PHC6194 SPATIAL EPIDEMIOLOGY

Spatial Data Visulization

Hui Hu Ph.D.

Department of Epidemiology

College of Public Health and Health Professions & College of Medicine

February 12, 2020

Spatial Data Visualization

 

Lab 1: Visualization Using QGIS


Lab 2: Visualization Using Carto

 

Lab 3: Visualization Using R

Spatial Data Visualization

Map

  • Map provides a powerful way to visualize spatial data
     
  • However, sometimes it can be misleading, like many other visualization tools

Cartography

  • The art and science of mapmaking
     
  • Make decisions on:
    -  what data to display
    -  how to display them

Types of Maps in Spatial Epidemiology

  • Methods of display:
    -  static map: to show static spatial pattern
    -  animated map: to present spatial pattern over time
     
  • Features to display:
    -  maps for points
    -  maps for polygons

Maps for Points

  • Point map
    -  delineate the locations of point features
    -  visualization of the spatial pattern of point features
     
  • Contour map
    -  made from point features with some attribute values
    -  e.g. air pollution level from stationary monitors

Spatial distribution of sulfate concentrations based on 1980-1981 average values in 144 metropolitan statistical areas

Source: Environmental Health Perspectives Supplements Volume 109, Number S3, June 2001

Maps for Polygons

  • Graduated color map (choropleth map)
    -  the most common maps to display polygons
     
  • Symbol map
    -  a symbol is located in the centroid of each polygon and attribute values are indicated by the choice of symbol

Maps for Polygons (cont'd)

  • Dot densities map
    -  show the amount of an attribute within an area
    -  each dot represents a specified number of features (e.g. each dot represents 1,000 people within an area)
    -  the dots are distributed randomly within each area
    -  the closer together the dots are, the higher the density of features in that area

Maps for Polygons (cont'd)

  • Chart map
    -  bar/column charts, stacked bar charts, and pie charts can present large amounts of categorical data in an eye catching fashion

Source: https://www.e-education.psu.edu/natureofgeoinfo/sites/www.e-education.psu.edu.natureofgeoinfo/files/image/hisp_pies.gif

Symbolization

  • Location
    -  provide the spatial structure and support of the geographic data
     
  • Size
    -  size of points can indicate some attribute values
     
  • Shape
    -  different shapes can be used to indicate different types of features
     
  • Orientation
     
  • Texture and color

Color

Color

Lab 1: Visualization Using QGIS

git pull

Lab 2: Visualization Using Carto

Lab 3: Visualization Using R

PHC6194-Spring2020-Lecture6

By Hui Hu

PHC6194-Spring2020-Lecture6

Slides for Lecture 6, Spring 2020, PHC6194 Spatial Epidemiology

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