Open map List

Quantitative Data

In cartography, quantitative data refers to numerical information that represents measurable values or magnitudes of geographic features. It is used to analyze and visualize spatial variations, distributions, and intensities on maps, making it essential for data-driven geographic analysis.

Basic

Introduction

Key Characteristics of Quantitative Data in Cartography:

  1. Numerical and Measurable – Represents values such as elevation, temperature, population density, or rainfall.
  2. Can Be Ordered and Compared – Allows for statistical analysis and ranking of geographic phenomena.
  3. Uses Visual Scaling Techniques – Represented through graduated symbols, proportional symbols, color gradients, and contours.
  4. Supports Thematic Mapping – Common in choropleth maps, isopleth maps, and proportional symbol maps.

Explanation

Types of Quantitative Data in Cartography:

  1. Interval Data – Measured on a scale with equal intervals but no true zero (e.g., temperature in °C or °F).
  2. Ratio Data – Has equal intervals and a true zero (e.g., population, distance, income levels).

Comparison of Quantitative vs. Qualitative Data in Cartography:

Feature Quantitative Data Qualitative Data
Definition Numerical, measurable data Descriptive, categorical data
Examples Population density, elevation, temperature Land use, road types, vegetation types
Measurement Uses numbers to represent magnitude No numerical value, only classification
Mapping Techniques Choropleth maps, heat maps, proportional symbol maps Categorical maps, symbol maps

Examples

Examples of Quantitative Data in Cartography:

  • Elevation Data – Measured in meters or feet above sea level.
  • Population Density – Expressed as people per square kilometer.
  • Temperature Variations – Recorded in degrees Celsius or Fahrenheit.
  • Rainfall Levels – Measured in millimeters or inches.
  • Traffic Volume – Number of vehicles per hour on a road.

Outgoing relations