What Is Spatial Distribution in Geography?


What’s your current location? You’re somewhere. So is the person next to you. While this might seem like an apparent observation, it’s an important one. Human lives exist within a physical space. This allows us to study the correlation of situations in our lives and the spaces in which they occur. Where do you live? How far can an average person run? Which areas have the most children? Human lives can be studied in terms of geography, and for this, we turn to spatial distribution.

Concept of Spatial Distribution

Spatial distribution refers to the set of geographic observations depicting the importance of the behavior of an extraordinary phenomenon or characteristic across different locations on the earth’s surface. Examples of such analysis include the distribution of the human population across the globe and the investigation of the movements of societies and their influential factors. Such factors include dispersal, migration, dispersion and habitat fragmentation.

A spatial distribution study works by choosing a specific variable and outlining incidents of that variable on a map. For instance, you may want to know which locations in your city have houses that cost more than $200,000. The cost of the house is your variable, so you assign them different colors. For example, locations that have houses costing more than $200,000 are green. Then, fill in the map by giving each house its correct color, depending on what it offers. When it’s complete, look at the relationship between the colors. Are all the green clumped together? Are they dispersed? What does this mean? The following are three basic patterns we expect to find.

Uniform Pattern

A uniform pattern happens when the data points are spaced evenly. An example of such a pattern is a parade marching band where the musicians are evenly spaced out. Humans are known to form uniform patterns through planning. If there is an equal distribution of houses represented by green dots on that map, we’d assume that somebody planned for the entire location to be filled with houses costing more than $200,000. 

Random Distribution

This pattern shows that there’s no direct correlation between any data points. This means that communities or items are scattered randomly. In our example, if the green dots were sporadically dispersed, we’d know the houses weren’t built according to the location. Communities just built houses of different prices wherever they wanted to and didn’t try to form any specific neighborhood. 

Clumped or Clustered Dispersion

This form of dispersion features data points that are related to one another but may not be quite evenly spaced. This illustrates how people can come together based on individual shared experiences. If the green dots are clumped together in one location, we’d know that people who could afford such houses wanted to live close to one another. 

Importance of Studying Spatial Distribution

Tracking populations over time helps predict how they’re likely to change in the future. Monitoring the size and structure also helps manage populations. It’s essential in marketing and planning product lines and end-users. Through spatial distribution, policymakers can estimate resource needs. Spatial distribution variables can also guide the planning of health services.