Making Effective MapsEfficiently

AIM: make the appropriate number of maps swiftly, without multiple

revisions, that communicates to the intended audiences so as to

accomplish our goals

ArcView’s power paradoxically can limit efficient map production:

offers many options doesn’t help people make design choices as computer-based tool, encourages

managers to expect easy, multiple revisions thus mapmakers rarely take time to

consider communication effectiveness of their maps, reducing chances of success

. what data to map

. how many maps are needed to present the message(s) to audience(s) in what locations

. who your audience(s) is (are)

. what your message(s) will be

. where the map will be used(oral presentation; report; newspaper/TV)

Decisions to Get Started

Who Your Audience is

your immediate superior fellow program staff other programs’ staff senior managers (Management Team, etc.) legislature/Governor stakeholders (industry, environmentalists…) general public (attentive; non-attentive)

Why Considering Audiences is Important

Effective communication depends upon:

(1) understanding what information your audience wants about the topic

(2) understanding how your audience might interpret the information you want to give them

(3) incorporating (1) and (2) into map design

What the agency knows What the agency does/will do What reactions the audience might take Reasons for agency/audience reaction

What the Message Will Be

Where the Map Will Be Used

Affects the complexity of the message that can be conveyed.

Affects the ability to offer supplementary information. (e.g. text, graphics)

Affects text and symbol choices. Affects color choices (beware of designing

in color but printing in black & white)

What Data to Map

The most current data The most accurate data Data that pertains to area of interest Data that is readily understood by

intended audience.

How Many Maps are Needed

Complex maps, especially those with more than one message, are not easily understood.

If you make your audiences work too hard to interpret your map, they may be distracted from your message

Map Type, Display Type Data Type Symbolization Graphic Hierarchy Geographic Frame of Reference Color

Audience-Message-Venue-Data

Affects:

Choose the most appropriate one based on your message, data, audience and venue

Map Types

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Standard

Images

Choropleth Unique Value

Choropleth Graduated Color

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Del

awar

e R

iver

Camden

Gloucester City

Collingswood

1989 TRI facilitiessmall, medium, & large

emissions

Graduated Symbol

#S#S#S#S#S#S#S#S#S#S#S#S#S#S#S#S#S

#S#S#S#S

#S#S#S#S#S#S

#S#S#S

BURLINGTON CITY

BURLINGTON TWP

Delaware River

1989 TRI SitesReleases to

Air, Water, & Land

Chart

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HUNTERDON

MIDDLESEX

UNION

MORRIS

MERCER

ESSEX

Somerset CountyPopulation Density

1 dot = 200 people sq/mi

Dot Density

3-D

Result of a T-test performed to identify areas of significant change in deer harvest.

Statistical Analysis

DATA TYPES

The most important factor in determining map type and symbols

Point

Differences in Kind

Qualitative Data

LOWER TWP

CAPE MAY POINT

WEST CAPE MAY

AtlanticOcean

Polygon

EwingTwp

Trenton

Line

. Polygon Data - Absolute vs. Ratio

. Point Data - Discrete vs. Continuous

Differences in amounts and measures

e.g. number of persons (absolute)e.g. population density (ratio)

e.g. chemical releases at a site (discrete)e.g. rainfall (continuous)

. Line Data e.g. flow lines, thickness of line

Quantitative Data

Discrete vs. Continuous

Discrete Continuous

#S#S#S#S#S#S#S#S#S

#S#S#S#S#S#S#S#S

#S#S#S#S#S#S

BURLINGTON CITY

Releases toAir, Water, & Land

1989 TRI Sites

DelawareWaterGap

WALPACKTWP

Point Data

Population Pop Den

CorrectIncorrect

New York

Bay

UNION

ESSEX

BERGENBERGEN

ESSEX

UNION

New YorkBay

Polygon Data – absolute & ratio

Incorrect

Population - 1990

Correct

Population Density

Correct

BERGEN

ESSEX

UNION

HUDSON

Population

Maple Grange

State Hwy 94

Road

Trail

Appalachian

VERNON TWP

Line Data

SYMBOLIZATION

The key to communicating to your audience

Qualitative Data

Make symbols as intuitive as possible

Use professional standards whenever possible

Legends

•Natural Breaks (default)

•Quantile

•Equal Area

•Equal Interval

•Standard Deviation

Quantitative Data

. ArcView’s default classification method.

. Identifies break points by looking for groupings and patterns inherent in the data. Extreme values are obvious.

Natural Breaks

BERGEN

ESSEX

UNION

New YorkBay

Natural Breaks - example

. Each class is assigned the same number of features.

. It doesn’t matter if features on either side of a class boundary have almost the same values.

. Best suited for a data set that does not have a large number of features with similar values.

Quantile

BERGEN

ESSEX

UNION

New YorkBay

Quantile - example

. Classifies polygon features by finding breakpoints in the attribute values so that the total area of the polygons in each class is approximately the same.

. Polygons with the largest values tend to hide variation in population between geographically smaller areas.

Equal Area

BERGEN

ESSEX

UNION

New YorkBay

Equal Area - example

. The range of attribute values is divided into equal sized sub-ranges.

. Useful when you want to emphasize the amount of an attribute value relative to another value. (e.g. If you want to show that a municipality is part of a group of municipalities that make up the bottom 20% for population density).

. Not good if you want to reveal subtle differences between features with similar values.

Equal Interval

BERGEN

ESSEX

UNION

New YorkBay

Equal Interval - example

. Shows you the extent to which an attribute’s values differ from the mean of all the values.

. ArcView first finds the mean value and then places the class breaks above and below the mean at 1, .5, or .25 standard deviations.

. ArcView will aggregate any values beyond three standard deviations from the mean into two classes: ‘>3 Std Dev’ and ‘<3 Std Dev’.

Standard Deviation

BERGEN

ESSEX

UNION

New YorkBay

Standard Deviation - example

Loading Legend Symbols

Loading legend symbols continued

Loading and Saving a Legend

Loading and Saving a Legend continued

Loading and Saving a Legend continued

Point symbols can be rotated to symbolize additional information about features. e.g. wind direction

d

d

d

d d

Rotating

Used when you have two features represented by one line.e.g. pipelines and roads are sometimes represented by the same line.

Line offset will allow you to display both as two separate features.

Line Offset

GRAPHIC HIERARCHY

Message should be “high” in the hierarchy, supporting information

should be “low”.

ForegroundObjects that stand out from the background.

BackgroundNot immediately noticeable, but enhances map design and understanding.

- Contrast- Geographic Frame of Reference- Color

Foreground/Background

Aids the eye in discerning differences on a map.

Lack of visual contrast makes it difficult to distinguish important from unimportant parts.

Contrast

e

e

e

e

Contrast – bad example

e

e

e

e

Contrast – good example

GEOGRAPHIC FRAME OF REFERENCE

Aids orientation, thus enhances understanding for the map reader

Geographic Frame of Reference

Aids orientation, thus enhances understanding for the map reader

OCEAN COUNTY

Without a frame of reference

Atlantic Ocean

MONMOUTH

OCEAN

BURLINGTON

ATLANTIC

With a frame of reference

COLOR

The distinction between foreground and background can be enhanced by choosing colors with their advancing and retreating characteristics in mind

Advancing/Receding

Advance Warm hues High values Bright Colors

Recede Cool hues Low values Dull colors

Yellow BEST Black

White Blue

Black Orange

Black Yellow

Orange Black

Black White

White Red

Red Yellow

Green White

Orange White

Red WORST Green

Foreground & BackgroundColor Combinations

More COLOR Issues

. Affects clarity and legibility

.Generates different visual hierarchical levels in the map.

Hue

Physiographic Provinces

The name given to the colors we perceive

Color Dimensions

. The most pleasant combinations result from significant differences in lightness (value).

. A foreground color must stand out from the background by being definitely lighter or darker.

The quality of lightness or darkness of a color.

Value

LOWER TWP

CAPE MAY POINT

WEST CAPE MAY

OceanAtlantic

LOWER TWP

CAPE MAY POINT

WEST CAPE MAY

AtlanticOcean

Value - example

. Popular foreground colors are those containing little gray.

. But vivid colors combined with a grayish background can be very effective.

Amount or saturation of pigment. 0 % gray - 100% maximum color.

Saturation

Blue - Water, Cool temperature

Red - Warm temperature, warning, danger

Green - Lush, thick vegetation, safety

Yellow/Tan - Dry, little vegetation, caution

Brown - Land surfaces (e.g. uplands, contours)

Red/Yellow/Green - danger/caution/safety

Qualitative Conventions

Color Plan - The way a designer chooses to use the color dimensions of hue, value, and brightness to symbolize different amounts of data on a map.

Three commonly used color plans are...

Quantitative Conventions

BERGEN

ESSEX

UNION

New YorkBay

Single Hue Plan

BERGEN

ESSEX

UNION

New YorkBay

Double-ended plan

DelawareWaterGap

WALPACKTWP

Full-spectral plan

. Effectiveness of the use of color on the map.

. Appropriateness of the conventional uses of color on the map.

. Overall appropriateness of color selection relative to map content.

. Easily recognized link between legend and map.

Color Harmony

Some colors will be different on a computer screen than in the final product. (HP Printer, TV, Slides etc.)

Maps designed in color but printed in black and white may produce shades of gray that are hard to interpret. Design with blacks, whites, and grays and vary the texture or pattern.

Design for Final Product

CHARTS

. Presents complex tabular information effectively. Provides an immediate impact and takes less effort to understand.

. Complements map information. Shows the same information in a different way, or provides additional information about map features.

Charts

Good for comparing values and showing trends

Bar Chart

Good for comparing values and showing trends

Column Chart

Good for showing the relative value for each category as well as the total.

Area Chart

Combines features of both the bar and area charts

Cumulative Bar Chart

Shows relationships between the parts and the whole, particularly useful for showing proportions and ratios.

Pie Charts

Emphasizes rate of change. Particularly good for representing trends over a period of time.

Line Charts

Reveals trends or patterns in the data. Can help reveal associations, sometimes cause-and-effect relationships.

Scatter Charts

Map, Data, and Symbolization- affect the message of your map

Message- affects your choice of map, data and symbols.

Summary