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:
Fire hydrant #22 is located west of Richie Dr. &
south of #21 and north of #23
Absolute Accuracy:
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 surveyedhas 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
GPS unit/ receiver
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”= 50’
1”= 5,000’
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:
- Process of shading your map according to a theme
- 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
- Graduated
- 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
Ranged Thematic maps:
- displays data according to values grouped together
- 4 classifications of Ranged thematic maps
- Natural Break
-Standard Deviation
- Equal Count
- Equal Range
Ranged Thematic map:
Natural Break: Shows data that is NOT evenly
distributed, patterns can be seen
100
-sort data by value
75
V
A
L
U
E
- data values clustered
58
50
- groups by slope
42
- determines range cutoff values
25
- unbiased, scientific method to
determine ranges
8
0
0
5
10
15
OBSERVATION (SORTED BY VALUE)
20
Ranged Thematic map:
Standard Deviation: Shows data that is NOT evenly
distributed, patterns can be seen
mean
1 standard deviation
75
- calculates mean (average) of data values
50
- calculates variance (value of each item minus
the average)
25
- square the deviation (or change from average)
for each data item
0
- divide by number of data items minus 1
(variance)
0
100
200
300
400
500
- 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
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.
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
6.
Grid
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:
Graduated :
-uses symbols to represent different
data values
- can be used with points, lines, or polygons
- works best with numeric values
6.
Grid
Graduated example: :
-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
Pie or Bar Chart :
-uses pie or bar to represent different
data values
-used with polygons only
- can use numeric & nominal values
6.
Grid
Pie Chart example:
-uses pie size to represent different
population data values
and uses black & light gray to
represent male or female
-uses with city polygons
Males
Females
-uses numeric (population)
& nominal values (male/ female)
Same data values
but uses bars instead of pies
Individual :
-Shows points, lines, or polygons
by their unique value
-used with points, lines, or polygons
- can use numeric or nominal values
6.
Grid
Individual :
-Shows neighborhood polygons
by their unique condition value
-used with polygons
- using nominal values
Grid :
- Shows gradational change from
centroid of polygon
- used with polygons
- uses numeric values
6.
Grid
Thematic Map- Grid
Grid example: :
- Shows gradational change of
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.
Read the following exert from
“How to Lie with Maps”