Spatial Scale Problems (Atkinson and Tate 2000)

Scale is a complex topic with numerous definitions encompassed within diverse conceptual frameworks. For example, in human geography, scale may be perceived as a consequence of social behavior at different levels such as household, neighborhood, state, and nation. In this article, the spatial data analysis perspective is at the forefront, and a definition of scale which relates to spatial extent is used through this article. Atkinson and Tate (2000) divide spacial scale into two elements: 1. scale of spatial measurement, and 2. scale of spatial variation. Any analysis of spatial data is dependent on the support (e.g., geometrical size, shape, and orientation of the measurement units) and coverage of the data. Thus, characterizing the spatial scale of variation and how this relates to the measurement scale should be a fundamental part of any application of such data. Overall, this article provides a comprehensive account of spatial scale problems in geographical information science contexts and presents a variety of geostatistical approaches useful for characterizing scales of spatial variation and re-scaling data.

As a transportation geographer, I am particularly interested in the modifiable areal unit problem (MAUP), which lies at the heart of any analysis of spatial aggregation. Although spatial data are increasingly disaggregated, many studies on transportation geography require some level of aggregation (e.g., traffic analysis zones, census tracts, dissemination areas). Atkinson and Tate (2000) argue that MAUP can contribute to a significant loss of information in the aggregation of data in large units of geography. Indeed, the aggregation of the same data in different configurations of spatial units can lead to dramatically different results. Besides of the MAUP, we must also be cautious when we transfer relationship at the individual level to aggregates of individuals. For example, a survey can reveal that men ride bikes more frequently than women. However, one can measure lower cycling rate at census tracts with a higher share of male since these census tracts lack access to cycling facilities.

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