The 3rd ISPRS Workshop on Dynamic and Multi-Dimensional GIS & the 10th Annual Conference of CPGIS on Geoinformatics

Chen, Jun

Bibliographic data

Monograph

Persistent identifier:: 856566209

Author:: Chen, Jun

Title:: The 3rd ISPRS Workshop on Dynamic and Multi-Dimensional GIS & the 10th Annual Conference of CPGIS on Geoinformatics

Sub title:: May 23 - 25, 2001, Bangkok, Thailand

Scope:: VI, 434 Seiten

Year of publication:: 2001

Place of publication:: Pathumthani, Thailand

Publisher of the original:: AIT

Identifier (digital):: 856566209

Illustration:: Illustrationen, Diagramme, Karten

Language:: English

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2016

Document type:: Monograph

Collection:: Earth sciences

Chapter

Title:: BUILDING OF B/S-BASED OBJECT ORIENTED ELECTRONIC CHART DATABASE. Guangru LI, Shaopeng SUN, Depeng ZHAO

Document type:: Monograph

Structure type:: Chapter

ISPRS, Vol.34, Part 2W2, "Dynamic and Multi-Dimensional GIS”, Bangkok, May 23-25, 2001 inheritance, encapsulation, congregation, etc. Objected oriented geographic database need maintain the integrality and consistency of storage and expression. For example, a route has only one geometrical identification and one geographic identification. The data organization of geographic data includes organization and management of spatial data, attribute data, image data, etc. The key technology of data organization is to express and store spatial data and attribute data integration. 1) spatial objects mainly divided into five categories: • Point: It includes single point (e.g. buoy, navigation mark, etc.), vector point (e.g. beacon), etc. • Line: Line is interconnected points or arcs, they may netlike, but must interconnected, such as fiber cable, etc. • Region: Region was made up of one or many closed and disjointed polygons and rings, it can include multi-island. For Example, anchorage ground, restricted navigation zone are all region. • Complicated object: The object was made up of two or more basic objects (point, line, region) or other complicated objects. For example, school can act as a complicated object,. It includes roads, houses, water tower and some other basic geographic elements. • Annotate. Annotate is used to describe place name, features of geographic objects, etc. Because the model need all terrain features should be stored integration, each integrated terrain feature only has single geometric object identification no matter how big the terrain feature is. The spatial data of terrain feature should be stored integration. But the segregation of integration of terrain features should depend the requests of users and applications completely. 2) Attributes: Attributes of all spatial object should be managed in project unitedly by RDBMS. Attribute data were stored in tables of RDBMS. Referring to standard objects, users classify them unitedly, and appoint single classification code (identification) of terrain features. For example, we classify them into control point, road, habitation, water system, vegetation, etc. in different tiers. Any integrated terrain feature only corresponds to one record of attribute data. Single object identification (OID) connects spatial object and the corresponding attribute record, which was described in figure 1. In order to organize and express spatial geographic objects efficiently, we extract objects hierarchically according to the size of geographic objects, and arrange, delaminate and build spatial index for these objects. The system architecture of object oriented chart database. The B/S map database is the production of combination of database technology and computer network technology. It is a computer system to manage distributed map database. A distributed map database is a set that was composed by many logic related databases distributed in network. Each node of this network has independent processing ability to implement local application. At the same time, each node can implement global application through network system. Map database server is mainly used to manage SQL requests from clients, and return results to clients. In practice, database server achieves all data operations, spatial data organizations, concurrency control, security auditing, and system management in C/S database. Client mainly presides send user’s SQL requests to server, and processes and expresses the results. In a typical application structure, client usually deals with the application’s expressive logic. B/S map database is an organic association of member map database located in nodes of network. The management of this association is B/S map database system. Electronic Chart evolved from file-based application to spatial geographic extended RDBMS, and aim to a integrated object relational system. Therefore, we can use spatial geographic technology to process file, time series data, image and audio, and some other standard, abstract data type seamlessly. The problem, which must be resolved by RDBMS, can use more direct and accurate approach (e.g. SQL) to resolve. Traditionally, there are two kinds of spatial data index: The first is to build a spatial index out of the server and stored in BLOB, and you can use it or search BLOB when you use it. However, no matter how fine this index’s structure is, the maintenance and searching include external parts, which will lead to more I/O overhead and coexist problem, to make system slower and inefficient. Second method is spatial segmentation. This method divides data into cells according to stated grid and other layered architecture (e.g. quad tree). Each cell was assigned a number, and each spatial object relates to the number of the same cell. But space is not in linear order. The irregularity of many spatial features needs intricate searching and the check for many potential errors. It’s also a slower and inefficient method. Comparing to the methods we discuss above, R-tree is a high-powered, multidimensional access approach. This approach is built in kernel of database and cooperates with extensional data type to manage spatial geographic data properly. Being different from standard index. R-tree does not divide the space into integrated overlay made up of non-overlap and adjoining cells. Adversely, it automatically represents each object with "side box” that is decided by spatial figure. These “side box” may overlap, and do not fill all space. We should not know the spatial dimension of data in advance. A spatial data engine (SDE) layer or data class is geographic feature classes that have the same attribute class. In order to search conveniently, SDE uses DBMS attribute column index. SDE index all features in a layer, to realize rapid spatial searching, and provides high-powered searching for oversize database. The unique function of spatial index is to provide special two dimensions index of spatial features, and to realize a logical and nonphysical hierarchy. The efficient supporting of geographic data not only needs point, line and region objects, but also needs a set of steady spatial object models that can express their features clearly. SDE can describe linear features, for instance, an uncrossed road, a road crossed at termination, a self-crossed rode, and multi-roads that crossed at end-point to form a network. Similarly, we can describe region features by single polygon, hollow polygon, and poly-polygons. Attribute also cannot be directly indexed into regional piece object, but indexed into a concrete place in this regional piece. Due to each accessing of polygons need be included into reconstruction of multi-accessing, the feature we talk above may become a default. The spatial object model of SDE stores each regional piece into an integrated polygon. Thus, we can find entire object by only one accessing. In SDE, geographic features include spatial objects (e.g. point, line or region) and relevant attributes described by these objects. In RDBMS, data were stored in the tables made up of rows and columns. The crossed cell of row and column names field, and the data stored in field names value. Row represents a specific event, distance or geographic feature, and column includes the attribute of this feature. There are many types in attributes, which make geographic features become a value type stored in a column. SQL provides a interface of rational table, which enable user can select rows according to the number in the field. SQL statement is very flexible to program any basic query request. Through the key, user can query the required data from tables. A key (it may be made up of one or more columns) represents the table uniquely. A column or several columns can be copied to another table, named external key. Main key and external key link two tables together, which can reduce the redundancy of the database. This technology is called database standardization. We can satisfy the request and return the accurate geographic data through adding more tables and using the relations among main keys and external keys. The query results are a series of rows that satisfy the corresponding SQL statements. These SQL statements are called cursor. The application can index large numbers of active cursors, and query every independent row from a cursor. In object oriented DBMS, SDE can make IDS store and manage complicated geographic data. SDE does not change existing database or affect current application. It only adds a “Shape” column into existing table, and provides software to manage and access geometrical features of this column. SDE use R-tree to

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