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Lecture 5 (Geographic Data Modeling) Flashcards

1
Q

Geographic Data Modeling

A

How to represent real life object, data with a CPU

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2
Q

Model

A

Which is used in PRACTICAL and DATABASE fields (many shapes, styles, etc.) - We use because it simplifies the real world (human idea into a CPU model)

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3
Q

Data Model

A

A set of constructs for describing OBJECTS and PROCESSES in the digital environment.

  • Control the ways how data to be stored
  • Impact how the analytical operations to be performed (geography location of object)
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4
Q

Representation

A

Focus on CONCEPTUAL and SCIENTIFIC ISSUES (when thinking about real world -> GIS model for continuous world and discrete objects)

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5
Q

Role of Data Modeling

A

1) REAL WORLD -> 2) GIS DATA MODEL (DESCRIPTION AND REPRESENTATION) -> 3) OPERATIONAL GIS (ANALYSIS AND PRESENTATION) -> 4) PEOPLE (INTERPRETATION AND EXPLANATION)

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6
Q

Data Model Levels

A

Human Oriented (Reality (Real world phenomena/ All aspects may or may not be perceived by individuals) and Conceptual (HUMAN-ORIENTED/ Partially structured model for a particular problem) // INCREASING - Abstraction/ Simplification/ Generalization // Computer Oriented (Logical Model (Implementation-oriented/ Diagram or lists) Physical Model (Computer-oriented/ Tables, databases)).

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7
Q

Model Levels and Concerns

A
  • Conceptual: What do you want to do? (Define major GIS questions)
  • Logical: Who, When, Where, and How? (How GIS will be able to do under a specified temporal and spatial extent?)
  • Physical: By what means? (Describe the EXACTLY database to store data, relationship between objects, and PRECISE operatiosn to be performed)
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8
Q

Modeling Process

A

Physical Model (Database Schema) -> Real World -> Conceptual Model (Objects and relationships) -> Logical Model (Lists, Diagrams, Flow Charts)

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9
Q

Continuous Fields and Discrete Objects

A

Two fundamental CONCEPTUAL models in geographic representation (Colorado, USA)

  • Raster LOGICAL model
  • Vector LOGICAL model
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10
Q

Three generations of GIS data model

A

1st, CAD = File based
2nd, Coverage (e.g., coverage and shapefile)
- separation of spatial and attribute table
- topology
- geometry-centric
3rd, Geodatabase (DBMS-based, object oriented)

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11
Q

GIS Data Models and Applications

A

CAD - Engineering design and drafting
GCC - Simple Mapping
Image - Simple grids processing and analysis
Raster/ Grid - Spatial analysis/ modeling
Vector - Geoprocessing, geometric features
Network - Transportation and utility analysis
TIN - Surface/ Terrain analysis/ modeling
Object - Feature with its method/ behavior

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12
Q

The earliest GIS Data Models

A

CAD (Computer Aided Design and Drafting)

  • Point, line, and area vector
  • Local drawing coordinates instead of real work coordinates for representing objects
  • Difficult to tag the individual objects with attributes
  • Can’t store details of the RELATIONSHIPS between objects

ex. Graphical representation of objects

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13
Q

The earliest GIS Data Models

A

Graphical Computer Cartography (GCC)

  • Digitizing paper map in a computer for subsequent plotting and printing
  • Points, lines, and areas with annotations
  • No tag objects with attributes
  • Can’t work objects relationships ex. digitalized topographic map

Image Processing

  • Raster and grids
  • Data Sources (Scanned aerial photographs/ Digital satellite images)
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14
Q

Demo in ArcGIS

A

Scanned aerial photographs and Digital Satellite Images

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15
Q

Raster Data Model

A
  • GENERALLY, the implementation of continuous field conceptual model
  • Use a set of cells to represent objects
  • Useful as background maps (Look like conventional maps and convey lots of information quickly)
  • Spatial analytical and modeling applications (disease dispersion modeling/ surface-water flow analysis/ store location modeling)

ex. Land Cover Classification, Landsat 5 of Olympic Peninsula,

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16
Q

Electromagnetic Energy

A

Decreasing Wavelength ->
Increasing energy ->
ex. Landsat 8

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17
Q

Vector Data Model - Simple Features

A
  • Generally, the implementation of discrete object conceptual mode (Geometric representation: point, line and polygon)
  • Characteristics (Precise nature of its representation method, storage efficiency, high quality of the cartographic output)
  • Widely Used in Functional Tools for Operations (Map Projection: Overlap Processing: Cartography and network analysis)
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18
Q

Vector Data Model - Simple Features

A

Representation of point, line, and polygon objects using the vector data model.

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19
Q

Vector Data Model - Topological Feature

A
  • Vector Topological feature = simple features + topological rules
  • Science and mathematics of geometrical relationships used to validate the geometry of vector entities.
  • Topology describes the SPATIAL RELATIONSHIPS between adjacent features (Node (x,y coordinates) to identify the location of a particular point, line, or polygon/ How features share geometry/ Define DATA INTEGRITY RULES)
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20
Q

Vector Data Model - Topological Feature

A

Topology is important to GIS

  • DATA VALIDATION - ensure the data quality
  • MODELING - the integrated behavior of different feature types
  • EDITING PRODUCTIVITY - sophisticated tools
  • OPTIMIZING QUERIES - spatial analysis
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21
Q

Vector Data Model - Topological Feature

A

Data Validation - Data Quality

  • Topological Integrity
  • Network connectivity
  • Line Intersection
  • No Overlap
  • No Duplicate Line

SEE SLIDE

22
Q

Vector Data Model - Topological feature

A
  • Modeling the integrated behavior of different feature types which share common locations and partial identities
  • When multi behaviors of different feature types (points, line, and polygons) happened, but share common boundaries. It can be modeled in multiple objects (separate geometry types) and single features integrated.
    MULTIPLE OBJECTS WITH SEPARATE GEOMETRY, BUT, INTEGRATE THEM FOR EDITING, ANALYSIS, AND REPRESENTATION MORE EFFICIENTLY
    SO, THEY ARE TREATED AS SINGLE FEATURES IN GIS
23
Q

Vector Data Model - Topological Feature

A

Topology is Important to GIS (ex. New Shapefile)

  • Data validation
  • Modeling the integrated behavior of different feature types
  • Editing productivity (support sophisticated editing tools)
  • Optimizing Queries - Spatial Analysis (Network tracing e.g. find all connected water pipes and fittings/ Polygon Adjacency e.g. determine who owns the parcels adjoining those owned by a specific owner/ Containment e.g. find out which manholes lie within the pavement area of a given street/ Intersection e.g. examine which census tracts intersect with a set of health areas).

See EXAMPLES

24
Q

Polygon Topology Model (In Sum)

A

Topologically structure polygon data layer
- each polygon is defined as a collection of polyline with an ordered list of coordinates (vertices)
Storing common boundaries between adjacent polygons
- Benefits: Avoid the potential problems of gaps, avoid overlaps between adjacent polygons.
The downside, however, is that drawing a polygon requires that multiple polylines must be retrieved from the database and then assembled into a boundary
- time consuming and multiple polylines required in big database

25
Polygon Topology Contiguity
Def: polygons on the left- and right-hand side of each polyline, in the direction defined by the list of coordinates Planar enforcement - all the space on a map must be filled and any points must fall in one polygon alone - Polygons must NOT overlap SEE EXAMPLES
26
Vector Geo-Relational Model
See EXAMPLES
27
Network Data Model
- A special type of topological feature model - Store nodes, lines and record the locations of GEOGRAPHIC ENTITIES as x, y, and z coordinates - Network topological relationships define: how lines connect with each other at NODES and rules about how flows can move through the network - Two primary types of networks are: radial/ tree networks: upstream and downstream and looped networks: self-intersection - Examples: Electricity, street, and stream network; tracing water distribution from pump to houses
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Two Primary types of networks
Radial/ Tree networks DRAINAGE SYSTEM or STREAM REFERENCE POWER POINTS FROM THIS POINT ONWARD
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Network Model
Water line network
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network data model
street network
31
Network Data Model
Linear referencing Record the locations as distances along a network from an original point (Called a route system) Benefit: Efficient way to store information such as the surface characteristics Dynamic segmentation: • a special type of linear referencing • data values dynamically added to the route each time when users query the database
32
The Dynamic SEGMENTation Process
``` This is especially useful in situation in which the event data change frequently and need to be stored in a database due to access from other applications (e.g., traffic volumes, rate of pipe corrosion) ```
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Raster and Vector Models (ex)
SEE POWERPOINT
34
Interpolation Methods
- Creating a gridded surface from sample data (points) - Things that are closer together tend to be more alike than things that are farther apart. - Inverse distance weighting (IDW), Natural Neighbor, Spline, and Geostatistical interpolations (Kriging).
35
Inverse Distance Weighting (IDW)
``` - Provide a simple way of guessing the values of a continuous filed at locations where no measurement is available. - The unknown value is estimated by taking averages over the known values ->weighting each known value by its distance from the point, giving greatest weight to the nearest points ->implementation of Tobler’s First Law ```
36
The Function of IDW
SEE POWERPOINT - Notation used in the equations defining spatial interpolation - the estimate is a weighted average - weights: the inverse square of distances/ weights decline with distance
37
Triangular Irregular Network (TIN)
- An alternative to the raster data model for representing continuous surfaces. - Allows surface models to be generated EFFICIENTLY TO ANALYZE. - Display terrain, elevation and other types of surfaces.
38
Components of TIN
- Topological data - Nodes (X,Y,Z) - Edges - Triangles - Neighboring Triangles TIN satisfied the Delaunay Triangulation criterion Vertex, Edge, Face SEE SLIDES
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Delaunay Triangulation Criterion
- Let P be a set of points in the plane. Three points Pi, Pj, PkP are vertices of the same face in the Delaunay graph (empty circle) of P The circle through Pi, Pj, Pkcontains no point of P in its interior. SEE SLIDES
40
TIN: Vector data model
For vector GIS, TINs = polygons - Attributes of slope, aspect, and area, - Three nodes with elevation attributes - Three edges with slope and directional attributes SEE SLIDES
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TIN APPLICATIONs
Visualization/ Viewshed analysis | Volumetric calculation/ Drainage study
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TIN model data
Structure - No smoothing of the original data Limitations - Susceptible to extreme high and low values - Unable to deal with DISCONTINUITY of slope across triangle boundaries - Difficult to CALCULATE OPTIMUM ROUTES
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TIN model data: no discontinuity
Recognizes same features/ Sandy Beach, Water | SEE SLIDES
44
Using the Spatial Models Together
Vector Data Model, Raster Data Model, TIN Data Model <- GEOMETRY-CENTRIC MODELS
45
Why object-oriented data model?
Why geometry-centric models can't satisfy our needs? - Many geographic information contains large numbers of properties, complex relations, and sophisticated behavior. - Separate the attribute/ properties from its behavior/ method. - > Make software and database development tedious, time-consuming and error prone
46
What is object-oriented data model?
- GIS object data model an integrated package of geometry, properties, and methods. -> Geometry is treated like any other attribute of the object - GIS object data model the collection of geographic objects and the relationships between the objects - Three types of relationships -> Topological; Geographic; General - Objects = Classes: because many of the object-oriented characteristics are built at the class level
47
Three major types of relationships
- Topological relationship - Describe the structure (i.e., points, line, polygon, raster, TINs, or network) for building objects. - Geographic relationship - Determine the interaction (i.e., overlap, adjacency, inside, and touching) between objects. - General relationship - Define other types of relationship between objects (i.e., the relationship between data properties and data behaviors)
48
Rules for maintaining object-oriented database integrity
- Attribute rule - Define the possible attribute value that can be entered for any object (e.g., highway traffic speed must be in the range 25-70 miles per hour [range attribute rule]), or pipe material must be of type steel, copper, lead, or concrete [Coded attribute rule]). - Connectivity rule - specify the valid combination of features derived from geometry, topology, and attribute properties. E.g., in an electric distribution system, a 28.8-kV conductor can only connect to a 14.4-kV conductor via a transformer. - Geographic rules - Define what happens to the properties of objects when splitting or merging them
49
Examples of Geographic Rules
Split or Merge | SEE SLIDES
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Example of Water-Facility Object Data Model
SEE SLIDES

GIS I (7 decks)

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