4. Data Models

Front 1

GIS is a system designed to...

Back 1

efficiently capture, store, manipulate, analyze, and display geographically referenced information

Front 2

what 5 things does GIS include?

Back 2

1. hardware
2. software
3. data
4. people
5. methods
   

Front 3

what are the 2 major classes of spatial data?

Back 3

vector and rastor

Front 4

in the vector model, spatial entities are represented as...

Back 4

3 types of features:

1. points
2. lines
3. polygons

Front 5

vector data

Back 5

an example of an object in a data model (e.g. objects such as houses, roads, ponds, etc.)

Front 6

raster data

Back 6

an example of a field data model (e.g. elevation, rainfall, vegetation)

Front 7

points are represented by...

Back 7

an X-value and a Y-value

Front 8

lines are represented by...

Back 8

a series of connected "X-Y" values (nodes and vertices)

Front 9

the lines connecting the X-Y values in line features are called _______

Back 9

arcs

Front 10

polygons are represented by...

Back 10

areas bounded by lines

Front 11

what are the 2 types of vector data models?

Back 11

1. spaghetti data model
2. topological model

Front 12

spaghetti data model

Back 12

• stores coordinates of each data structure separately

• no spatial relationships stored

Front 13

topological model

Back 13

• lines share connecting nodes

• polygons share adjacent borders

• explicitly defines spatial relationships

Front 14

attributes data is stored in _________

Back 14

tables

Front 15

table columns are called __________

Back 15

fields

Front 16

table rows are called ___________

Back 16

records

Front 17

table records are linked to __________

Back 17

features

(each record is associated with one and only one feature)

Front 18

what are the 3 attribute data types?

Back 18

1. text

2. integer

3. floating point

Front 19

text

Back 19

descriptive information/categorical

Front 20

integer

Back 20

ordered data, counts, etc.

Front 21

floating point

Back 21

continuous

Front 22

what are the 2 types of raster data?

Back 22

1. discrete
2. continuous

Front 23

what is discrete raster data?

Back 23

unique categories (qualitative)

Front 24

what is continuous raster data?

Back 24

large—or possibly infinite—number of values (quantitative)

Front 25

[ raster data ]

space is modeled as...

Back 25

a grid of equal-sized cells

Front 26

[ raster data ]

each cell is known by...

Back 26

its row and column location

Front 27

[ raster data ]

where is the origin usually?

Back 27

upper left corner

Front 28

[ raster data ]

each cell has __________ value(s) and the values are coded to ______________

Back 28

each cell has one and only one value and the values are coded to land cover, road types, etc.

Front 29

[ vector-raster conversion ]

while vector point is represented by __________, raster point is represented by _____________

Back 29

while vector point is represented by an X-Y value, raster point is represented by a grid cell that has a predefined set of dimensions

Front 30

[ vector-raster conversion ]

while vector line is represented by __________, raster line is represented by _____________

Back 30

while vector line is represented by a series of connected points, raster line is represented by grid cells that contain the line feature

Front 31

[ vector-raster conversion ]

while vector polygon is represented by __________, raster polygon is represented by _____________

Back 31

while vector polygon is represented by connected arcs that begin and end at the same node, raster polygon is represented by grid cells in which the polygon feature is a majority

Front 32

what is 1 problem with data conversion?

Back 32

some features (ponds, small canopy openings, rare vegetation types) can be lost entirely if they are smaller than the cell size

Front 33

[ changing cell size ]

decreasing cell size enhances _____________, but ____________ also increase rapidly

Back 33

decreasing cell size enhances spatial resolution, but data storage requirements and time required for processing and display also increase rapidly

Front 34

the raster data model with continuous data

Back 34

• some spatial data (elevation) varies continuously across the landscape

• can be difficult to represent using a vector-based data model with homogeneous polygons

• instead, record mean elevation of evenly-spaced grid cells

Front 35

attributes of raster data

Back 35

• does not have true attribute tables

• uses a look-up table instead

Front 36

list 3 advantages of raster data

Back 36

1. simple data structure
2. represents continuous surfaces well
3. complex overlays with multiple data layers are faster

Front 37

list 3 disadvantages of raster data

Back 37

1. large data storage requirements

2. represents objects poorly

3. boundaries not very exact

Front 38

list 3 advantages of vector data

Back 38

1. compact data structure
2. precise representation of feature locations and boundaries
3. explicit topology...easy to tell what is next to what
   

Front 39

list 3 disadvantages of vector data

Back 39

1. complex data structure

2. not good for representing gradual trends

3. spatial overlays are time consuming

Front 40

when should you use raster data?

Back 40

• when you need to represent continuous surfaces
• when you need to perform complex analyses or develop spatial models using many different data sets
  

Front 41

when should you use vector data?

Back 41

• the boundaries between features and the shapes of the features themselves are important

• when you need to know what features are adjacent to one another

• when you need accurate measurements of area, length, and direction are important