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Transcript
CE 250 - Introduction to Surveying
and
Geographic Information
Systems
eLearning Version
Donald J. Leone, Ph.D., P.E.
Lecture 3
Introduction





What are databases and database
management systems (DBMS)?
What is a relational data base model?
How are databases linked with GIS?
How do we get paper maps into the
computer?
How can we edit and convert data?
Databases

Spatial Data – “Where things are”
Attribute Data – “What things are”
Attribute Data – Stored in databases

Def: Database – “A set of structured


data – usually in table form”, or
“ A Collection of related data”
Traditional Database Example
Traditional Databases
Some Problems

Duplication of Data

High Maintenance Costs

Data Sharing Difficulties

Lack of Security and Standards
Computer Based Databases






Different data access methods will be
available.
Are independent of application.
Unnecessary duplication of data –
minimized.
Access controlled and centralized.
Maintaining and Updating relatively
easy.
Can ask questions - “query”
Database Approach
Database Data
DBMS
Database Management
System
Hotel
Ski School
Travel
Booking
Booking
Arrangements
Application
Database Management Systems
Functions





File Handling/management
Adding/deleting/updating records
Extraction of data (sorting,
querying)
Maintenance (security, backup)
Application building
Data Base Table
PIN Owner Address
Sale
Date
Acres Zone Zoning
Code
P101
Wang
101 Oak St.
1-10-98
1.0
1
Res.
P101
Chang
200 Maple
St.
1-10-98
1.0
1
Res.
P102
Smith
300 Spruce
Rd.
10-6-68
3.0
2
Com.
P102
Jones
100 Ash St.
10-6-68
3.0
2
Com.
P103 Costello
206 Elm St.
3-7-97
2.5
2
Com.
P104
300 Spruce
St.
7-30-78
1.0
1
Res.
Smith
Separate Data Tables – A Relational Database
PIN
Zone Code
PIN
Owner name
Owner name
Zone Code
Creating a New Table
Key Field
Joined Table
PIN Owner Address
P101
Wang
101 Oak St.
P101
Chang
200 Maple
St.
P102
Smith
300 Spruce
Rd.
P102
Jones
100 Ash St.
P103 Costello
206 Elm St.
P104
300 Spruce
St.
Smith
Creating New Tables – “The Query”



Standard Query Language – SQL
Generate New tables
Advantages:



Completeness, Simplicity
Style, Wide Application
Disadvantages:


Slow, Difficult to implement
Can’t Handle geographic concepts, i.e. “near to”
Parcel Table
PIN
Sale
Date
P101
1-10-98
1.0
1
P102
10-6-68
3.0
2
P103
3-7-97
2.5
2
P104
7-30-78
1.0
1
Acres Zone
Code
“Which Parcels (PINS) have 2 or more acres?”
Create a New Table Using SQL
“Acres” =>2.0
Query:
Result:
PIN
Sale
Date
Acres Zone
Code
P102
10-6-68
3.0
2
P103
3-7-97
2.5
2
Creating a Database
1. Data Investigation – Fact finding.
2. Data Modeling – Relationships
between entities and attributes –
Define Tables.
3. Database Design – Fit data
modeling to software at hand.
4. Database Implementation – Filling
in the actual data.
Data Modeling
Entity Attribute Modeling (EAM)
1. Identification of Entities
2. Identification of the Relationship between
entities (1:1, 1:M, M:1, M:N)
3. Identification of the Attributes of the
entities
4. Development of the Tables
EAM for Ski Resort
1. Entitles – Hotels, Travel Companies,
Ski Schools, Visitors
2. Relationships
a) Many visitors stay at One hotel (M:1)
b) One Travel Co, organizes for Many visitors
(1:M)
c) One Ski School teaches Many visitors (1:M)
d) Different Travel Co.s may use Different
Ski Schools (M:N)
EAM Diagram
N
d
b
a) Many visitors stay at One hotel (M:1)
b) One Travel Co, organizes for Many
visitors
(1:M)
c) One Ski School teaches Many visitors
(1:M)
d) Different Travel Co.s may use
Different Ski Schools (M:N)
c
a
Attributes of the Entities
HOTEL (Hotel ID, Name, Other Attributes)
TRAVEL CO. (Travel Co. ID, Travel Co. Name,
Other Attributes)
SKI SCHOOL (Ski School ID, Ski School Name,
Other Attributes)
VISITOR (Visitor ID, Visitor Name, Hotel ID,
Travel Co. ID, Ski School ID, Other Attributes)
LINK (Travel Co. ID, Ski School ID)
Ski Resort Tables
Linking Spatial and Attribute Data
Database Applications
Single User/PC
Simple Software
Large Computers
Large Corporate
Databases
Control Access
Manage Data
Security
Different Sites
Little Grey Cells Quiz



SQL stands for standard question link. T or F
One of the functions of a DBMS is to allow
several applications access to the data. T or F
Give one advantage of a computer database
over a “traditional” database.
Break!
Getting the Data Into The Computer
Data Input (Encoding) and Editing
ANALOG

What is data encoding?



DIGITAL
How are paper maps digitized?
How are paper maps scanned?
Methods of Data Editing and Conversion
Maps
Satellite Data
Digitizing
Digital Data
Scanning
Data Encoding
Tabular Data
Data Transfer
Soft Ideas
Key Coding
Data Capture
Methods
Editing/Cleaning
Re-Projection
Data Editing
Generalization
Edge Matching and Rubber Sheeting
Layering
Integrated GIS
Database
Data Encoding Methods
Digitizing




Tracing over a
map with a
cursor.
Mechanical
Device with a
Human
Operator.
Most errors
operator
induced.
Produces A
Vector Map.
Data Encoding Methods
Scanning
Some problems with scanning (automatic
digitizing)




Distortion.
Automatic scanning of unwanted images.
Produces a raster image- can be vectorized
with some problems.
Amount of editing required to produce
suitable spatial data.
University of Hartford Aerial Photo
Sports Center
HJG Center
UT Hall
Ground Truthing Points
Scanning
Original Paper Map
Scanned Image
Data Encoding Methods
Electronic Data Transfer



What data exist?
How much they cost?
What format will it be in?
Pay off – Considerable time and
effort saved!
Data Editing Methods
Detecting and Correcting Errors





Missing or Duplicate Features
Mislocated Features
Missing or Duplicated Labels
Unwanted Results of Digitizing
or Scanning
Noise
Errors in Vector
Data
Errors in
Raster Data
Noise
Original “noisy” data
3 x 3 Mean Filter
9 x 9 Mean Filter
Producing a Common Reference

Re-Projection

Transformation

Generalization
Producing a Common Reference
Re-Projection
All data needs to be referenced to the
same projection.
Trying to Overlay Different
Projections
Cylindrical
Conic
Producing a Common Reference
Re-Projection
All data needs to be referenced to the same
projection.
Transformation
All data needs to have the same origin.
Producing a Common Reference
Re-Projection
All data needs to be referenced to the same
projection.
Transformation
All data needs to have the same origin.
Generalization
All data needs to be set to the same
scale.
Remaining Problems After Re-Projection,
Transformation, and Generalization
Edge Matching
Remaining Problems After Re-Projection,
Transformation, and Generalization
Rubber Sheeting
An Integrated Database
Ski Resort Example
Layer Name
Source
Data Model
Infrastructure
Scanned –
1:5000
Raster
Hotels
Survey Data
Vector
Ski Schools
Survey Data
Vector
Weather Stations
GPS Data
Vector
An Integrated Database
Ski Valley Example
Layer Name
Source
Data Model
Roads
Digitized 1:25000
Vector
Ski Trails
Digitized
Aerial Photos
Vector
Ski Resort
Boundary
Digitized 1:25000
Vector
Topography
File Transfer
1:25000 DTM
Vector/Raster
Land Use
Satellite Image
Raster
Summary





What are databases and data base
management systems (DBMS)?
What is a relational data base model?
How are databases linked with GIS?
How do we get paper maps into the
computer?
How can we edit and convert data?
What’s Next

Up to now – Data Formation

Data Analysis – Decision Making