# What is (if there's any) difference between MAUP and Edge Effect

I heard both the term MAUP and Edge Correction in association with Spatial Statistics, zoning/quadrats, demographics etc.

Is there a difference between the two? What is the difference then?

• did you try googling the terms? in both cases the first hit is a good definition, that should get you started on what sounds like a homework question. – Ian Turton Apr 14 '16 at 16:50
• I looked at the wikipedia article but it is not clear what is the difference between the two. How do you understand the difference? – Rudolf O Apr 14 '16 at 16:53

The Modifiable Aerial Unit Problem (MAUP) is a change of support issue associated with arbitrary aggregate units. Two classic examples are census tracks and wildlife game units. These have been found to be arbitrary political units and the underlying statistical response in demography acts independent of the unit. Because of this, the unit is not an accurate representation of the process and statistics are unstable through time. Aggregation bias associated with MAUP can be in zonal units (polygons) or in scale (raster cell resolution).

Edge effect, on the other hand can mean a few things but is always directly related to a boundary problem and represents a loss of neighbors. In raster analysis it is where the edge of the raster truncates the number of cells being evaluated in focal functions. This provides a bias in the resulting cells along the edge. Whereas, in spatial statistics or, more specifically, point pattern analysis edge effect has a direct effect on the expected null of complete spatial randomness (CSR) that the observed point pattern is tested against. Additionally, the loss of neighbors in the observed point process can effect the resulting statistic. Edge correction accounts for this bias.

This is, of course, an very over simplified description and I encourage you to dig into the primary literature to better understand how these issues effect spatial analysis. Here are a few references to get you started.

Barber, G. M. (1988) Elementary Statistics for Geographers. Guilford Press: New York, NY.

Diggle, P.J. (1985) A kernel method for smoothing point process data. Applied Statistics, Journal of the Royal Statistical Society, Series C 34:138–147.

Diggle, P.J. (2003) Statistical analysis of spatial point patterns, Second edition. Arnold.

Fotheringham, A. S., and D.W.S. Wong. (1991). The modifiable areal unit problem in multivariate statistical analysis. Environment and Planning 23:1025-1044

Gatrell, A.C., T.C. Bailey, P.J. Diggle, and B.S. Rowlingson. (1996) Spatial point pattern analysis and its application in geographical epidemiology. Transactions of the Institute of British Geographers 21:256-274.

Openshaw S. (1984). The Modifiable Areal Unit Problem. Geobooks, Norwich, England.