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Oracle Spatial and Mapviewer Problems From Real World Applications

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Title: Oracle Spatial and Mapviewer Problems From Real World Applications


1
Oracle Spatial and MapviewerProblems From Real
World Applications
2
Oracle Spatial Capabilities
Spatial Analysis
Spatial Data Types
Spatial Indexing
Fast Access to Spatial Data
All Location/Spatial Data Stored in the Database
Spatial Access Through SQL
3
Manage ALL Geospatial Data Types
Networks (Connectivity)
Parcels (polygons)
Locations (points)
Data
Imagery (Raster)
3D data (models, LIDAR)
Structured Networks/Boundaries (persistent
topology)
4
ltInsert Picture Heregt
Some Interesting Problems From The Commercial
World
5
Network Partitioning
6
Network Data Model
  • Data Model
  • Store network (graph) structure in the database
  • Maintains connectivity of the network
  • Attributes at link and node level
  • Network Analysis Functions
  • Traditional network algorithms are based on main
    memory
  • Need new approaches to deal with large networks
    that are too big to fit into main memory

7
Load On Demand Analysis
  • Supports load-on-demand approach for very large
    networks
  • Networks are logically partitioned
  • Each sub-network is small (thousands of
    nodes/edges)
  • Sub-networks are incrementally loaded into memory
    as needed for analysis
  • Partitioning utilities are available for
    partitioning large spatial networks

8
Spatial Network Partitioning
9
Logical Network Partitioning
Very Large networks (few hundred million
nodes/links) Updates to the data are common
10
Automated Generation of 3D data
11
SDO_GEOMETRY for 3D Data
  • Points
  • Lines
  • Simple Surfaces
  • All points of a surface lie in a 3D plane
  • A 3 point 3D polygon is the simplest surface
  • A simple surface can have any polygonal shape
  • Composite surfaces
  • has one or more connected simple surfaces
  • It can be closed or open
  • The simple surfaces in a composite surface cannot
    cross each other
  • surface of a cube is an example of a composite
    surface
  • Cube has six simple surfaces
  • Each simple surface is a 3D square

12
SDO_GEOMETRY for 3D Data
  • Simple Solids
  • Solids are composed of closed surfaces
  • It has to have one outer surface and one or more
    interior surfaces
  • Cube is an example of a simple solid
  • A pyramid is another example of a simple solid
  • Composite Solids
  • Consists of n simple solids as a connected solid
  • Can be represented as a simple solid with a
    composite surface
  • Topologically there is an equivalent simple
    solid, but the composite solid representation is
    easier
  • Example A building composed of rooms
  • Simple, composite solids
  • Always define a single contiguous volume

13
3D Data Extraction
  • Extract faces of buildings
  • Generation of valid 3D objects from primitive
    elements
  • Generating a valid multi-surface from a set of
    planar polygons
  • Generating a valid solid/multi-solid from a set
    of planar polygons

14
3D Extrusion
  • Extruding 2D foot-prints to valid 3D objects

15
Generalization in 3D
16
City GML Example
  • Start with building models generating using CAD
    data
  • Generate generalized views of the data for large
    volumes of data (city models)

17
Map Generalization
18
Map Simplification with Multiple Layers
  • Mapshaper.org

19
Managing Very Large TINs
20
TIN Triangulated Irregular Network
  • What is a TIN?
  • Vector-based topological data model used to
    represent terrain/surface
  • Contain a network of irregularly spaced triangles
  • 3D surface representation derived from
    irregularly spaced points
  • Each sample point has an x, y coordinate and a z
    value or surface value

Node No X Y Z
1 5 6 3
2 3 6 5
3 1 5 6
4 4 4 4
5 6 5 3
6 2 2 2
. . . .
21
Disk based TIN Generation
  • Many main memory algorithms for creating TINs
  • These algorithms do not scale for very large
    number of points
  • Constrains add additional complexity
  • Break lines, stop lines
  • Void polygons

22
Grid based TIN Generation
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