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Spatial Databases - Introduction Spring, 2015 Ki-Joune Li
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STEMPNU 2 Spatial Databases What are on these images ? How to represent, store, and retrieve these data
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STEMPNU 3 What are on these images? These include Pixels Objects Buildings, Roads, Symbols, etc Terrain Height Data Non-Spatial Data Name of Roads, Levels of Buildings, Capacity of Bridge, etc Relationship Between Objects Goal of Spatial Databases Spatial databases are for representing, storing and retrieve useful information from these data
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STEMPNU 4 Properties and Challenges Characteristics of Spatial Databases Spatial Data: Very Large Amount of Data Example : more than 200 peta bytes for EOS Project Very complicated Major Challenges How to represent sophisticated data: Representation How to store and manage a large amount of data: Management
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STEMPNU 5 Issue I: Modeling Example Building Spatial DB about Pusan City What is Modeling? (cf. Schema Design) Modeling is much more important than schema design Real World Computer World
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STEMPNU 6 Issue II: Management System How to Handle Large Volume of Data Cost for Storage Media Not very important and negligible Processing Time I/O time How to reduce disk i/o time ? DBMS Issue
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STEMPNU 7 Spatial Databases ? Databases for spatial phenomena Spatial phenomena ? Phenomena with spatial properties Spatial properties ? What are spatial properties ? Example Distance, Surface, Position (Coordinates) Adjacency, Connectivity
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STEMPNU 8 Spatial Properties: Space Depending on the Type of Space Euclidean Space Flat space represented by R n coordinate systems Point p is represented as an n-ary tuple (x 1,x 2, …, x n ) Road Network Space, Terrain Space, Indoor Space
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STEMPNU 9 Open Space vs. Constraint Space Open Space Distance is determined by the straight line connecting two points Example: Euclidean distance (or Euclidean metric) Constrained Space Constraint on the straight line Distance is the length of shortest path detouring constraints Examples of Constraint Road Network Indoor Terrain
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STEMPNU 10 Example: Indoor Space Emergency Bell A 401 W.C. 404 405 406 Elevator Stairs p Real distance Emergency Bell B
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STEMPNU 11 2-D space and 3-D space 3-D (cf. 2-D) More information Large amount of data Example Rectangle: 4 vertices, 4 edges, and 1 face Cube: 8 vertices, 12 edges, and 6 faces Complicated geometric processing Example Overlapping of two polygons Overlapping of two polyhedrons
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STEMPNU 12 2.5-D space 2.5-D space (cf. 3-D space) 3-D space: Solid Modeling 2.5-D space Only one height value at any given point: f (x, y)=h Field and 2.5-D Field: Terrain, Temperature distribution, etc.. 2.5-dimensional representation: Field Representation
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STEMPNU 13 Spatio-Temporal Model Spatial Model Stationary objects or phenomena Every object on the earth is moving! Spatio-Temporal Model Object changing its location or shape according to time Discrete change Example: Change of administrative boundary Continuous change Example: Moving Objects, Meteorological Lines, Pollution Areas
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STEMPNU 14 Topological and Geometric Properties Geometry: Geo + Metry Geo: Earth, Space Metry meter, metric, etc.. something to measure Geo+Metry Something to measure in space Quantitative m, m 2, etc.. Topology Relationship between Spatial Objects Qualitative adjacent, inside, left, right
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STEMPNU 15 Spatial Database Building Procedure Comparison with Software Life Cycle Comparison with Building Construction
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STEMPNU 16 Spatial Database Building Procedure Requirement Analysis Scope of databases: depends on applications Data Items, Attributes, Accuracy, etc.. Use-Case Diagram Current State: As it isAs it must be
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STEMPNU 17 Spatial Database Building Procedure Data Modeling Understanding the real world and application A very small piece of the real world According to viewpoint Determined by applications Drawing what you have understood in formal method Example. UML 4 steps Requirement Analysis Entity and Granularity Attributes Relationships
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STEMPNU 18 Spatial Database Building Procedure Data Collection Legacy System and Databases Interoperability and Standard Issue Data Generalization Metadata Data Input Relies on Manual work Automatization
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STEMPNU 19 Spatial Database Building Procedure Quality Control Check the correctness of data Maintenance Periodic Backup Updates Equivalent to 30% of the total amount of data Determine the quality of DB
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