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MAUP – Modifiable Areal Unit Problem

MAUP Scale Effect

What Is the Modifiable Areal Unit Problem (MAUP)?

The modifiable areal unit problem (MAUP) is a statistical bias that occurs when you aggregate point data. There are two types of biases for the MAUP:

  • Scale effect
  • Zonal effect

The Modifiable Areal Unit Problem (MAUP) is an issue in GIS where the results of spatial analysis can vary based on the arbitrary delineation of geographic units, highlighting the sensitivity of analysis to the choice of spatial boundaries.

Scale Effect

The scale effect occurs when maps show different analytical results at different levels of aggregation. Despite using the same points, each successive smaller unit consequently changes the pattern.

MAUP Scale Effect

The scale effect can yield different results based on the size of the boundary. As you move from higher to lower aggregation levels yields different results, each level of aggregation paints a different picture.

Zonal Effect

The zonal effect occurs when you group data by various artificial boundaries. In this type of MAUP error, each subsequent boundary yields major analytical differences.

MAUP Zone Effect

For example, here are points aggregated at a county level. But when you aggregate at a state level, it produces different visible results.

Gerrymandering and Redistricting

The zonal effect can occur by accident or on purpose. For example, this can occur when a political party wants to favor an election by

MAUP Gerrymeandering

As an example in the diagram above, you can manipulate any of the political boundaries below to favor either blue or red. This is how to rig an election so it’s in favor of one political party.

Gerrymandering – Manipulation of electoral districts for political gain.
Redistricting – Changing the boundary lines for electoral districts such as with the Esri Redistricting extension.


The Modifiable Areal Unit Problem (MAUP) occurs by aggregating data and representing it with bias at different scales or boundary extents.

Despite being essentially an unsolvable issue, you can help map readers by:

  • Stating the scale of aggregation.
  • Representing it at multiple scales simultaneously.

As described in the book “How To Lie With Maps”, mapmakers – consciously or unconsciously – can present only one of many possible stories about the places it depicts.