In-Depth Notes on Geographic Information Systems and Thematic Mapping

Overview

  • Geographic Information Systems: Key topics in GENS 2441 include data display and cartography, thematic mapping, spatial interpolation, and more.

Thematic Mapping

  • Definition: A thematic map displays spatial attributes of a single theme (e.g., temperature maps).

  • Main Uses:

    • Provide specific information about locations.
    • Visualize spatial patterns (e.g., clusters, gradients).
    • Compare attributes across different maps.

  • When to Create: Use thematic maps for visualizing or communicating spatial patterns, such as changes in forest cover to agriculture.

    1. Research statistical summaries of relevant countries.
    2. Link summary information to GIS maps.
    3. Decide on an appropriate mapping method.

Map Making Process

  1. Consider the real-world distribution of the phenomenon.
  2. Determine the purpose of the map.
  3. Collect appropriate data.
  4. Design and construct the map.
  5. Identify potential audience interpretation barriers.

Types of Thematic Maps

  1. Choropleth Maps: Use color-shaded symbols to represent numeric data classes for polygons. Ideal for representing data collected at enumeration units (e.g., counties).
  2. Isopleth Maps: Depict smooth continuous phenomena (e.g., elevation) using isolines.
  3. Proportional Symbol Maps: Use symbols varied by size to indicate quantitative variable strength (e.g., population density).
  4. Dot Maps: Use dots to indicate the intensity of a variable over a specific area.

Choosing Mapping Methods

  • Consider:
    1. Spatial dimension of the variable (point, line, polygon).
    2. Data type/level of measurement.
    3. The effectiveness of visual elements.
    4. Normalization of mapped attribute values for comparison.

Data Types and Levels of Measurement

  1. Nominal Data: Named categories (e.g., land types).
  2. Ordinal Data: Ranked data (e.g., habitat suitability).
  3. Interval Data: Numerical data with regular intervals, no absolute zero (e.g., temperature).
  4. Ratio Data: Numerical data with absolute zero (e.g., population).

Data Classification Methods

  • Equal Intervals: Divide range of data into equal size intervals. Good for familiar data ranges.
  • Quantiles: Classify data ensuring the same number of observations in each class.
  • Mean-Standard Deviation: Classes based on standard deviations from mean values.
  • Natural Breaks: Classes based on inherent data groupings.

Interpolation Techniques

  1. Thiessen Polygons: Create boundaries so all points within a polygon are closer to that polygon’s control point.
  2. Inverse-Distance Weighting (IDW): Predicts values based on the average of neighboring control points, weighted by distance.
  3. Kriging: A geostatistical method accounting for spatial correlation between points, producing raster surfaces.
  4. TIN (Triangulated Irregular Network): Vector-based and maintains the value of control points while interpolating values between them.
  5. Trend Surfaces: Use regression models to relate values to XY coordinates, useful for smoothing data trends but may miss sudden changes.

Summary

  • Thematic mapping is crucial for visualizing geographic data effectively. Understanding various mapping methods and when to apply them is essential for effective geographic analysis. Various interpolation methods enhance our ability to predict and understand spatial phenomena, supporting numerous applications from environmental studies to urban planning.