Representation of geographic concepts

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Representation of geographic concepts

• Geog 495 GIS database design
• November 7, 2005

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Outlines

• D Review of the article Egenhofer et al 1999
• Discussion will be focused on
• Relational DB and GIS
• Cognitive approach to GIS
• GIS and DBMS
• GISystems and GIServices
• L Representation of spatial entity
• Lecture is organized into three parts
• Spatial data model
• Spatial data structure
• Design consideration

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DB implementation of geographic concepts is
divided into three subfields in GIScience

• Spatial data model/spatial query language
• Spatial data type/operators
• Spatial access method
• Q. What are they about?
• Q. Indicate a level of abstraction for each
• Q. What are different focuses on these?

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Mathematics and GIS

• It is said that database implementation of
  geographic concepts heavily borrows from
  mathematics. So which subfields of mathematics
  are influential in the followings?
• Representation of geographic entities
• e.g. Spatial primitives of vector data (point,
  line, polygon)
• Representation of spatial relationships
• e.g. Connectivity in road network

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Database and GIS

• Since most of GIS is implemented using RDB, lets
  focus on RDB.
• Examples building Country database, how can you
  store geometric features of Country in table? Is
  multi-valued attribute allowed? Then break it
  down to 4NF. And then What about query such as
  displaying boundary of France? What about query
  such as returning adjacent countries of France?
• Now generalizing your point, go to the next slide

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Inadequacy of RDB to GIS

• What is the inadequacy of employing relational
  database model for representing geographic
  concepts?
• What is the legacy of storing spatial information
  in relational database when creating GIS
  database?
• How can we accommodate this problem? Think from
  different perspectives. If you are DB developer,
  If you are network administrator who makes
  decision on GIS/DBMS purchase, if you work in ISO
  committee, if you are a researcher...

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Cognitive approach to GIS

• Do you agree with authors view on cognitive
  approach?
• Where do you think cognitive approach will be
  useful for making a better GIS (thats the goal
  of GIScience)? Remember the current GIS is a just
  snapshot. You could be a person who can create a
  better GIS.
• Query based on natural language (for visually
  impaired?)
• Design of better user interface design
• Development of spatial data model (beyond
  vector/raster?)

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GIS and DB systems

• Four different approaches to integrating GIS with
  DB systems
• Extension of GIS with DB functionalities
• e.g. Arc/Info, Arcview support ODBC
• Coupling of a GIS with commercial DBMS
• e.g. spatial data is stored in relation DB so
  that SQL can be called upon the spatial data
• Extension of DBMS with spatial functionalities
• e.g. Illustras DataBlades, Oracles Cartridges
• Open toolbox approaches where GIS provides
  specialized services
• e.g. you work in your computer where you can
  download data or processing tools from server

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GISystems and GIServices

• Would a gradual shift toward GIServices replace
  GISystems?
• What would be the likely impact of GIServices?
  What about the impact on the integration of GIS
  with DB systems?

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• Representation of spatial entity

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Data hierarchy

• Data model how the real-world is viewed
• e.g. Relational DB, Object-Oriented DB Model
• e.g. Object view, Field view
• Data structure how data is stored in the
  computer
• e.g. Vector, Raster, TIN
• Data (file) format how data storage is specified
  in s/w-specific way, you need particular viewer
  to display the data
• e.g. VPF, shapefile, MrSID

Level of abstraction
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Spatial data modelhow spatial things are viewed

• Object view
• See that the world is composed of discrete entity
• Interested in precise location of geographic
  features
• Space is measured, attribute is controlled
• Human beings prefer discrete perception of things
  rather than fuzzy perception
• e.g. parcel, lake, city
• Field view
• See that the world is composed of continuous
  field
• Interested in smooth variation in attribute over
  space
• Space is controlled, attribute is measured
• Measuring attribute for all locations are
  infeasible due to its continuity
• e.g. elevation, temperature

Q. So which view is implicitly supported by DB
model such as OO or relational?
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Spatial data structurehow spatial things are
stored in the machine

• Way to represent spatial things
• Vector point, line, polygon, node, vertices
• Raster a set of grid cell
• Way to represent spatial relationships
• TIN (Triangulated Irregular Network) a set of
  triangulated line between neighboring points
• Matrix stores attributes of relationships
  between spatial objects

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Note on spatial data structure

• Spatial data structure appears to correspond to
  spatial data model (i.e. nature of phenomenon
  continuous/discrete)
• However, data structure is largely determined by
  the manner of data input regardless of the nature
  of geographic phenomenon
• Vectorization of paper map (i.e. digitizing)
• Satellite image, Air photo
• You should choose data structure suitable for the
  nature of phenomenon given users need

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More on vector

• Higher-level vector
• Overlapping polygon (e.g. flycircle)
• Multi-part polygon (e.g. Hawaiian island)
• Hole in polygon (e.g. lake in island)
• Spaghetti model vs. topological model
• Cartographic purpose spaghetti will do
• What is topology? Why do we need topology?
• e.g. Network model commonly uses link-node
  representation
• Planar vs. non-planar
• How to represent overpass in contrast to
  intersection?

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How topology is stored
Q. What kind of topology is measured?
containment, connectivity, contiguity
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How to build topology

• Do some exercise in the lab
• 1) Digitize features over backdrop (say airphoto)
  say at arcview
• 2) Save the file and import this file into
  arc/info coverage (use SHAPEARC)
• 3) Use CLEAN command in Arc/Info workstation
• 4) Read attributes at feature attribute table,
  say AAT and PAT

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Planar vs. non-planar
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More on Raster

• Same values are often repeated in the cell
• Efficient storage method (or compression method)
  is needed as it uses space rather inefficiently
• These are methods for storing
• Run-length code linear representation of cell
  values
• Quadtree hierarchical organization of raster
  structure (e.g. SPAN)

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Run-length code, Quadtree
Run-length code 3A1B2A2B2A2B1A3B
Quadtree is also known for spatial access method
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• See how, run-length code can save space, and save
  time in searching the location of Well

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Triangulated Irregular Network (TIN)

• Point is not sampled in a regular manner
• Sample points are connected by lines to form
  triangles
• Compact representation of surface (compare this
  to point-based DEM)

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Matrix

• Used to represent attributes of spatial
  interaction (e.g. commuting flow, traffic flow,
  commodity flow, migration, and so on)
• Conversion between matrix and relational table
  often necessary as matrix is not well supported
  in GIS software

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Same phenomenon can be represented differently
(data structure)

• Q. How topography is stored in GIS?
• In Raster
• In TIN
• In Vector

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Spatial file format

• This is system-specific, so you need a specific
  software to view them
• TIGER/Line, DXF, SHP, TIFF
• SDTS (Spatial Data Transfer Standard)
• MrSID
• Need for metadata to exchange info
• FGDC standard, XML
• Need for interoperability
• Converting file formats are tedious and sometime
  it loses information
• OpenGIS

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Special aspect of spatial data

• Spatial data, unlike attribute data, are designed
  for display in addition to query
• Therefore, some technical aspects of cartographic
  representation should be taken into account when
  you design database for GIS
• e.g. some cartographic symbol can be exaggerated
  to enhance readability without regard to its
  positional accuracy

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Which model to choose will be influenced by

• Users need/application
• e.g. routing application requires link-node
  model, road maintenance application requires
  polygon representation of road as width of road
  can be important
• Geographic scale
• Line generalization (e.g. Douglas-Peuker
  algorithm)
• Multiple representation
• Annotation

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Terms

• Interoperability the ability of two or more
  systems or components to exchange information and
  to use the information that has been exchanged
• Open GIS Consortium Non-profit organization that
  works for standardizing the implementation
  specification of geospatial information designed
  to form the architecture for interoperability
  promotes COM technology
• Middleware software that glues two separate
  applications e.g. link a database system to
  application balances traffic between the two

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Terms

• MBR (Minimum Bounding Rectangle) spatial access
  method uses filter-refine step. Where filter
  select candidates using minimum bounding
  rectangle.
• R-trees spatial access method that stores
  overlapping MBR into tree-structure
• Quadtree spatial access method that stores
  non-overlapping multi-scale grid into
  tree-structure, also known as the method for
  compressing raster data structure
• Which version of SQL has the spatial extensions?
• 1) SQL1 2) SQL2 3) SQL3