Lecture 5 (Geographic Data Modeling) Flashcards
Geographic Data Modeling
How to represent real life object, data with a CPU
Model
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)
Data Model
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)
Representation
Focus on CONCEPTUAL and SCIENTIFIC ISSUES (when thinking about real world -> GIS model for continuous world and discrete objects)
Role of Data Modeling
1) REAL WORLD -> 2) GIS DATA MODEL (DESCRIPTION AND REPRESENTATION) -> 3) OPERATIONAL GIS (ANALYSIS AND PRESENTATION) -> 4) PEOPLE (INTERPRETATION AND EXPLANATION)
Data Model Levels
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)).
Model Levels and Concerns
- 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)
Modeling Process
Physical Model (Database Schema) -> Real World -> Conceptual Model (Objects and relationships) -> Logical Model (Lists, Diagrams, Flow Charts)
Continuous Fields and Discrete Objects
Two fundamental CONCEPTUAL models in geographic representation (Colorado, USA)
- Raster LOGICAL model
- Vector LOGICAL model
Three generations of GIS data model
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)
GIS Data Models and Applications
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
The earliest GIS Data Models
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
The earliest GIS Data Models
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)
Demo in ArcGIS
Scanned aerial photographs and Digital Satellite Images
Raster Data Model
- 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,
Electromagnetic Energy
Decreasing Wavelength ->
Increasing energy ->
ex. Landsat 8
Vector Data Model - Simple Features
- 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)
Vector Data Model - Simple Features
Representation of point, line, and polygon objects using the vector data model.
Vector Data Model - Topological Feature
- 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)
Vector Data Model - Topological Feature
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
Vector Data Model - Topological Feature
Data Validation - Data Quality
- Topological Integrity
- Network connectivity
- Line Intersection
- No Overlap
- No Duplicate Line
SEE SLIDE
Vector Data Model - Topological feature
- 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
Vector Data Model - Topological Feature
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
Polygon Topology Model (In Sum)
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
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
Vector Geo-Relational Model
See EXAMPLES
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
Two Primary types of networks
Radial/ Tree networks
DRAINAGE SYSTEM or STREAM
REFERENCE POWER POINTS FROM THIS POINT ONWARD
Network Model
Water line network
network data model
street network
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
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)
Raster and Vector Models (ex)
SEE POWERPOINT
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).
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
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
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.
Components of TIN
- Topological data
- Nodes (X,Y,Z)
- Edges
- Triangles
- Neighboring Triangles
TIN satisfied the Delaunay Triangulation criterion
Vertex, Edge, Face
SEE SLIDES
Delaunay Triangulation Criterion
- Let P be a set of points in the plane.
Three points Pi, Pj, PkP 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
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
TIN APPLICATIONs
Visualization/ Viewshed analysis
Volumetric calculation/ Drainage study
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
TIN model data: no discontinuity
Recognizes same features/ Sandy Beach, Water
SEE SLIDES
Using the Spatial Models Together
Vector Data Model, Raster Data Model, TIN Data Model <- GEOMETRY-CENTRIC MODELS
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
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
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)
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
Examples of Geographic Rules
Split or Merge
SEE SLIDES
Example of Water-Facility Object Data Model
SEE SLIDES
