Lecture 5 (Geographic Data Modeling) Flashcards Preview

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Flashcards in Lecture 5 (Geographic Data Modeling) Deck (50)
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1

Geographic Data Modeling

How to represent real life object, data with a CPU

2

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)

3

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)

4

Representation

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

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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)

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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)).

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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)

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Modeling Process

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

9

Continuous Fields and Discrete Objects

Two fundamental CONCEPTUAL models in geographic representation (Colorado, USA)
- Raster LOGICAL model
- Vector LOGICAL model

10

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)

11

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

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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

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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)

14

Demo in ArcGIS

Scanned aerial photographs and Digital Satellite Images

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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,

16

Electromagnetic Energy

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

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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)

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Vector Data Model - Simple Features

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

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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)

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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

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Vector Data Model - Topological Feature

Data Validation - Data Quality
- Topological Integrity
- Network connectivity
- Line Intersection
- No Overlap
- No Duplicate Line

SEE SLIDE

22

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

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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

24

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

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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

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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

30

network data model

street network