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Uncertain geographic context problem

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The uncertain geographic context problem (UGCoP) is a source of statistical bias that can significantly impact the results of spatial analysis when dealing with aggregate data.[1][2][3][4][5] The UGCoP is very closely related to the Modifiable areal unit problem (MAUP), and like the MAUP, arrises from how we divide the land into aerial units.[1][2][6][7][8] It is caused by the difficulty, or impossibility, of understanding how phenomena under investigation (such as people within a census tract) in different enumeration units interact between enumeration units, and outside of a study area over time.[1][2][9] It is particularly important to consider the UGCoP within the discipline of time geography, where phenomena under investigation can move between spatial enumeration units during the study period.

Introduction

Schematic and example of a space-time prism using transit network data: On the right is a schematic diagram of a space-time prism, and on the left is a map of the potential path area for two different time budgets.[10]

The uncertain geographic context problem, or UGCoP, was first coined by Dr. Mei-Po Kwan in 2012.[1][2] The problem is highly related to the ecological fallacy, edge effect, and Modifiable areal unit problem (MAUP) in that it relates to aggregate units as they apply to individuals. The crux of the problem is that the boundaries we use for aggregation are arbitrary, and may not represent the actual neighborhood of the individuals within them.[6][3][7][8] While a particular enumeration unit, such as a census tract, contains a person's location, they may work, go to school, and shop in completely different areas. If a boundary is able to be crossed, the geographic phenomena under investigation may extend beyond the delineated boundary. Different individuals, or groups of individuals, may have completely different activity spaces, making an enumeration unit that works for one person meaningless to another.[1][2][3][11] For example, a map using school districts as a means of aggregation will be more meaningful when studying a population of students than the general population. Traditional spatial analysis, by necessity, treats each discreet aerial unit as a self-contained neighborhood and does not consider the daily activity of crossing the boundaries.

The UGCoP has further implications when considering the area outside of a study area. Tobler's second law of geography states, "the phenomenon external to a geographic area of interest affects what goes on inside."[12] As a study area is often a subset of the planet, data on the edges of the study area will be excluded. If the boundary demarcating the study area is permeable to travel, then the phenomena under investigation within it may extend beyond, and be impacted by, forces excluded from the analysis. This uncertainty contributes to the UGCoP.

Implications

Suggested solutions

See also

References

  1. ^ a b c d e Kwan, Mei-Po (2012). "The Uncertain Geographic Context Problem". Annals of the Association of American Geographers. 102 (5): 958–968. doi:10.1080/00045608.2012.687349.
  2. ^ a b c d e Kwan, Mei-Po (2012). "How GIS can help address the uncertain geographic context problem in social science research". Annals of GIS. 18: 245–255. doi:10.1080/19475683.2012.727867. Retrieved 4 January 2023.
  3. ^ a b c Chen, Xiang; Kwan, Mei-Po (2015). "Contextual Uncertainties, Human Mobility, and Perceived Food Environment: The Uncertain Geographic Context Problem in Food Access Research". American Journal of Public Health. 105 (9). doi:10.2105/AJPH.2015.302792.
  4. ^ Zhou, Xingang; Liu, Jianzheng; Gar On Yeh, Anthony; Yue, Yang; Li, Weifeng (2015). "The Uncertain Geographic Context Problem in Identifying Activity Centers Using Mobile Phone Positioning Data and Point of Interest Data". Advances in Geographic Information Science: 107–119. doi:10.1007/978-3-319-19950-4_7.
  5. ^ Matthews, Stephen A. (2017). International Encyclopedia of Geography: People, the Earth, Environment and Technology: Uncertain Geographic Context Problem.
  6. ^ a b Openshaw, Stan (1983). The Modifiable Aerial Unit Problem (PDF). GeoBooks. ISBN 0-86094-134-5.
  7. ^ a b Chen, Xiang; Ye, Xinyue; Widener, Michael J.; Delmelle, Eric; Kwan, Mei-Po; Shannon, Jerry; Racine, Racine F.; Adams, Aaron; Liang, Lu; Peng, Jia (27 December 2022). "A systematic review of the modifiable areal unit problem (MAUP) in community food environmental research". Urban Informatics. 1. doi:10.1007/s44212-022-00021-1. S2CID 255206315. Retrieved 27 December 2022.
  8. ^ a b Monmonier, Mark (10 April 2018). How to lie with maps (3 ed.). University of Chicago Press. ISBN 978-0226435923.
  9. ^ Gao, Fei; Kihal, Wahida; Meur, Nolwenn Le; Souris, Marc; Deguen, Séverine (2017). "Does the edge effect impact on the measure of spatial accessibility to healthcare providers?". International Journal of Health Geographics. 16. doi:10.1186/s12942-017-0119-3. Retrieved 4 January 2023.{{cite journal}}: CS1 maint: unflagged free DOI (link)
  10. ^ Allen, Jeff (2019). "Using Network Segments in the Visualization of Urban Isochrones". Cartographica: The International Journal for Geographic Information and Geovisualization. 53 (4): 262–270. doi:10.3138/cart.53.4.2018-0013.
  11. ^ Thrift, Nigel (1977). An Introduction to Time-Geography (PDF). ISBN 0 90224667 4.
  12. ^ Tobler, Waldo (2004). "On the First Law of Geography: A Reply". Annals of the Association of American Geographers. 94 (2): 304–310. doi:10.1111/j.1467-8306.2004.09402009.x. S2CID 33201684. Retrieved 10 March 2022.
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