate Monitor system.     

A Spatiotemporal Data Model on Relational Databases for Coastal Dynamic Research

Spatiotemporal information is currently among the most significant data used in Geographical Information Systems (GIS), especially for modeling dynamic coastal areas. As the design of the data model is the most fundamental issue for representing spatiotemporal data, this article focuses on the basic solution of how to represent spatial, attribute, and temporal information in an integrated form. By presenting a data model on relational databases, together with an object-oriented model for system development, it is expected to provide both theoretic and technical support to the spatial and temporal analyses in GISs for various applications.     

Data model and visualization of 3D city landscape based on integrated databases

Data acquisition and modeling are the two important, difficult and costful aspects in a Cybercity project. 2D-GIS is mature and can manage a lot of spatial data. Thus 3D-GIS should make the best of data and technology of 2D-GIS. Construction of a useful synthetic environment requires integration of multiple types of information like DEM, texture images and 3D representation of objects such as buildings. In this paper, the method for 3D city landscape data model and visualization based on integrated databases is presented. Since the data volume of raster are very huge, special strategies(for example, pyramid gridded method) must be adopted in order to manage raster data efficiently. Three different methods of data acquisition, the proper data structure and a simple modeling method are presented as well. At last, a pilot project of Shanghai Cybercity is illustrated.     

省级国土资源数据中心数据库命名规则研究

在对省级国土资源数据的多业务、多时相,多领域,海量性等特征分析的基础上,依据国家的相关标准与规范,对省级国土资源数据中心数据库分类体系进行了研究,将信息分类编码方法应用于国土资源数据中心数据库的分类编码工作,制订了适用于省级国土资源数据中心的数据库命名编码规则。     

Integrated Storage and Querying of Spatially Varying Data Quality Information in a Relational Spatial Database

This article investigates a new, integrated technique for storing and retrieving spatially varying data quality information in a relational spatial database. Rather than storing global data quality statements, the system enables data quality information to be referenced to a spatial framework, individual spatial objects, or even parts of spatial objects. The integrated model, called as RDBMS for Spatial Variation in Quality (RSVQ), allows flexible storage of spatially varying data quality information, and seamless querying irrespective of the underlying storage model. RSVQ is founded on a formal model of relational databases, defining a new derived, polymorphic query operator      to join quality data with spatial data. The      operator is implemented in an extension to SQL as a new WITHQUALITY keyword. A performance evaluation of RSVQ was conducted, using an Oracle Spatial database and a case study of cadastral data for parts of Victoria, Australia. The results of this evaluation demonstrated that the system is practical and efficient for a wide range of queries, as well as indicating the performance trade-offs associated with the different data quality storage models. Using the integrated RSVQ approach provides the potential for a single, consistent, database engine for a wide range of existing and proposed spatial data quality management systems.     

城市空间数据库动态更新机制研究与实现

针对长期困扰城市空间数据库建设的“更新冲突”问题进行了深入分析,提出了基于对象特征的数据动态更新机制,并完成了系统的设计与开发。实验证明：该系统可以满足城市空间数据库动态更新的需要。     

A multigranular object‐oriented framework supporting spatio‐temporal granularity conversions

Several application domains require handling spatio‐temporal data. However, traditional Geographic Information Systems (GIS) and database models do not adequately support temporal aspects of spatial data. A crucial issue relates to the choice of the appropriate granularity. Unfortunately, while a formalisation of the concept of temporal granularity has been proposed and widely adopted, no consensus exists on the notion of spatial granularity. In this paper, we address these open problems, by proposing a formal definition of spatial granularity and by designing a spatio‐temporal framework for the management of spatial and temporal information at different granularities. We present a spatio‐temporal extension of the ODMG type system with specific types for defining multigranular spatio‐temporal properties. Granularity conversion functions are introduced to obtain attributes values at different spatial and temporal granularities.