# 6. Grid - PowerPoint PPT Presentation

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6. Grid. Positional Accuracy: degree of error between a modeled location (as seen in the GIS) and the actual location. 1. Relative Accuracy- relationship between visible spatial objects is correct 2. Absolute Accuracy- position of each spatial object is

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6. Grid

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6. Grid

Positional Accuracy: degree of error between a modeled location

(as seen in the GIS) and the actual location.

1. Relative Accuracy- relationship between visible spatial

objects is correct

2. Absolute Accuracy- position of each spatial object is

location is exact

Component Accuracy: completeness and integrity of all spatial

& attribute data

ie. When were the parcel objects updated to show changes?

Does the attribute data include updated data for this year?

Does your map only show the “positives” and not potential

problems? (Read – “How to Lie with Maps”).

Relative Accuracy:

Absolute Accuracy:

Fire hydrant #22 is located west of Richie Dr. &

south of #21 and north of #23

Fire hydrant #22 is located at

41.145367 N , 81.98634 W

Factors that can affect the positional accuracy of spatial data input:

1. Survey monuments

2. Global Positioning System (GPS)

3. Map scale

4. Map projection

Survey monuments: 2 to 3” pin in road, ground, etc. that was surveyed-

has some known x,y location values and elevation

The monuments are used as control points

for data input.

More monuments allows for more controls

points and more positional accuracy

Global Positioning System

24 satellites

in earth orbit

GPS:

captures locational positions

within 1 cm to few hundred yards

can increase control points &

thus increase the positional accuracy

of spatial objects in the data input process

Map Scale: measure of the distance on the paper map representing

the distance in real world

If map is digitized at a scale of 1” = 50’, will the digitized product

be more positionally accurate than a map digitized at a scale of 1” = 5000’????

1”= 5,000’

1”= 50’

Map Projections: process to transform 3 dimensional surface to

a 2 dimensional surface

Map projections will emphasize different aspects of accuracy:

Equal area projections display the geographic areas to show relative size

Directional projections allow navigation from place to place

If the study area for the GIS project is a “small” geographic area, any map projection

is acceptable for data input:

Equal Area Projection

Directional Projection

Display Information using Thematic Maps:

• Shading can be by color, black & white, patterns, dots, or symbols

• Uses values of data to allow comparisons of data and see patterns

• Variety of thematic options to display the same data.

• Thematic map types:

• Ranged

• Dot Density

• Pie or Bar chart

• Individual

• Grid

Thematic Map example:

Thematic maps:

- Use number values or nominal values

- Nominal values are name values and are usually character fields

ie. In a basement flooding database, a field called

condition may have the value of Flood or Not Flood

- Data displayed on the map is called a thematic variable

- In most thematic maps, one variable is mapped,

however 2 or more variables can be mapped.

• Thematic map types: Ranged, Dot Density, Graduated, Pie or Bar chart, Individual, Grid

RangedThematic maps:

• displays data according to values grouped together

• 4 classifications of Ranged thematic maps

• Natural Break

• Standard Deviation

• Equal Count

• Equal Range

RangedThematic map: Natural Break: Shows data that is NOT evenly distributed, patterns can be seen

100

75

50

25

0

• sort data by value

• data values clustered

• groups by slope

• determines range cutoff values

• unbiased, scientific method to

• determine ranges

V

A

L

U

E

58

42

8

05101520

OBSERVATION (SORTED BY VALUE)

RangedThematic map: Standard Deviation: Shows data that is NOT evenly

distributed, patterns can be seen

mean

1 standard deviation

75

50

25

0

• calculates mean (average) of data values - calculates variance (value of each item minus

• the average) - square the deviation (or change from average)

• for each data item

• - divide by number of data items minus 1

• (variance) - take square root of variance= standard deviation

• - each standard deviation above/ below are used to

• determine the set of ranges in the thematic map

• - unbiased, scientific method to determine ranges

0 100 200 300 400 500

Equal Count:

Same number of records

are placed in each range

Good to use if you need number

of data records divided into

equal amounts.

ie. You want the same number of

tracts in each range so that you can

assign 4 workers an equal work

load for research in more detail.

Equal Range:

Divides the records across ranges

of equal size

Good to use if you need to determine

how many records fall within each

range of equal size

ie. You want the number of

tracts in each equal interval

range.

6. Grid

• Dot density :

• uses dots to represent data value

• associated with a polygon

• only used with polygons

• very useful map type to show

• densities of values

• Total number of dots represent

• the polygon’s data value

• ie. Population by city

• Pop. in Berea = 15,000 people

• if 1 dot = 150 persons, there

• should be 100 dots in the

• polygon for Berea.

Ways to change how data

is displayed on dot density maps:

1. Dot value

2. Dot size

3. Dot color

4. Dot shape

Changing the Dot value

Which dot value shows population

densities best???

1 dot = 1000 persons

1 dot = 150 persons

1 dot = 300 persons

Dots too small

Dots too large

Which dot density map

shows the densities best????

Value too small

Value too large

Dot value & size- just right

Changing the Dot Size:

6. Grid

• uses symbols to represent different

• data values

• can be used with points, lines, or polygons

• works best with numeric values

• uses varying symbol size to represent

• different population values per city

• used with city polygons

• works best with numeric values for

• the size of circle

6. Grid

• Pie or Bar Chart :

• uses pie or bar to represent different

• data values

• used with polygons only

• can use numeric & nominal values

• Pie Chartexample:

• uses pie size to represent different

• population data values

• and uses black & light gray to

• represent male or female

• uses with city polygons

• uses numeric (population)

• & nominal values (male/ female)

Males

Females

Same data values

but uses bars instead of pies

6. Grid

• Individual :

• Shows points, lines, or polygons

• by their unique value

• used with points, lines, or polygons

• can use numeric or nominal values

• Individual :

• Shows neighborhood polygons

• by their unique condition value

• used with polygons

• using nominal values

6. Grid

• Grid :

• centroid of polygon

• used with polygons

• uses numeric values

Thematic Map- Grid

• Grid example: :

• population from

• centroid of polygon

• used with tract polygons

• uses numeric values

• colors are based interpolated

• values between centroids

Maps can mislead if you are

not careful or are unscrupulous.