Scaling up the DBSCAN Algorithm for Clustering Large Spatial Databases Based on Sampling Technique

Clustering, in data mining, is a useful technique for discovering interesting data distributions and patterns in the underlying data, and has many application fields, such as statistical data analysis, pattern recognition, image processing, and etc. We combine sampling technique with DBSCAN algorithm to cluster large spatial databases, and two sampling based DBSCAN (SDBSCAN) algorithms are developed. One algorithm introduces sampling technique inside DBSCAN, and the other uses sampling procedure outside DBSCAN. Experimental results demonstrate that our algorithms are effective and efficient in clustering large scale spatial databases.

Unified Platform About Information Issuing,Integration and Management of Meta-Database and Spatial-Database Based on Geology Metadata Standard

With the deepening informationization of Resources & Environment Remote Sensing geological survey conducted,some potential problems and deficiency are:(1) shortage of unified-planed running environment;(2) inconsistent methods of data integration;and(3) disadvantages of different performing ways of data integration.This paper solves the above problems through overall planning and design,constructs unified running environment, consistent methods of data integration and system structure in order to advance the informationization

Federated Spatial Databases and Interoperability

It is a period of information explosion. Especially for spatial information science, information can be acquired through many ways, such as man made planet, aeroplane, laser, digital photogrammetry and so on. Spatial data sources are usually distributed and heterogeneous. Federated database is the best resolution for the share and interoperation of spatial database. In this paper, the concepts of federated database and interoperability are introduced. Three heterogeneous kinds of spatial data, vector, image and DEM are used to create integrated database. A data model of federated spatial databases is given.

Processing Constrained K Closest Pairs Query in Spatial Databases

In this paper, constrained K closest pairs query is introduced, wbich retrieves the K closest pairs satisfying the given spatial constraint from two datasets. For data sets indexed by R trees in spatial databases, three algorithms are presented for answering this kind of query. Among of them, two-phase Range＋Join and Join＋Range algorithms adopt the strategy that changes the execution order of range and closest pairs queries, and constrained heap-based algorithm utilizes extended distance functions to prune search space and minimize the pruning distance. Experimental results show that constrained heap-base algorithm has better applicability and performance than two-phase algorithms.

DCAD:a Dual Clustering Algorithm for Distributed Spatial Databases

Spatial objects have two types of attributes: geometrical attributes and non-geometrical attributes, which belong to two different attribute domains (geometrical and non-geometrical domains). Although geometrically scattered in a geometrical domain, spatial objects may be similar to each other in a non-geometrical domain. Most existing clustering algorithms group spatial datasets into different compact regions in a geometrical domain without considering the aspect of a non-geometrical domain. However, many application scenarios require clustering results in which a cluster has not only high proximity in a geometrical domain, but also high similarity in a non-geometrical domain. This means constraints are imposed on the clustering goal from both geometrical and non-geometrical domains simultaneously. Such a clustering problem is called dual clustering. As distributed clustering applications become more and more popular, it is necessary to tackle the dual clustering problem in distributed databases. The DCAD algorithm is proposed to solve this problem. DCAD consists of two levels of clus- tering: local clustering and global clustering. First, clustering is conducted at each local site with a local clustering algorithm, and the features of local clusters are extracted. Second, local features from each site are sent to a central site where global clustering is obtained based on those features. Experiments on both artificial and real spatial datasets show that DCAD is effective and efficient.

A CADASTRAL SPATIAL DATA STORAGE STRUCTURE BASED ON RELATIONAL DATABASE

This paper presents a cadastral spatial data storage structure based on relational database,the method and the procedure to realize it.The paper consists of three parts.In the first part,some existing problems in some developed cadastral management systems are discussed.These problems are the following four.1) The security of cadastral spatial data is difficult to be assured.2) It is difficult to varify cadastral data and the integrality of cadastral data is difficult to be kept.3) To transmit and share cadastral data is difficult.4) The efficiency of data access is low.In the second part,the feasibility of using relational database to store spatial data is analyzed and a new cadastral spatial data storage structure is presented.At the same time,the related table structures and field descriptions are given,and then the merits and demerits of this storage structure are analyzed in detail.In the last part,through a real example,the detailed methods to make the new storage structure a reality are given.Moreover,some involving key techniques of the new storage structure are discussed.These techniques are:1) the application of database transaction,2) the application of database trigger,3) and the application of secure recovery of database.

THE INTEGRATED SPATIAL DATABASES OF GEOSTAR

GeoStar is the registered trademark of GIS software made by WTUSM in China.By means of the GeoStar,multi_scale images,DEMs,graphics and attributes integrated in very large seamless databases can be created,and the multi_dimensional dynamic visualization and information extraction are also available.This paper describes the fundamental characteristics of such huge integrated databases,for instance,the data models,database structures and the spatial index strategies.At last,the typical applications of GeoStar for a few pilot projects like the Shanghai CyberCity and the Guangdong provincial spatial data infrastructure (SDI) are illustrated and several concluding remarks are stressed.

Concepts and Applications of Spatial Database for Geo-Archives Catalog

The searching method of spatial information on traditional geo-archives catalog database(TGCD) is based on the text,and the result of retrieval can be only from the text of fields of relational database.The information queried must be input into the relational database as a text form in advance,otherwise,the visitors would not get any result from it.So。

Construction of Spatial Database of Tourism Resources in the Lijiang River Basin Based on MapGIS

GIS and GPS technology was applied to construct spatial database of ecotourism resources in the Lijiang River Basin,the process of constructing database was elaborated,data collection and processing as well as specific schemes of building graphic database and attribute database were introduced,in order to provide data support for optimizing the development spaces of regional tourism resources,regulating development activities,and realizing sustainable development of ecology,environment,tourism economy and society.In addition,this paper also offered data support for eco-environment monitoring,building tourism resource management information system and "Digital Lijiang".

A recovery method using recently updated record information in shared-nothing spatial database cluster

A shared nothing spatial database cluster is system that provides continuous service even if some system failure happens in any node. So, an efficient recovery of system failure is very important. Generally, the existing method recovers the failed node by using both cluster log and local log. This method, however, cause several problems that increase communication cost and size of cluster log. This paper proposes novel recovery method using recently updated record information in shared nothing spatial database cluster. The proposed technique utilizes update information of records and pointers of actual data. This makes a reduction of log size and communication cost. Consequently, this reduces recovery time of failed node due to less processing of update operations.

Topo semantic constraint-violations in spatial database

Aiming at the problem that current geographical information systems(GIS)usually does not maintain semantic and user-defined constraints out of three consistency-constrains(third refers to topology constraint),this research focuses on building an efficient spatial data management system using two constraint violation detection methods.An algorithm for constraint violation detection has been derived to maintain the error-free up-to-date spatial database.Results indicate that the developed constraint violation detection(CVD)system is more efficient compared with conventional systems.

An Introduction to the Latest-generation Spatial Database of Active Tectonics of China

Based on ArcGIS and MapInfo software, we digitized the active tectonics map (1:4,000,000) of China, which was compiled and revised by academician Deng Qidong, and built the spatial database of active tectonics of China. The database integrates rich active tectonic data, such as a catalogue of earthquakes with magnitude above 6.0, active faults, Quaternary basins, active folds and their associated attribute parameters, and implements scientific and effective management to this data. At the same time, the spatial database joins the spatial map data and the associated attribute data together, which implements the data query between spatial properties and attribute parameters and also makes it possible to perform spatial analysis with different data layers. These provide much convenience for earthquake study and allows engineering construction institutions to use this data in practical applications.

A solution for digital image management in spatial databases

Digital Orthographic Map (DOM) can be used in various applications because it contains both image features and terrain information. Spatial database management systems aim at the effective and efficient management of data related to a space, engineering design and so on. Thereby spatial database provides an efficient solution for managing DOM. According to large amounts of the DOM data in storage, a data compression based on wavelet is introduced into the storage. Another strategy to solve this problem is to decompose the raw image into tiles and store the tiles individually as separate tuples. The metadata of DOM can be used to organize and manage spatial information, especially for spatial data sharing and fast locating. A tool for browsing, zooming and querying the DOM data is also designed. We implemented these ideas in SISP(Spatial Information Sharing System) and applied the subsystem into the DOM management of Beijing City, which is an component of the Beijing Spatial Information Infrastructure.

A solution of spatial query processing and query optimization for spatial databases

Recently, attention has been focused on spatial query language which is used to query spatial databases. A design of spatial query language has been presented in this paper by extending the standard relational database query language SQL. It recognizes the significantly different requirements of spatial data handling and overcomes the inherent problems of the application of conventional database query languages. This design is based on an extended spatial data model, including the spatial data types and the spatial operators on them. The processing and optimization of spatial queries have also been discussed in this design. In the end, an implementation of this design is given in a spatial query subsystem.

Version based spatial record management techniques for spatial database management system

The search operation of spatial data was a principal operation in existent spatial database management system, but the update operation of spatial data such as tracking are occurring frequently in the spatial database management system recently. So, necessity of concurrency improvement among transactions is increasing. In general database management system, many techniques have been studied to solve concurrency problem of transaction. Among them, multi version algorithm does to minimize interference among transactions. However, to apply existent multi version algorithm to improve concurrency of transaction to spatial database management system, the waste of storage happens because it must store entire version for spatial record even if only aspatial data of spatial record is changed. This paper has proposed the record management techniques to manage separating aspatial data version and spatial data version to decrease waste of storage for record version and improve concurrency among transactions.

基于3S的溱湖湿地Geodatabase构建及景观格局评价

运用景观生态学的研究方法,以1995年和2006年的2期溱湖湿地航空影像为主要数据源,TM、ETM+多光谱数据、Globcover300m及1∶100000土地利用数据为辅助数据,建立Geodatabase空间数据库,对溱湖湿地景观空间格局及其演变进行分析。研究表明:1995至2006年,研究区内沼泽地景观面积、分维度有所增加,斑块数、破碎度和分离度有所减少;有林地分维度、破碎度有所减少;呈现以水域、沼泽地为基质,有林地、耕地和居民地相对为主体的湿地景观格局,湿地生态系统的保护和利用成效显著。同时,景观多样性、破碎度有所增加,优势度减少,可见人类活动范围的扩大和干扰活动的加剧,一定程度上引起景观内部空间格局的改变,加速了破碎化。

基于Geodatabase模型的空间数据库设计方法

近年来,利用空间数据库存储和管理空间数据,成为GIS领域研究的热点问题,其关键是空间数据库的设计。针对这方面研究相对较少的现状,作者以Geodatabase空间数据库设计为例,对空间数据库设计过程中所涉及到的关键技术和疑难问题进行了论述,提出了分析数据、选择模型、划分实体、确定关联、映射转换等设计步骤中需要遵循的设计原则,强调了CASE工具与UML建模在空间数据库设计中的重要作用。

基于Geodatabase的面向对象空间数据库设计

在Arc/Info中,支持空间数据库的数据模型经历了C AD模型、C overage模型和G eodatabase模型。文章通过讨论新一代的数据模型———G eodatabase及其G eodatabase数据库的结构体系和数据组织方式,实现了面向对象的空间数据库的设计。