Introduction to Geographic Information Systems

- Miles Logsdon
- mlog_at_u.washington.edu

http//sal.ocean.washington.edu/

Spatial Information Technologies

- Geographic Information Systems GIS
- Global Positioning System GPS
- Remote Sensing and Image Processing - RS

Technologies to help answer

- What is here? give a position
- What is next to this? given some

description - Where are all of the ??? detecting or finding
- What is the spatial pattern of ???
- When X occurs here, does Y also occur?

GIS

Geographic Information System

GIS - A system of hardware, software, data,

people, organizations and institutional

arrangements for collecting, storing, analyzing,

and disseminating information about areas of the

earth. (Dueker and Kjerne 1989, pp. 7-8)

- GIS - The organized activity by which people
- Measure aspects of geographic phenomena and

processes - Represent these measurements, usually in a

computer database - Operate upon these representations and
- Transform these representations. (Adapted from

Chrisman, 1997)

A KEY POINT Geo-referenced Data

GIS - consists of

- Components
- People, organizational setting
- Procedures, rules, quality control
- Tools, hardware software
- Data, information
- Functions
- Data gathering
- Data distribution

Common short hands

- CAM- Computer Aided Mapping
- AM - Automated mapping
- CAD - Computer-Aided Design
- LIS - Land Information Systems
- AM/FM - Automated Mapping/Facilities Management

Systems

- RS - Remote Sensing
- aerial Photography
- Photogrammetry
- Photo interpretation
- Thermal sensing
- Radar imaging
- Satellite Remote Sensing
- Meteorological
- Terrestrial
- Image Processing

Geographic Data

- Spatial Data
- location
- shape
- relationship among features

- Descriptive Data
- attributes, or
- characteristics of the features

After Sinton, 1978 Components of spatial

information time, space, theme

(attribute) Sounds obvious. useful starting

point to remember Role of these Dimensions One

must be fixed, one controlled, one measured.

Components of Spatial Data

Temporal examples Control Measure Time

(hour) Attribute (water level) strip chart

(stream guage) The Basic Spatial Data Structures

Control Measure Location

Attribute gt Raster (Location controlled by

grid) Attribute Location gt Categorical

coverage (Vector) Indirect measurement

Control Measure First Attribute

Location gt Categorical Coverage (eg. land use

category) Second Category Attribute gt

Estimate for category (eg. Corn

yeild) Composite Measurement Control

Measure First Attribute Location gt

Collection Zones (eg. counties) Second

Location Attribute gt Choropleth (eg. vote

for Initiative 187)

DATA - more than one DATUM - only one item,

or record

- Three Attributes of Data
- Thematic (Value Variable)
- Nominal, name, label
- Ordinal, rank ordered
- Interval / Ratio, measurement on a scale
- Spatial (location)
- Temporal

Spatial Data the spatial attribute is

explicitly stated and linked to the thematic

attribute for each data item.

Spatial - thematic value types

200

Sta. 94, DOC 4.9

Stream,3

Former Land Fill

100

FOREST

URBAN

Duvall, pop 1170

Brush Creek, 2

FOREST

AGRICULTURE

100

200

Snoqualmie River, 1

WELL

Geographies

Layers, Coverages, Themes

Land use

Soils

Streets

Hydrology

Parcels

Concept of Spatial Objects

- POINTS
- LINES
- AREA

Spatial Encoding - RASTER

POINT

0

0

0

0

0

1

0

0

0

5

5

3

AREA

3

3

1

1

1

2

LINE

1

0

0

0

1

0

1

0

Spatial Encoding - VECTOR

a single node with NO area

POINT

- x, y

- x1, y1 - x2, y2 . . - xN, yN

LINE

a connection of nodes (vertices)

beginning with a to and ending with a

from

(Arcs)

Area (Polygons)

a series of arc(s) that close around a

label point

- x1, y1 - x2, y2 . . - xN, yN (closure Point)

Vector - Topology

Descriptive

Spatial

Object

VAR1 VAR2

1 2 3

x1,y1 x2,y2 x3,y3

1 2 3

VAR1 VAR2

Fnode Tnode x1y1, x2y2

1

1 2

1 2

1 2 xxyy, xxyy 2 3

xxyy,xxyy

3

2

2

1

VAR1 VAR2

2

3

1 2

1 2

10, 11, 12, 15 10, .

15

10

1

4

12

5

11

Raster Data Model

Set Selections

1 2 3 4 5 6 7 8 9 10

Reduce Select - RESEL GT 5 6 7 8 9 10 Add

Select - ASEL EQ 5 5 6 7 8 9

10 Unselect - UNSEL GE 9 5 6 7 8

Null Select - NSEL 1 2 3 4 9 10

AND, OR, XOR

Spatial Overlay - UNION

1

1

2

1

3

6

2

4

5

2

3

7

8

11

3

12

9

10

4

5

13

14

16

17

15

A B C D

102 103

102 A

A 102 B

102

Spatial Overlay - INTERSECT

1

1

1

2

2

2

3

3

4

5

3

6

7

4

5

8

9

A B C D

102 103

A 102 B

102 A 103 B

103

Spatial Overlay - IDENTITY

1

1

1

2

5

2

3

4

2

3

6

7

3

8

9

4

5

10

11

12

13

A B C D

102 103

A A

102 B 103 B

Spatial Poximity - BUFFER

Constant Width

Variable Width

Spatial Poximity - NEAR

Assign a point to the nearest arc

Spatial Proximity - Pointdistance

DISTANCE

2,045 1,899 1,743

1 2 3

1 2 3

Spatial Proximity - Thiessen Polygons

Map Algebra

- In a raster GIS, cartographic modeling is also

named Map Algebra. - Mathematical combinations of raster layers
- several types of functions
- Local functions
- Focal functions
- Zonal functions
- Global functions
- Functions can be applied to one or multiple layers

Local Function

- Sometimes called layer functions -
- Work on every single cell in a raster layer
- Cells are processed without reference to

surrounding cells - Operations can be arithmetic, trigonometric,

exponential, logical or logarithmic functions

Local Functions Example

- Multiply by constant value

2 0 1 1 2 3 0 4

1 1 2 3 2

6 0 3 3 6 9 0 12

3 3 6 9 6

X 3

- Multiply by a grid

2 0 2 2 3 3 3 3

2 2 2 1 1

4 0 2 2 6 9 0 12

2 2 4 3 2

2 0 1 1 2 3 0 4

1 1 2 3 2

X

Focal Function

- Focal functions process cell data depending on

the values of neighbouring cells - We define a kernel to use as the neighbourhood
- for example, 2x2, 3x3, 4x4 cells
- Types of focal functions might be
- focal sum,
- focal mean,
- focal max,
- focal min,
- focal range

Focal Function Examples

- Focal Sum (sum all values in a neighborhood)

2 0 1 1 2 3 0 4 2

1 1 2 2 3 3 2

(3x3)

16 13

17 19

- Focal Mean (moving average all values in a

neighborhood)

2 0 1 1 2 3 0 4 4

2 2 3 1 1 3 2

1.8 1.3 1.5 1.5 2.2 2.0 1.8 1.8 2.2 2.0

2.2 2.3 2.0 2.2 2.3 2.5

(3x3)

Zonal Function

- Process and analyze cells on the basis of zones

- Zones define cells that share a common

characteristic - Cells in the same zone dont have to be

contiguous - A typical zonal function requites two grids
- a zone grid which defines the size, shape and

location of each zone - a value grid which is processed
- Typical zonal functions
- zonal mean,
- zonal max,
- zonal sum,
- zonal variety

Zonal Function An Example

- Zonal maximum Identify the maximum in each zone

2 2 1 1 2 3 3 1

3 2 1 1 2 2

1 2 3 4 5 6 7 8 1

2 3 4 5 6 7 8

5 5 8 8 5 7 7 8

7 5 8 8 5 5

Useful when we have different regions

classified and wish to treat all grid cells of

each type as a single zone (ie. Forests, urban,

water, etc.)

Global function

- In global functions -
- The output value of each cell is a function of

the entire grid - Typical global functions are distance measures,

flow directions, or weighting measures. - Useful when we want to work out how cells

relate to each other

Golbal Function An Example

- Distance Measures Euclidean distance based upon

cell size

1 1 1

2

2 1 0 0 1.4 1 1 0 1

0 1 1 1.4 1 1.4 2

Or some function which must consider all cells

before determining the value of any cell

(cost associated with a path across the surface)

Examples

outgrid zonalsum(zonegrid, valuegrid) outgrid

focalsum(ingrid1, rectangle, 3, 3) outgrid

(ingrid1 div ingrid2) ingrid3

Spatial Modeling

- Spatial modeling is analytical procedures applied

with a GIS. Spatial modeling uses geographic data

to attempt to describe, simulate or predict a

real-world problem or system. - There are three categories of spatial modeling

functions that can be applied to geographic

features within a GIS - geometric models, such as calculating the

Euclidean distance between features, - coincidence models, such as topological overlay
- adjacency models (pathfinding, redistricting, and

allocation) - All three model categories support operations on

spatial data such as points, lines, polygons,

tins, and grids. Functions are organized in a

sequence of steps to derive the desired

information for analysis. - The following references are excellent

introductions to modeling in GIS - Goodchild, Parks, and Stegaert. Environmental

Modeling with GIS. Oxford University Press, 1993. - Tomlin, Dana C. Geographic Information Systems

and Catograhic Modeling. Prentice Hall, 1990.