Open map List

Qualitative Data

In cartography, qualitative data refers to non-numerical, categorical information that describes the characteristics, types, or classifications of spatial features without conveying numerical values or magnitudes. It is used to distinguish different features on a map based on their type, name, or category rather than their quantity or intensity.

Basic

Introduction

Key Characteristics of Qualitative Data in Cartography:

  1. Categorical and Descriptive – Represents types, labels, or classifications of geographic features (e.g., land use, soil type, road classifications).
  2. Symbol-Based Representation – Uses colors, patterns, and symbols rather than numerical scales.
  3. Non-Ordered – Data may be nominal (unordered categories) or ordinal (ordered categories) but does not involve measurable values.
  4. Supports Thematic Mapping – Often used in choropleth, dot density, or categorical maps.

Explanation

Comparison of Qualitative vs. Quantitative Data in Cartography:

Feature Qualitative Data Quantitative Data
Definition Descriptive, categorical data Numerical, measurable data
Examples Land use, road types, soil classification Elevation, temperature, population density
Measurement No numerical value, only classification Uses numbers to represent magnitudes
Mapping Techniques Symbol maps, choropleth maps, categorical maps Proportional symbol maps, heat maps

Examples

Examples of Qualitative Data in Cartography:

  • Land Use Types: Residential, Commercial, Industrial, Agricultural.
  • Vegetation Types: Deciduous Forest, Evergreen Forest, Grassland.
  • Political Boundaries: Countries, States, Provinces.
  • Road Classifications: Highways, Local Roads, Unpaved Roads.
  • Soil Types: Sandy, Clay, Loam.

Outgoing relations