Chapter 2 Mapping GIS Data

Outline GIS Concepts Mapping GIS data Displaying rasters Classifying numeric data

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

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

Single symbol maps Display all features with the same symbol Combine with labels to portray nominal data

Categorical data Places features into defined number of distinct categories Category names may be text or numeric Portrayed by different symbol for each category

Unique values maps Different symbol for each category or value

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…

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

Mapping numeric data Interval and ratio data must be divided into classes before mapping Mapped using variations in symbol size, thickness, or hue

Classed maps Graduated color map (choropleth map) Simply color variation Graduated symbol map Symbol size variation Normalized map

Unclassed maps Proportional symbol map Dot density map

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

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

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

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

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

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