Maps as data sources… …Truth or fiction?. Some ideas about maps Maps = truth Maps are unbiased Maps are objective ICA definition of a map: –“A symbolized.

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Presentation transcript:

Maps as data sources… …Truth or fiction?

Some ideas about maps Maps = truth Maps are unbiased Maps are objective ICA definition of a map: –“A symbolized image of geographic reality, representing selected features or characteristics, resulting from the creative effort of its author’s execution of choices, and is designed for use when spatial relationships are of primary importance.”

Sources of attribute data Remote sensing Ground surveys Count-based surveys Already-published maps Looking with a critical eye at maps as data sources

Gathering data from maps Maps are “authored” Maps are conventional Maps used for various “agendas” Affect on data collection?

Ways maps can be biased Projection: distortion of areas Distortion by symbol choice Generalization: distortion by simplification Avoidable or unavoidable? Intentional or unintentional?

Distortion by Projection choice Mercator projection: Accompanied John Birch Society presentations on communist threat

Distortion by symbol choice “One dot represents 1000 square kilometers”

Distortion by symbol choice In this case, 26 of fifty states used a different product State Governments that use “our product”

Distortion by symbol choice: Color Intuitive colors: Like traffic lights Non-intuitive: Low elevations happen to be arid!

Distortion by symbol choice: Color What is the pattern of high and low birth rates?

Distortion by symbol choice: Categories Different categories can lead to radically different interpretations

Generalization Why do maps simplify?

Generalization: Selection

Generalization: Simplification Locational shift

Generalization: Combination or aggregation..

Generalization Amount and type of generalization depends on scale and purpose Emphasizes connectivity, orientation

What is the purpose of the generalization on the right? “Real World” Generalized

More Generalization

Summary: Why generalize? Legibility Design Persuasion

Data Compilation from Maps: The Rule of Scale Never use a small scale map as a data source for a large-scale map 1:100,000 1:250,000

The Rule of Scale A good map for variation in Phoenix metro area temperature?

Summary: Maps as data sources In looking for data sources … Keep in mind … –Purpose of original data collection –Scale of source data –Age of source data –Utilize multiple sources Affect all data sources, not just maps!