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Chapter 2 Mapping GIS Data
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Outline GIS Concepts Mapping GIS data Displaying rasters
Classifying numeric data
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Mapping GIS data Map type Data type Nominal data Categorical data
Ordinal data Interval and Ratio data Single symbol map Unique values maps Quantities maps Graduated color Graduated symbol Dot density
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Nominal Data Names or uniquely identifies objects
State names Owner of parcel Tax ID number Parcel ID Number Each feature likely to have its own value Usually portrayed on a map as labels
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Single symbol maps Display all features with the same symbol
Combine with labels to portray nominal data
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Categorical data Places features into defined number of distinct categories Category names may be text or numeric Portrayed by different symbol for each category
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Unique values maps Different symbol for each category or value
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Ordinal data Type of categorical data
Ranks categories along an arbitrary scale Low, Medium, High slope Village, Town, City Grades: A, B, C, D, F Rank of Best City to Live In: 1, 2, 3…
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Interval and Ratio data
Interval data places values along a regular numeric scale Supports addition and subtraction Temperature, pH, and elevation Ratio data places values along a regular scale with a meaningful zero point Supports addition, subtraction, multiplication, and division Population, rainfall, and median rent
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Mapping numeric data Interval and ratio data must be divided into classes before mapping Mapped using variations in symbol size, thickness, or hue
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Classed maps Graduated color map (choropleth map)
Simply color variation Graduated symbol map Symbol size variation Normalized map
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Unclassed maps Proportional symbol map Dot density map
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Displaying rasters Discrete data Continuous data
Represents discrete objects such as lines or polygons Takes on relatively few values Adjacent cells often have same values Values may change abruptly at boundaries Continuous data Thousands or millions of potential values Few adjacent cells have same values Values may change rapidly from cell to cell
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Raster types Thematic rasters Image rasters
Contain quantities that represent map data such as land use or rainfall May be continuous or discrete Image rasters Contain satellite or air photo data Generally represent brightness Usually continous
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Classifying numeric data
Applies to both vector and raster maps Different classification methods available Choice impacts map appearance and validity Best method depends on data distribution and objective of map Same data, different classifications
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Classifying types 1. Jenks Natural Breaks 2. Equal Interval
Exploits natural gaps in the data Good for unevenly distributed or skewed data Default method, works well for most data sets 2. Equal Interval Specify number of classes Divides into equally spaced classes Works best for uniformly distributed data 3. Defined interval User chooses the class size Data determines number of classes
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Classifying types cont..
4. Quantile Same number of features in each class May get very unevenly spaced class ranges Results depend on data distribution 5. Geometrical Interval Multiplies each succeeding class boundary by a constant Works well for normal and skewed distributions 6. Standard Deviation Shows deviation from mean User chooses units e.g. 0.5 standard deviations Assumes data are normally distributed
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References Price, M. (2013). Mastering ArcGIS (6th ed.). McGraw-Hill
Price, M. (2013). Mastering ArcGIS (6th ed.). McGraw-Hill. Mastering ArcGIS, 6/e Instructor Edition Chapter 2: PowerPoint Notes and Figures
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