🌍 Map Visualization Overview¶

What is Map Visualization?¶

Map visualization is a technique to represent spatial (location-based) data through graphical means. It helps with:

  • Analysis
  • Decision-making
  • Transforming location data into visuals

Map visualization incorporates geographic coordinates (e.g., latitude and longitude).

🔍 Why Use Map-Based Visualizations?¶

  • Enhances data understanding
    Example: COVID-19 maps show hotspots more clearly than tables.

  • Reveals patterns
    Urban planners can optimize roads using traffic flow maps.

  • Identifies anomalies
    Maps of crime rates can highlight unexpected spikes.

  • Communicates complex data
    Example: Animated hurricane maps show path and impact.

🗺️ What is Spatial (Geospatial) Data?¶

Spatial data refers to data representing location, shape, and relationships of objects in a geographic space.

Key Components:¶

  • Geometric information: Location & shape (e.g., latitude, longitude)
  • Attribute information: Descriptive info (e.g., city name, category)

🧱 Types of Spatial Data¶

  • Vector data (discrete features):

    • Points: Landmarks, addresses
    • Lines: Roads, rivers
    • Polygons: Cities, forests, parcels

  • Raster data (continuous features):

    • Grids of cells or pixels
    • Examples: Temperature maps, satellite images

🗂️ Common Data Formats for Maps¶

  • .shp — Shapefile (used in GIS software)
  • .geojson — GeoJSON (used in web-based apps)
  • .kml — Keyhole Markup Language (used in Google Earth)
  • .tiff / .png — Raster formats for satellite imagery

💡 What is GeoJSON?¶

GeoJSON is a JSON-based format that stores geodata and associated attributes.

GeoJSON Object Types:¶

  • Point
  • LineString
  • Polygon
  • MultiPoint, MultiLineString, MultiPolygon

Example: A Point¶

{
  "type": "Point",
  "coordinates": [-79.9959, 40.4406]
}

Map Visualization Design Principles – Recap¶

Now that we’ve gone over how map visualizations help us communicate spatial data, here’s a breakdown of key principles to keep in mind when designing maps. These fit into two big buckets: making content readable and clear, and guiding the viewer to spot patterns.

🔍 1. Visual Contrast¶

Good contrast helps features pop. Black and white offer max contrast, but they’re not always ideal for maps. Better combos use color meaningfully — like blue for water, green for land. Poor examples use colors that blend together or aren’t intuitive.

🔤 2. Legibility¶

This is about being easy to read. Use simple, familiar symbols (like an ✈️ for airports). Make sure icons or labels aren’t too small to see. Think clarity and function over style.

🎯 3. Figure-Ground Organization¶

Helps viewers focus on the main data layer (figure) and separate it from background (ground). Techniques like drop shadows, whitewash, and labels help establish what the viewer should pay attention to.

🗂️ 4. Hierarchical Organization¶

Use font sizes, line weights, and label grouping to show levels of importance. This creates visual order — like distinguishing major cities from small towns or national borders from state lines.

⚖️ 5. Balance¶

A well-balanced map feels intuitive. It avoids heavy clusters in one corner or misaligned elements. Balanced layouts improve how a map is perceived and navigated visually.