Uncertain geographic context problem

 

  • [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.

  • [6][7]
    Suggested solutions
    Geographic information systems, along with technologies that can monitor the position of individuals in real time, are possible methods for addressing the UGCoP.

  • [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.

  • [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.

  • Tobler’s second law of geography states, “the phenomenon external to a geographic area of interest affects what goes on inside.

  • [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.

  • [2][15] These technologies have helped to address the problem by moving away from aggregate data and introducing a temporal component to the modeling of subject activity.

  • [2] Web GIS has also been employed to address the UGCoP by allowing researchers to better contextualize subjects’ real and perceived activity space.

 

Works Cited

[‘1. 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. ^ Jump up to:a b c d e f g h i 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. ^ Jump up to:a b Openshaw, Stan (1983). The Modifiable Aerial Unit Problem (PDF). GeoBooks. ISBN 0-86094-134-5.
5. ^ Jump up to:a b c d 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. ^ Jump up to:a b c d 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. ^ Jump up to: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): 1734–1737. doi:10.2105/AJPH.2015.302792. PMC 4539815. PMID 26180982.
8. ^ Jump up to:a b 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. ^ Jump up to:a b 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.
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. ^ Jump up to:a b c 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.
16. ^ Tobler, Waldo (1999). “Linear pycnophylactic reallocation comment on a paper by D. Martin”. International Journal of Geographical Information Science. 13 (1): 85–90. Bibcode:1999IJGIS..13…85T. doi:10.1080/136588199241472.
17. ^ Franch-Pardo, Ivan; Napoletano, Brian M.; Rosete-Verges, Fernando; Billa, Lawal (2020). “Spatial analysis and GIS in the study of COVID-19. A review”. Sci Total Environ. 739: 140033. Bibcode:2020ScTEn.73940033F. doi:10.1016/j.scitotenv.2020.140033. PMC 7832930. PMID 32534320. S2CID 219637515.
18. ^ Ge, Haoxuan; Wang, Jue (January 2023). “Spatial Non-Stationarity Effects of Unhealthy Food Environments and Green Spaces for Type-2 Diabetes in Toronto”. Sustainability. 15 (3): 1762. doi:10.3390/su15031762.
19. ^ Jump up to:a b Monmonier, Mark (10 April 2018). How to lie with maps (3 ed.). University of Chicago Press. ISBN 978-0226435923.
Photo credit: https://www.flickr.com/photos/aidanmorgan/2256214682/’]