LECTURE 3: COVERAGES

1. FLAT-FILE GIS

Canada Geographic Information System

magnetic tape storage

reduce a map to a linear sequence of bits

all maps classified land

soil capability

forest capability

recreation capability

current land use

...

maps scanned as rasters

vectorized for compression, calculation of area, apparent accuracy

the arc as the basic record

strung end to end on tape

left poly ID, right poly ID, number of points, x,y,x,y,x,y,x,y,...

all input and output involved tape


2. THE RELATIONAL MODEL

Database management systems

pre-1970s
programs handled input and output

commands to read, write hard disk, diskettes, tapes

a GIS had to do its own

many lines of code

the database approach

all reading and writing through a simple interface

no need for user to care about details of disk, tape etc

easy to replace database layer

with another vendor's product
database handles basic housekeeping

knows the details of format

knows about variables

e.g. house price

knows units of measurement

knows range (negatives not possible)

can export data to another system easily
"export" command
enables simple operations

total a column of numbers

search for records satisfying some condition

Need a model of what data look like

the relational model

emerged in the 1980s as the dominant model

replaced the hierarchical and network models
Oracle, Access, Informix, Empress, ...
What does the relational model assume about data?

needs to be widely applicable, so can't assume too much

must assume something, or it wouldn't be useful

1. Data consist of tables (relations)

the rows define the cases, objects, instances, records of some class of objects

the columns define the known properties or attributes

all of the objects in the class must have the same kinds of properties

in GIS, must be all points, all lines, all areas, all pixels, etc.
Flight arrangements for Presidential inauguration in Washington, Jan 20

5 attendees (rows)

4 attributes (columns)

       Name                      Airport                   Flight                      Date
 
Obama ORD 2372 Jan 6
McCain PHX 145 Jan 18
Kerry BOS 58 Jan 18
Clinton LGA 5136 Jan 19
Penn LAX 226 Jan 19

What can go in the columns?

data (integers, floats, dates, text)

BLOBs (images, music, video)

hyperlinks to web sites

links to initiate programs

e.g. links to GIS

compare Excel

2. Applications can involve several tables

passengers with reservation details

aircraft with maintenance, schedule details

crew with schedule, pay details

a model of an enterprise

county data (polygons)

customer data (points)

road data (lines)

3. Tables can be linked through common keys

flight number in a passenger record

flight number in a crew record

flight number in an aircraft record

When was the aircraft that will carry McCain last maintained?

passenger table relates McCain to a flight

aircraft record relates flight to an aircraft

user doesn't need to know these are in separate tables

Example of two tables

A GIS example:

table of car accidents

county as an attribute
table of counties

link any accident to attributes of the county it occurred in

county as the common key

Core concepts of the relational model
relation
a table
tuple

a record in a table

a row in a table

key
a subset of attributes that is

unique for each record

no redundancy

can't throw away any attribute in the key
e.g. phone directory

phone number is unique key

last name, first name, street address is unique

drop any part and the result is not necessarily unique

still possible to be non-unique?

join

merger of two tables

using key to add attributes from Table 2 to records of Table 1

not symmetrical

number of records in join is determined by Table 1
reversible

normalization

spatial join

use location as the common key

match point to point, point to polygon, polygon to polygon

Advantages of the relational model

very flexible

no need to worry about implementation

user can ask questions that involve more than one table

linkage of tables is automatic


3. COVERAGES

The relational model applied to GIS

the georelational model

representing maps in the relational model

ARC/INFO circa 1980

Components:

polygons

arcs

nodes

 Coverage slide 1

 Coverage slide 2

 Coverage slide 3

Using arcs as the basic unit

avoids double representation of internal boundaries

easier to build the database

easier to edit and maintain

keeps track of 'topology'

which nodes are connected by which arcs

which polygons are separated by which arcs

Topology
a concept strongly associated with the coverage model
coverages have more topology than shapefiles
1) relationships between objects
every arc points to two polygons
the "outside world" is a special polygon

every arc ends at two nodes

nodes have any number of arcs

but sometimes limited to three
polygons have any number of arcs
but sometimes limited by design
Euler's Theorem
P-A+N=2
or 1 if the outside world is not counted
2) integrity of objects
polygons must be closed
building topology
assembling lines into arcs and polygons

forming junctions

removing overshoots

Coverage tables

Polygon attribute table (PAT)

Arc attribute table (AAT)

Tics (TIC)

Annotation (LAB)

Tolerances (TOL)

INFO relational database

Microsoft Access

Handling arcs in coverages

shapes (points) stored in special file (ARC)

not directly viewable

Data that fit the coverage model

all points within one polygon have the same attributes

all points must lie in exactly one polygon

a field

values at each point are classes

a categorical coverage

an area class map

resource management

forest stands

soil type

vegetation cover class

land use class

the cadaster
land ownership parcels
demographics

census data

data by state

data by county

marketing data by market area

population by ZIP

the choropleth map

the area class map

coverages capture the field view of the world

a continuous world

one value of a variable at every point

sharp changes in value as boundaries are crossed

Other types of coverages (classic ARC/INFO)

points

lines

arcs

TINs

grids