User:Geo arbo/GES 679/FP v1

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The modifiable areal unit problem (MAUP) is a source of statistical bias that can radically affect the results of statistical hypothesis tests. It affects results when point-based measures of spatial phenomena (e.g., population density) are aggregated into districts. The resulting summary values (e.g., totals, rates, proportions) are influenced by the choice of district boundaries. For example, census data may be aggregated into census enumeration districts, or postcode areas, or police precincts, or any other spatial partition (thus, the 'areal units' are 'modifiable'). The issue was discovered in 1934 and described in detail by Openshaw (1984), who lamented that "the areal units (zonal objects) used in many geographical studies are arbitrary, modifiable, and subject to the whims and fancies of whoever is doing, or did, the aggregating.".

Overview

(Overview words were based on Jason's assignment 1 submission)
Increased computing capabilities have improved the way the world can be visualized, analyzed and understood. Of these capabilities, Geographic Information Systems (GIS) have emerged as powerful tools for researching and analyzing data geographically. Relationships between previously incomparable or incompatible data can now easily be analyzed by associating them using a common platform (e.g., coordinate systems in the case with GIS).

The increased ability to analyze data using GIS is sometimes associated with a problem. The problem is how to delimit or draw the boundaries of data to represent the data’s geographic distribution accurately. This is the Modifiable Areal Unit Problem (MAUP) and it persists as a potentially unsolvable problem in geographic research.

GIS uses computer systems to visualize the world. It is a means of representing objects at point locations. Each person, fire hydrant, or house has a precise position on the earth that can be described as a specific latitude and longitude. However, in some cases, point data are neither required nor preferred. Point data are regularly aggregated to some larger area (areal unit), whether it be the sum of houses in a neighborhood, people in a county, or fire hydrants in a city. Sometimes there are simply too many data points for time sensitive calculations. Whatever the reason for aggregation may be, point data are frequently grouped into polygonal areal units in order to explore relationships.

Areal units are simply polygons that delimit areas. Examples of areal units are census tracts, police districts, zip codes, counties, and states. There is no prescribed base ‘areal unit because there is no set of standards by which areal units are defined. Areal units used in geographic analyses are chosen by researchers. There is great variation in the shapes and sizes of areal units. These two items – shape and size – are a double-edged sword. They are what give GIS its unprecedented ability to derive spatial information and insights, and conversely form the fundamental basis of the Modifiable Areal Unit Problem.

The MAUP is split into two main sub-problems: scale problems and zonal problems. These problems were identified by Openshaw as early as 1977, before the application of GIS in research. The scale problem is seen when census block information is aggregated to the tract level, and then to the county level. Zonal problems occur when the number of units remains the same, but the shapes of the units change (Wilson, 2011). In some cases, the zonal problem is referred to as an aggregation problem (Openshaw, 1985).

Use of Census blocks and tracts in analysis provides an example of both the scale and zonal problems. Census blocks are smaller units than the tracts. More detailed information is known about the people that reside within the block boundaries. Differences that distinguish nearby blocks are eliminated when information is aggregated to the tract level. The information that was defined to a smaller geographic region has been normalized to a larger area.

Since these areal units (blocks and tracts) generally contain an equal number of people between like units, the shape and size of the unit may vary. For example, densely populated urban areas will have smaller areal units compared to rural areas, where the population is distributed over larger areas. A block for an urban area may delimit a few square miles whereas areas of rural blocks may range into the 10s and 100s of square miles and still contain the same number of residents as the urban block.

The ecological fallacy problem may be associated with the shape and size sub-problems. The ecological fallacy may occur when observations about aggregated attributes, resulting from analyses based on areal units, are assumed to be attributes of each of the individuals whose data were aggregated (Openshaw, 1984).
(link to ecological fallacy could be included above).

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Examples

Examples introductory paragraph....

Crime

The MAUP in Crime analyses...

Economics

The MAUP in Economic analyses...

Traffic

The Political Science in Traffic analyses...

Economics

The MAUP in Political Science analyses...

GIS data processing

MAUP in the Processing of GIS Data (from the theories of GIS papers)

Mitigating MAUP

There are ways to mitigate MAUP...

Optimizing Units with Algorithms

Algorithms can be used to optimize areal units....

Bibliography

Ron will provide citations here...

See also

General topics

• Representation theory
• Spatial analysis

Specific applications

• Spatial epidemiology
• Spatial econometrics
• Gerrymandering
• Boundary problem (in spatial analysis)

References

• Cressie, N. (1996). "Change of Support and the Modifiable Areal Unit Problem." Geographical Systems, 3:159-180.
• Gehlke, C. and Biehl, H. (1934). Certain effects of grouping upon the size of the correlation coefficient in census tract material. Journal of the American Statistical Association Supplement, 29, 169–170. doi:10.2307/2277827
• Holt D, Steel D, Tranmer M, Wrigley N. (1996). "Aggregation and ecological effects in geographically based data." Geographical Analysis 28:244–261.
• Openshaw, S. (1984). The Modifiable Areal Unit Problem. Norwich: Geo Books. ISBN 0-86094-134-5.
• Unwin, D. J. (1996). "GIS, spatial analysis and spatial statistics." Progress in Human Geography. 20: 540-551.

Category:Bias Category:Geographic information systems Category:Spatial analysis