User:Dlinds1/sandbox

===Summarization of The modifiable areal unit problem (MAUP) in physical geography (Dark, Bram 2007) ===

The journal article The modifiable areal unit problem (MAUP) in physical geography by Shawna J. Dark and Danielle Bram in the Progress in Physical Geography journal identifies examples of how the modifiable areal unit problem (MAUP) arises in physical geography studies. Dark and Bram (2007) maintain that while considerable attention has been given to the importance of scale, little attention has been given to the issue of aggregation among physical geographers. The Modifiable Areal Unit Problem (MAUP) occurs when data captured at one scale is analyzed at a different scale or when the boundary scheme is changed in the analysis. Data loss may occur when attempts are made to aggregate data into larger scales, disaggregate data to smaller scales or redefine analysis boundaries. The data loss may obscure natural processes and patterns and cause errors in the statistical analysis.

Dark and Bram (2007) point out that remotely sensed data may be collected at a scale that is too granular to be useful at a regional or landscape level and that it is collected based on a grid pattern with no concern for the patterns existing within the natural environment. When the data is aggregated to another scale and a more natural boundary pattern, the diversity of the original dataset may be lost and statistical analysis errors might arise. Dark and Bram (2007) discuss how the MAUP affects GIS analysis of remotely sensed data. The DEMs used in the analysis of watershed stream drainage systems and slope analysis, are used as an example. They demonstrate that depending on the scale of the DEM used to produce a stream drainage system, the flow accumulation values can vary, and therefore produce erroneous flow line placements. Slope analysis to identify riparian protection zones are produced using DEM and a buffer. Due to the data already being averaged first with neighboring data points in the DEM raster grid, and then further summarized through the use of the buffer analysis, these two processes combined could result in erroneous results, and missed important data points (Dark and Bram, 2007). Of the possible ways to decrease MAUP, most are based on collecting data on an individual basis based on the variable being analyzed, and are mostly too costly in time and funding (Dark and Bram, 2007).

Dark and Bram (2007) concluded that while the issues associated with the MAUP have been known by social scientists and economic geographers for more than four decades, physical geographers have given it little attention. They have seen some renewed interest in new scaling techniques for dealing with the MAUP but they want to bring attention to the problem to physical geographers since it is still an open problem.