Uncertain geographic context problem

The uncertain geographic context problem or UGCoP is a source of statistical bias that can significantly impact the results of spatial analysis when dealing with aggregate data.[1][2][3] The UGCoP is very closely related to the Modifiable areal unit problem (MAUP), and like the MAUP, arises from how we divide the land into areal units.[4][5] 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][6] 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.[2] Examples of research that needs to consider the UGCoP include food access and human mobility.[7][8]

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.[9]

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.[5] 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.[4][5] While a particular enumeration unit, such as a census tract, contains a person's location, they may cross its boundaries to work, go to school, and shop in completely different areas.[10][11] Thus, the geographic phenomena under investigation extends beyond the delineated boundary .[6][12][13] Different individuals, or groups may have completely different activity spaces, making an enumeration unit that is relevant for one person meaningless to another.[7][14] For example, a map that aggregates people by school districts will be more meaningful when studying a population of students than the general population.[15] Traditional spatial analysis, by necessity, treats each discrete areal unit as a self-contained neighborhood and does not consider the daily activity of crossing the boundaries.[1][2]

  1. ^ a b c d 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. S2CID 52024592.
  2. ^ a b c d Kwan, Mei-Po (2012). "How GIS can help address the uncertain geographic context problem in social science research". Annals of GIS. 18 (4): 245–255. Bibcode:2012AnGIS..18..245K. doi:10.1080/19475683.2012.727867. S2CID 13215965. Retrieved 4 January 2023.
  3. ^ Matthews, Stephen A. (2017). International Encyclopedia of Geography: People, the Earth, Environment and Technology: Uncertain Geographic Context Problem. Wiley. doi:10.1002/9781118786352.wbieg0599.
  4. ^ a b Openshaw, Stan (1983). The Modifiable Aerial Unit Problem (PDF). GeoBooks. ISBN 0-86094-134-5.
  5. ^ a b c 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 (1): 22. Bibcode:2022UrbIn...1...22C. doi:10.1007/s44212-022-00021-1. S2CID 255206315.
  6. ^ a b 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 (1): 46. doi:10.1186/s12942-017-0119-3. PMC 5725922. PMID 29228961.
  7. ^ a b 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): 1734–1737. doi:10.2105/AJPH.2015.302792. PMC 4539815. PMID 26180982.
  8. ^ 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 Spatial Data Handling and Analysis. Advances in Geographic Information Science. pp. 107–119. doi:10.1007/978-3-319-19950-4_7. ISBN 978-3-319-19949-8.
  9. ^ 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. S2CID 133986477.
  10. ^ Zhao, Pengxiang; Kwan, Mei-Po; Zhou, Suhong (2018). "The Uncertain Geographic Context Problem in the Analysis of the Relationships between Obesity and the Built Environment in Guangzhou". International Journal of Environmental Research and Public Health. 15 (2): 308. doi:10.3390/ijerph15020308. PMC 5858377. PMID 29439392.
  11. ^ Zhou, Xingang; Liu, Jianzheng; Yeh, Anthony Gar On; 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 Spatial Data Handling and Analysis. Advances in Geographic Information Science. pp. 107–119. doi:10.1007/978-3-319-19950-4_7. ISBN 978-3-319-19949-8. Retrieved 22 January 2023.
  12. ^ Cite error: The named reference Tobler1 was invoked but never defined (see the help page).
  13. ^ Salvo, Deborah; Durand, Casey P.; Dooley, Erin E.; Johnson, Ashleigh M.; Oluyomi, Abiodun; Gabriel, Kelley P.; Van Dan Berg, Alexandra; Perez, Adriana; Kohl, Harold W. (June 2019). "Reducing the Uncertain Geographic Context Problem in Physical Activity Research: The Houston TRAIN Study". Medicine & Science in Sports & Exercise. 51 (6S): 437. doi:10.1249/01.mss.0000561808.49993.53. S2CID 198375226.
  14. ^ Thrift, Nigel (1977). An Introduction to Time-Geography (PDF). Geo Abstracts, University of East Anglia. ISBN 0-90224667-4.
  15. ^ Shmool, Jessie L.; Johnson, Isaac L.; Dodson, Zan M.; Keene, Robert; Gradeck, Robert; Beach, Scott R.; Clougherty, Jane E. (2018). "Developing a GIS-Based Online Survey Instrument to Elicit Perceived Neighborhood Geographies to Address the Uncertain Geographic Context Problem". The Professional Geographer. 70 (3): 423–433. Bibcode:2018ProfG..70..423S. doi:10.1080/00330124.2017.1416299. S2CID 135366460. Retrieved 22 January 2023.