Transcript No Slide Title

Data Modeling for Spatial Analysis
• What is spatial analysis?
– "a set of methods whose results change when the
locations of the objects being analyzed change"
• Methods for working with spatial data
– to detect patterns, anomalies
– to find answers to questions
– to test or confirm theories
• deductive reasoning
– to generate new theories and generalizations
• Inductive reasoning
What is Spatial Analysis (cont.)
• Methods for adding value to data
– in doing scientific research
– in trying to convince others
• A collaboration between human and
machine
• How do we set up the framework for
spatial analysis?
– Data model to data structure
A Georelational to a Geodatabase Model
• coverage and shapefile data structures
– homogenous collections of points, lines, and
polygons with generic, 1- and 2-dimensional
"behavior"
• can’t distinguish behaviors
– Point for a marker buoy, same as point for OBS
• “smart features” in a geodatabase
– lighthouse must be on land, marine mammal
siting must be in ocean
Purpose of Arc Marine, Arc Hydro
and others
• basic template for implementing GIS
projects
– input, formatting, geoprocessing, creating maps,
performing analyses
• basic framework for writing program
code and maintaining applications
– development of tools for the community
• promote networking and data sharing
through established standards
“Generic”
Marine Data Model
User Group
Data Model
Project
Data Model
User Group
Data Model
Project
Data Model
User Group
Data Model
Project
Data Model
Inheritance
Arc Marine Design Strategy
Geodatabase Concepts
• ESRI's new data object-oriented data model
– objects, features, behaviors
• Geodatabase
– collection of feature classes/data sets, rasters, TINs
– all data in relational tables
– behavior is coupled with features through rules (object-orientation
• Feature data set
– Contains feature classes
– defines topological role of features
– has a coordinate system
• Feature class
– stored in a relational table
– special field for geometric shape
– geometric data incorporated into the database
• Point, multipoint, segment, path, ring, polyline, polygon,
• Zeiler p. 114
Geodatabase Feature Class
Geometries
ArcMarine Geodatabase
Overall Geodatabase
Feature
Dataset
Feature
Class
Table
Relationship
Class
Modeling Process
Conceptual Model
Lists, flow diagrams, etc
Real World
Objects and
relationships
Logical Model
Diagram in
CASE Tool
Physical
Model
Database
Schema
(Object state)
Graphic courtesy of ESRI
Data Model Levels
Humanoriented
Reality
Conceptual Model
Increasing
Abstraction
Logical Model
Computeroriented
Physical Model
Specific Steps in Data Modeling
(1) Conceptualize the user's view of data
– what are the basic features needed to solve the
problem?
(2) Select the geographic representation
– points, lines, areas, rasters, TINs
(3) Define objects, features, and relationships
– draw a UML diagram, specify relationships,
“behaviors”
(4) Match to geodatabase elements
– Refine relationships, “behaviors”
(5) Organize geodatabase structure, add data
( 1 ) User’s View of Data
( 1 ) User’s View of Data cont.
(2)
Select
geographic
rep.
Steps in Data Modeling
(1) Conceptualize the user's view of data
– what are the basic features needed to solve the
problem?
(2) Select the geographic representation
– points, lines, areas, rasters, TINs
(3) Define objects and relationships
– draw a UML diagram, specify relationships,
“behaviors”
(4) Match to geodatabase elements
– Refine relationships, “behaviors”
(5) Organize geodatabase structure, add data
Unified Modeling Language
• Entity-relationship diagrams
• Design methodologies, diagram
notations
• UML
– Not a design methodology
– Just a diagrammatic notation based on methods
– Endorsed by leading software and database
companies
• HTML