C A R T O G R A P H Y P O R T F O L I OJ e n i f e r B o d e F a l l 2 0 0 5

Cartographic Communication Cycle

Real World vs. Percieved World

Map User

Map

Cartographer

map

interpretation

map

readin

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mapdesign

dataco

llectio

n

A map is a graphic that uses symbols to illustrate locational and thematic aspects of spatial distributions. To construct a map the cartographer goes into the real world and collects data which he/she then designs into a map. The map is then read by the map user who sees the real world as perceived by the cartogra-pher. When constructing a map the cartographic communication cycle must be considered because each aspect of the cycle influences the kind of map that needs to be created.

• Proper Symbolization• Appropriate Scales• Enticing Map Design• Long Attention Span• Visualization

Keys to Good Map Communication

THE SIX GRAPHIC VARIABLES

Size

Shape

Orientation

Pattern and Texture

ColorColor is the most power ful graphic variable. It works for points, lines and regions and for both qualitative and quantita-tive data. The three aspects of color are hue, value and chroma.

hue

value

chroma

Size is most effective for point and line symbolization and not effec-tive for area symbolization. Size works best with quantitative data.

Shape works best for point symbolization. It also works for line symbolization, but doesn’t work for area symbolization. Qualitative, not quantitative, data is best represented by shape.

Pattern and texture are effective in representing area symbolization and line symbolization, but not for point symbolization. Qualita-tive data is best represented by pattern and texture.

Jenifer Bode Geography 280 Fall 2005

Orientation can be used with both point and line data. This refers to the direction in which some-thing is pointing in relaiton to a fixed point.

R OLES O F T EX T

size type

24 pt

12 pt

18 pt

48 pt72pt= 1 inch

This is important in the readability of the map. Large font is easier to read, from farther away, thansmallertext.

Type controls how the text looks. This can be used

to add emphasis to certain words.

These are three common

types.

Bold

Italic

Roman

font

Myriad

Arial

Times New Roman

Curlz

Font can greatly affect the readability of a map. Generally the

more simple the font the easier

it is to read.

caseCase is used mainly asa tool to emphasizewords on a map. Important itemslike the titleare oftenuppercase.

UPPER CASE

lower case

Title Case

Text is important on a map and serves to support the map and answer questions for the reader. Things like the title, subtitle and legend are important compenents to any map. There is however a hierarchy of text. More important text should stand out more than niminal text. For example the map title should be the most prominent text on a map.

Jenifer Bode Geog 280 Fall 2005

M A P D E S I G N v s M A P D E S I G N

M e n t a lM a p

( t h i n k i n g )

D r a f t

F i n a l M a p

( r e s u l t s )

• W h a t i s t h e i m p o r t a n t d a t a t h a t n e e d s t o b e m a p p e d ?• H o w c a n t h a t i n f o r m a t i o n b e g r o u p e d ?• W h a t i s t h e b e s t w a y t o v i s u a l i z e t h a t d a t a ?

G r a p h i c P r o b l e m s

I d e a t i o n• I m a g e P o o l i n g• E x p e r i m e n t a t i o n• I n c u b a t i o n• I l l u m i n a t i o nH o w e v e r p e o p l e o f t e n g e t s t u c k i n t r a p s o f c o n v i e n e n c e , o b j e c t i v -i t y a n d b r a i n l a t e r l i z a t i o n .

( p r a c t i c e )

R i g h t B r a i n e d L e f t B r a i n e d

T h r e e F i n a l S t a g e s

• Tr i a l : B e s t D r a f t• E v a l u a t i o n : D o e s t h e m a p d o t h e j o b ?• R e v i s i o n : M a k i n g t h e n e c c e s a r y a d j u s t m e n t s .

• W h a t n e e d s t o b e i l l u s t r a t e d ? a n d f o r w h a t p u r -p o s e ?• W h o i s t h e a u d i e n c e ?

D e s i g n D e c i s i o n s

G o a l s o f M a p D e s i g nI s y o u r m a p p r e t t y a n d p l e a s i n g t o t h e e y e ?

• C l a r i t y a n d l e g i b i l i t y• V i s u a l c o n t r a s t• V i s u a l h i e r a r c h y• V i s u a l B a l a n c e / L a y o u t

C o n t r o l s o n M a p D e s i g n

• T h e m e - O b j e c t i v e• A u d i e n c e• G e o g r a p h i c R e a l i t y• S c a l e• Te c h n i c a l L i m i t a t o i n s

W h y c a r t o g r a p h e r s c a n ’ t g o c r a z y

J e n i f e r B o d eG e o g r a p h y 2 8 0

Fa l l 2 0 0 5

D O T M A P S : M I D T E R M E X A MJ e n i f e r B o d e G e o g r a p h y 2 8 0 F a l l 2 0 0 5

0 140 280 420 56070Miles

¯

1987 Crop Acres by County

1 Dot = 10,000

CROP_ACR87

1 Dot = 10,000

CROP_ACR87

0 130 260 390 52065Miles

¯

1987 Crop Acres by County Dot maps are less common than other mapping tech-niques. They can, however, visually represent certain types of data rather well. Data that works well for dot maps is data that is a count of features for a set area e.g. acres of a certain crop. It is not usually effective to have a dot for every feature. Instead, each dot repre-sents an assigned number of features. Like with any mapping technique many things need to be consid-ered when constructing dot maps. There are three basic variables: dot size, value assigned to a dot, and the location of the dots.Dot size is important because if the dot is too large, they will run into each other an appear as one blob and very dense. Additionally, if the dots get too large they can cover up other data on the map. If the dot size is too small, patterns are often hard to pick out and the data appears sparse. Dot value ties into dot size in that dot value con-trols the number of dots on the map. As previously mentioned it is not effective to have every feature represented by a dot, so each dot is assigned a value. This value controls how many dots will appear in an area. Again this is important because if the value is too large there will be too few dots and the patterns will be hard to identify. If the value is too small, there will be too many dots. Ideally each feature would have a dot represent-ing it. This, however, isn’t usually possible so we assign a multiple features to a single dot. This means that the dots can’t be located where the feature is so location of the dots needs to be considered. In the age of comput-ers, we usually allow the computer to place the dots.

The dot map below shows the number of crop acres by state. Each dot represents 10,000 acres. The map is somewhat ineffective however because of the dot location. The dots are ran-domly places throughout the state make patterns difficult to recognize.

The map above also displays the number of corop acres, but the data is by county. This has a much more effective placement of the dots. Instead of dots being randomly placed throughout the state, the dots are place randomly within the county which is a much smaller area. Patterns can easily be seen in this map.

MW STATES

1,000

10,000

50,000

100,000 ±0 180 360 540 72090

Kilometers

1987 Average Farm Sales: Psychological Classification

MW STATES

1,000

5,000

10,000

50,000

100,000 ±0 180 360 540 72090

Kilometers

1987 Average Farm Sales: Proportional Circles

MW STATES

1 - 30935

30936 - 53379

53380 - 75326

75327 - 100246

100247 - 173001±0 180 360 540 72090

Kilometers

1987 Average Farm Sales: Jenks Classification

The three maps below are all displaying the same data on average farm sales for the year 1987. The difference, however, is how that data is displayed. Using ArcMap quantitative data can be displayed in a variety of ways. ESRI, the creators of ArcMap, define classification as “The process of sorting or arranging entities into groups or categories; on a map, the process of representing members of a group by the same symbol, usually defined in a legend.” Different types of classification are more effective for different types of data.

The first map of average farm sales is a graduated symbol map using Jenks classification. Graduated symbol maps group data together in groups. According to ESRI, "ArcMap identi-fies break points by picking the class breaks that best group similar values and maximize the differences between classes. The features are divided into classes whose boundaries are set where there are relatively big jumps in the data values.” Jenks is a good default classification system.

The second map of average farm sales is a proportional circle map. In a proportional circle map the size of the circle is proportional to the value of the data it is representing. ESRI states that a good example of an effective proportional circle map would be mapping earthquakes where the size of the circle represents the magnitude of the Earthquake. This way to display data can be problematic if you have too many values.

The third map is like a proportional symbol map, except Flannery appearance compensation has been applied. This is called psychological classification because when people view a map, they often underestimate the value of the symbols. Appearance compensation makes everything slightly bigger to make up for human imperfection.

CLASSIFICATION OF DATA: MIDTERM EXAMJenifer Bode Geog 280

CHOROPLETH MAPS: MIDTERM EXAMJ e n i f e r B o d e G e o g r a p h y 2 8 0 F a l l 2 0 0 5

1987 Average Farm Sales: Jenks Classification

¯

0 280,000 560,000140,000

Meters

2500 - 30935

30936 - 53379

53380 - 75326

75327 - 100246

100247 - 173001

1987 Average Crop Acreage: Jenks Classification

¯

0 280,000 560,000140,000

Meters

1 - 106514

106515 - 204114

204115 - 300701

300702 - 474688

474689 - 960806

When mapping data, the method used to display the data needs to be taken into consideration. There are many different ways a cartographer can display different types of data. One the most basic and commonly used mapping technique is choropleth mapping. Choropleth maps use different colors, or values of color, to spatially display regions where the data is the same. Each area represented by a color should be fairly homogenous in the data it is representing. Choropleth maps are often tied to regions, such as counties, or zip codes. An example of this would be a popula-tion density map. Since this information usually comes from the government, the data is tied to counties or zip codes. Data tied to a specific point, such as a city, generally should not be made into a choropleth map. There are three elements of choropleth maps: the size/shape of the area, the number of classes, and class limits. For size and shape, the smaller the unit area, the more variation shows up in the map. Large areas blend data together making the region look homogeneous when there may be variations. This can be controlled by the number of classes. Classifying puts data of similar values into groups. The more classes the map has, the more detailed the map will be. However, too many classes can make the map difficult to read. When a cartographer uses a monochromatic scheme, it is hard for the map reader to distin-guish more than 5-8 classes. More classes can be used when more than one color is used. Class limits are ways that the classes are broken into groups. For example, an equal interval classification does just that. It breaks up classes at equal intervals not taking into consideration the number of areas in each class. In order to make the most effective and easy to read map, all of these aspects need to be taking into consideration.

These are both choropleth maps representing average farm sales and average farm acreage per county. Each map only has five classes so a monochromatic color scheme was used. The natural breaks, or Jenks, classification was used. Natural breaks tries to emphasize big jumps in data to set the classes. These two maps show the same general famring trends.

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6 Bemidji Community Art Center7 Headwaters Science Center16 Paul Bunyan and Babe Statues20 Beltrami County Historical Society

1 Courthouse2 St. Philips School3 Public Library4 Post Office5 City Hall15 Chamber of Commerce

12 Raphaels Bakery Cafe13 Tutto Bene17 The Cabin Coffee House and Cafe18 Uptown Cafe19 Union Station

8 Snow Goose Gifts9 Rainbow Gift & Book Shoppe10 Lady Slipper Designs11 Bemidji Woolen Mills14 Morell's Chippewa Trading Post

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L O C AT I O N A L M A P : O u r t a s k w a s t o u s e a e r i a l p h o t o s a n d p r o d u c e a m a p t h a t a c h a m b e r o f c o m m e r c e m i g h t d i s t r i b u t e . I u s e d a e r i a l p h o t o s t o d r a w i n t h e s t r e e t s a n d t h e n l o c t e d v a r i o u s i m p o r t a n t b u i l d i n g w i t h i n d o w n t o w n B e m i d j i .

Minnesota

J e n ’ s H o m e t o w n M a p Jenifer BodeGeography 280

Fall 2005

4035 Victoria St. NEShoreview, MN 55126

From Eau Claire, Wisconsin take Interstate 94 west. When 94 splits, take 694 until you reach Shoreview and take the Victoria street exit. At the stoplight take a right onto Victoria. Go about 3 blocks until you reach Crystal Ave and take a Left.

Snail L ake Blvd./ Ct y R d F

Cr ystal Ave.V

icto

ria S

t.

My Neighborhood

694

694

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to

ri a

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et

H O M E T O W N M A P : F o r t h i s p r o j e c t w e u s e d a e r i a l p h o t o s t o p r o d u c e a m a p o f o u r h o m e t o w n a r e a s .

F i r s t E x a m : F o r t h e f i r s t e x a m w e h a d t o c r e a t e g r a p h i c e s s a y s o n v a r i o u s a s p e c t s o f c a r t o g r a -p h y . W e h a d t o d i s c u s s t h i n g s t o t h i n k a b o u t b e f o r e m a p p r o -d u c t i o n a n d a l s o t h i n g s t h a t g o i n t o t h e p r o d u c t i o n o f a m a p .

M I D T E R M E X A M : F o r o u r m i d t e r m w e h a d t o c r e a t e g r a p h i c e s s a y s d i s p l a y i n g t h e s a m e d a t a i n t h r e e d i f f e r e n t w a y s a n d d i s -c u s s i n g t h e a d v a n t a g e s a n d d i s a d v a n t a g e s o f e a c h .